A partnership with academia

Building knowledge for trade and development

Vi Digital Library - Text Preview

Enterprising Women : Expanding Economic Opportunities in Africa

Book by Hallward-Driemeier, Mary, World Bank, 2013

Download original document (English)

The book looks at the ways to expand women entrepreneurs’ economic opportunities in Sub-Saharan Africa. What explains the gender sorting in the types of enterprises that women and men run? The analysis shows that many Sub-Saharan countries present a challenging environment for women. Four key areas of the agenda for expanding women’s economic opportunities in Africa are analyzed: strengthening women’s property rights and their ability to control assets; improving women’s access to finance; building human capital in business skills and networks; and strengthening women’s voices in business environment reform.



Enterprising
Women






Enterprising
Women


Mary Hallward-Driemeier


A copublication of the Agence Française de Développement and the World Bank


Expanding Economic
Opportunities in Africa




© 2013 International Bank for Reconstruction and Development / Th e World Bank
1818 H Street NW, Washington DC 20433
Telephone: 202-473-1000; Internet: www.worldbank.org


Some rights reserved
1 2 3 4 16 15 14 13


Th is work is a product of the staff of Th e World Bank with external contributions. Note that Th e World
Bank and the Agence Française de Développement do not necessarily own each component of the
content included in the work. Th e World Bank and the Agence Française de Développement therefore
do not warrant that the use of the content contained in the work will not infringe on the rights of third
parties. Th e risk of claims resulting from such infringement rests solely with you.


Th e fi ndings, interpretations, and conclusions expressed in this work do not necessarily refl ect the
views of Th e World Bank, its Board of Executive Directors, or the governments they represent, or the
Agence Française de Développement. Th e World Bank does not guarantee the accuracy of the data
included in this work. Th e boundaries, colors, denominations, and other information shown on any
map in this work do not imply any judgment on the part of Th e World Bank concerning the legal status
of any territory or the endorsement or acceptance of such boundaries.


Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges
and immunities of Th e World Bank, all of which are specifi cally reserved.


Rights and Permissions


Th is work is available under the Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
http://creativecommons.org/licenses/by/3.0. Under the Creative Commons Attribution license, you are
free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the
following conditions:
Attribution—Please cite the work as follows: Hallward-Driemeier, Mary. 2013. Enterprising Women;


Expanding Economic Opportunities in Africa. Africa Development Forum series. Washington, DC:
World Bank. doi:10.1596/978-0-8213-9703-9. License: Creative Commons Attribution CC BY 3.0


Translations—If you create a translation of this work, please add the following disclaimer along with
the attribution: Th is translation was not created by Th e World Bank and should not be considered
an offi cial World Bank translation. Th e World Bank shall not be liable for any content or error in this
translation.


All queries on rights and licenses should be addressed to the Offi ce of the Publisher, Th e World Bank,
1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org.


ISBN (paper): 978-0-8213-9703-9
ISBN (electronic): 978-0-8213-9809-8
DOI: 10.1596/978-0-8213-9703-9


Cover photo: Maasai women make, sell, and display their bead work in Kajiado, Kenya. 2010.
© Georgina Goodwin/World Bank. Cover design: Debra Naylor, Naylor Design Inc.
Library of Congress Cataloging-in-Publication Data
Hallward-Driemeier, Mary, 1966–
Enterprising women : expanding economic opportunities in Africa / Mary Hallward-Driemeier.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-8213-9703-9 — ISBN 978-0-8213-9809-8 (electronic)
1. Women—Africa, Sub-Saharan—Economic conditions. 2. Women—Africa, Sub-Saharan—Social
conditions. 3. Businesswomen—Africa, Sub-Saharan. 4. Women—Employment—Africa, Sub-Saharan.
I. Title.
HQ1788.H35 2013
331.4096—dc23


2012049861




v


Africa Developme nt Forum Series


Th e Africa Development Forum series was created in 2009 to focus on issues of
signifi cant relevance to Sub-Saharan Africa’s social and economic development.
Its aim is both to record the state of the art on a specifi c topic and to contrib-
ute to ongoing local, regional, and global policy debates. It is designed specifi -
cally to provide practitioners, scholars, and students with the most up-to-date
research results while highlighting the promise, challenges, and opportunities
that exist on the continent.


Th e series is sponsored by the Agence Française de Développement and
the World Bank. Th e manuscripts chosen for publication represent the high-
est quality in each institution and have been selected for their relevance to the
development agenda. Working together with a shared sense of mission and
interdisciplinary purpose, the two institutions are committed to a common
search for new insights and new ways of analyzing the development realities of
the Sub-Saharan Africa region.


Advisory Committee Members


Agence Française de Développement
Rémi Genevey, Director of Strategy
Alain Henry, Director of Research


World Bank
Shantayanan Devarajan, Chief Economist, Africa Region
Santiago Pombo-Bejarano, Editor-in-Chief, Offi ce of the Publisher




Sub-Saharan Africa


ZIMBABWE


ANGOLA


BURUNDI


RWANDA


CHAD


NIGER


UGANDA KENYA


SOMALIA


ETHIOPIA


ERITREASUDAN


SOUTH
SUDAN


CENTRAL
AFRICAN REPUBLIC


CONGO


NIGERIA


TOGO


SENEGAL


LIBERIA


SIERRA LEONE


GUINEA


CÔTE
D’IVOIRE


GUINEA-BISSAU


DEMOCRATIC
REPUBLIC
OF CONGO


SOUTH
AFRICA


LESOTHO


SWAZILAND


BOTSWANA


ZAMBIA


MOZAMBIQUE
MADAGASCAR


COMOROS


SEYCHELLES


MALAWI


TANZANIA


NAMIBIA


MAURITIUS


CAMEROON


GABON


EQUATORIAL GUINEA


SÃO TOMÉ AND PRÍNCIPE


MALI


BENIN
BURKINA FASO


MAURITANIACAPE
VERDE


THE GAMBIA


GHANA


Réunion
(Fr.)


Mayotte
(Fr.)


IBRD
39088




vii


Titles in the Africa Development Forum Series


Africa’s Infrastructure: A Time for Transformation (2010) edited by Vivien Foster
and Cecilia Briceño-Garmendia


Gender Disparities in Africa’s Labor Market (2010) edited by Jorge Saba Arbache,
Alexandre Kolev, and Ewa Filipiak


Challenges for African Agriculture (2010) edited by Jean-Claude Deveze
Contemporary Migration to South Africa: A Regional Development Issue (2011)
edited by Aurelia Segatti and Loren Landau


Light Manufacturing in Africa: Targeted Policies to Enhance Private Investment
and Create Jobs (2012) by Hinh T. Dinh, Vincent Palmade, Vandana Chandra,
and Frances Cossar


Informal Sector in Francophone Africa: Firm Size, Productivity, and Institutions
(2012) by Nancy Benjamin and Ahmadou Aly Mbaye


Financing Africa’s Cities: Th e Imperative of Local Investment (2012) by Th ierry
Paulais


Structural Transformation and Rural Change Revisited: Challenges for Late
Developing Countries in a Globalizing World (2012) by Bruno Losch, Sandrine
Fréguin-Gresh, and Eric Th omas White


Th e Political Economy of Decentralization in Sub-Saharan Africa: A New
Implementation Model (2013) edited by Bernard Daffl on and Th ierry Madiès
Empowering Women: Legal Rights and Economic Opportunities in Africa (2013)
by Mary Hallward-Driemeier and Tazeen Hasan


Urban Labor Markets in Sub-Saharan Africa (2013) edited by Philippe De
Vreyer and François Roubaud


Securing Africa’s Land for Shared Prosperity: A Program to Scale Up Reforms and
Investments (2013) by Frank F. K. Byamugisha


Free access to all titles in the Africa Development Forum series is available at
https://openknowledge.worldbank.org/handle/10986/2150






ix


Contents


Foreword xxi
Preface xxiii
About the Author xxv
Acknowledgments xxvii
Abbreviations xxix


Overview 1


Why Seek to Improve Women’s Opportunities? 2
Why Focus on Sub-Saharan Africa? 3
Part I. Mapping Women’s and Men’s Entrepreneurial Activities 4
Part II. Understanding Sorting 8
Part III. Expanding Opportunities for Women Entrepreneurs 10
Part IV. Toward an Action Agenda 19
Notes 22
References 23


Part I Where Women and Men Work 27


1 Self-Employed, Employers, and Wage Earners in
the Formal and Informal Sectors 29


Gender Patterns in Entrepreneurship: Laying Out the Facts 30
Gender Diff erences in Labor Force Participation by Region 34
Entrepreneurship: Sub-Saharan Africa in a Global Context 36
Notes 44
References 45




X CONTENTS


2 The Size, Formality, and Industry of Enterprises 47


Enterprise Size 51
Enterprise Formality 53
Enterprise Industry 54
Notes 61
References 61


Part II Why Women Work Where They Do 63


3 Effect of Country Patterns in Income, Human Capital,
and Assets on Where Women Work 65


Th e Importance of Income: A Cross-Country Perspective 66
Cross-Country Patterns of Entrepreneurship: Human Capital (Literacy) and
Access to Assets (Property Rights) 71
Link between Entrepreneurship and Access to Human Capital and Assets 81
Notes 87
References 88


4 Sorting into Entrepreneurial Activities: Individual Patterns 91


Choice 1: Participating in the Nonagricultural Labor Force 94
Choice 2: Becoming an Entrepreneur (Self-Employed or Employer) 95
Choice 3: Formal or Informal Sector 102
Choice 4: Line of Business 110
Notes 115
References 115


Part III How Women Perform—and
the Constraints They Face 119


5 How Sorting Affects Gender Gaps in Productivity
and Profi ts 121


Productivity and Gender Gaps 123
Country Characteristics’ Eff ect on Potential Gender Gaps 127
Notes 129
References 130




CONTENTS XI


6 How Sorting Affects Constraints 133


Constraints Facing Entrepreneurs 135
Infl uence of Constraints on Employment Category 141
Notes 153
References 154


Part IV Shifting Women to More Productive Work 157


7 Increasing the Right to Own and Control Assets 159


Regulations, Formal Law, and Practice 162
Focus of Women–LEED–Africa 163
Main Findings from Women–LEED–Africa 166
Gaps between Principle and Practice 174
Th e Way Forward 174
Notes 177
References 177


8 Expanding Women’s Access to Finance 181


Sub-Saharan Africa in a Global Context 182
Individuals’ Access to Finance 187
Access to Finance: A Barrier to Entry? 194
Financing New Businesses: Access to Loans aft er Start-Up 197
Entrepreneurial Choice Limited by Access to Finance 198
Notes 203
References 203


9 Enriching Managerial and Financial Skills 207


Managerial Skills 209
Financial Skills 212
Entrepreneurial Skills: Experience and Motivation 214
What Kind of Entrepreneurial Training Is Eff ective—And for Whom? 216
Exploiting Synergies between Human and Financial Capital 218
Notes 218
References 219




XII CONTENTS


10 Strengthening Women’s Voices in Business-
Environment Reforms 221


Why Focus on Women’s Voices? 222
Grounding Policy Advocacy in Gender-Informed Analysis 223
Women and Business Associations 224
Bringing Women into Public-Private Dialogue 231
Notes 238
References 239


11 Toward an Action Agenda 241


Reforming the Business Environment 241
Increasing Women’s Right to Own and Control Assets 242
Expanding Women’s Access to Finance 243
Enriching Managerial and Financial Skills 244
Strengthening Women’s Voices in Business-Environment Reform 245
Areas for Research 245
Notes 246
References 246


Appendix A: Sources of Data 249


Appendix B: Indexes of Gender Equality across Countries 257


Appendix C: Comparing Women–LEED–Africa and Its Peers 261


Index 263


Boxes


O.1 Strengthening Women’s Property Rights Aff ects Opportunities
Pursued 14


1.1 Expanding Opportunities 30
1.2 Types of “Work” 31
1.3 Primary Sources of Data Used in Th is Book 33
1.4 How to Capture Gender Gaps 42
2.1 How to Designate “Female” and “Male” Enterprises:


Ownership, Control, or a Mixture? 48
3.1 Strengthening Women’s Property Rights Aff ects the Opportunities


Women Pursue 87
4.1 Choice of Activity—Externally Constrained or Internally


Preferred? 92




CONTENTS XIII


4.2 Strengthening Data Collection 93
4.3 Motivation: Necessity or Opportunity? 96
4.4 Entrepreneurship: An Opportunity Th at Varies with Income


and Education 99
4.5 Scale of Enterprise 105
4.6 Relationship between Education and Work Experience 108
4.7 Do Entrepreneurs’ Reported Criteria for Success Refl ect Eff ort


and Performance? 112
5.1 Gender Gaps in Labor Productivity and in Firm Size Can Rise


with Income 128
7.1 Earlier Research on the Impact of Property Rights on Economic


Opportunities 160
7.2 A Step Back: A Kenyan Court’s Ruling on Dividing Marital


Property 175
7.3 Recommendations for Closing Gaps in Legal and Economic


Rights 176
8.1 A Review of the Literature on Women’s Access to Finance 183
8.2 Alternative Finance for Women in Sub-Saharan Africa 188
8.3 Expanding Access to Finance for Female Entrepreneurs—


Insights from the Supply Side 188
10.1 Uganda Gender Coalition: Using Gender Analysis to Lobby


for Change 225
10.2 Th e Africa Businesswomen’s Network: Amplifying


Women’s Voices 228
10.3 National Association of Business Women in Malawi:


Creating a Grassroots Advocacy Program 229
10.4 Resources for Country-Level Advocacy 231
10.5 Public-Private Dialogue for Investment-Climate Reform 232
10.6 Keys to Eff ective Public-Private Dialogue 235
10.7 Guiding Questions on Gender in Public-Private Dialogue and


Business-Environment Reforms 237


Figures


O.1 Women and Men Are Economically Active in Diff erent Types of
Employment, with Women’s Labor Force Participation Highest in
Sub-Saharan Africa 4




XIV CONTENTS


O.2 Female Self-Employment Falls with Country Income, but the Share
of Employers Is Stable 6


O.3 Controlling for Enterprise Characteristics Removes the Gender
Gap in Productivity (registered fi rms) 7


O.4 Education Varies More by Sector Formality Th an by Gender 11
O.5 Gender Gaps in Legal Rights Remain in Sub-Saharan Africa—and


Do Not Necessarily Close with Countries’ Income 12
O.6 Male Formal Entrepreneurs Had More Start-Up Capital Th an


Other Groups 15
B1.2.1 Typology of Employment Status Categories 31
1.1 Women’s Participation Rates Are Highest in Sub-Saharan Africa 35
1.2 Sub-Saharan Africa Has the Biggest Diff erence between Women’s


Overall Labor Force Participation and Women’s Nonagricultural
Labor Force Participation 36


1.3 Women’s Nonagricultural Self-Employment Rate Is Highest in
Sub-Saharan Africa 38


1.4 Th e Sub-Saharan Africa Region Leads in the Share of
Nonagricultural Self-Employed Who Are Women 38


1.5 Globally, Far Fewer Entrepreneurs Are Employers Th an Are
Self-Employed 39


1.6 Th e Share of Female Employers Is Lower Th an for
Self-Employment, but with Very Similar Rates for Five
of the Six Regions 40


1.7 Of All Regions, Sub-Saharan Africa Has the Lowest Rate and
Widest Gender Gap for Wage Employment 41


1.8 Th e Regions Show a Wide Variation in the Share of Female
Wage Earners 41


B1.4.1 Gender Gap in Self-Employment 42
B1.4.2 Gender Gap in Being an Employer 43
B1.4.3 Gender Gap in Wage Workers 43
B1.4.4 Degree of Correlation in Self-Employed and Employers 44
B2.1.1 Up to Half of Firms with Some Female Ownership Are Not Run


by Women 48
B2.1.2 Share of Formal Female Firms in Sub-Saharan Africa 49
2.1 Firms with Some Female Ownership Are Smaller in Sub-Saharan


Africa Th an in Other Regions 52




CONTENTS XV


2.2 Th e Gender Ownership Gaps with Other Regions Are Smaller
for Sole Proprietorships Th an for All Firms 52


2.3 Women’s Firms Are Smaller Th an Men’s (aft er controls for labor
intensity) 53


2.4 Informal Firms in Sub-Saharan Africa Are Oft en Female Run 54
2.5 More Male-Owned Firms Are Registered—but with


No Clear Diff erence in the Gender Gaps between the
Self-Employed and Employers 55


2.6 In Sub-Saharan Africa, Female-Owned Firms Are More
Concentrated Th an Men’s in Lower-Value-Added Industries
(formal sector) 57


2.7 Th e Degree of Formality Is a Good Predictor of Women’s
Participation in an Industry 58


2.8 Retail, Food, and Textiles Attract Female Entrepreneurs 59
3.1 Initially, the Share of Women Not in the Labor Force Rises


Steeply with Country Income 67
3.2 Th e Share of Men Not in the Labor Force Shows Little Change


as Country Income Climbs 67
3.3 Th e Share of Women in Nonagricultural Employment Changes


Little as Country Income Rises 68
3.4 Female Self-Employment Falls with an Increase in Country


Income (nonagricultural employment) 69
3.5 Male Wage Earners Gain as Income Improves


(nonagricultural employment) 70
3.6 Women Account for around a Quarter of Employers, Irrespective


of Country Income (nonagricultural employment) 70
3.7 Indicators of Equality and Opportunity Vary, but Most Show


Sub-Saharan Women in a Challenging Environment 72
3.8 Th e Correlation Is High between Low Levels of Women’s Literacy


and Large Gender Gaps in Literacy 76
3.9 Variation beyond Literacy Remains aft er GDP per


Capita Is Controlled for (using indicators from
international organizations) 77


3.10 Th e Distribution of Income Is Very Similar across Countries
with Weaker and Stronger Rights for Women 79


3.11 Th e Distribution of Female Literacy Is Very Similar across
Countries with Weaker and Stronger Rights for Women 80




XVI CONTENTS


3.12 Gender Gaps in Literacy Are Correlated with Patterns
in Self-Employment 82


3.13 Gender Gaps among Employers Are Sensitive to Gaps
in Women’s Economic and Legal Rights 84


3.14 More Women Become Wage Earners Where Gaps in Literacy
and Legal Rights Are Smaller 85


3.15 Stronger Literacy Closes the Employer–Self-Employed
Participation Gap 86


3.16 Stronger Literacy Shows Virtually No Employer–Wage Earner
Participation Gap for Women 86


B4.3.1 Th e Reason for Starting a Business Varies Little by Gender
or Formality 96


B4.3.2 Gender Plays Some Role among Necessity Entrepreneurs
in the Formal Sector 97


B4.4.1 Gaps in Education for Female Wage Earners versus
Female Self-Employed Rise as the Share of Women
in Self-Employment Rises 99


B4.4.2 Gap in Education for Wage Earners versus Employers
Is Higher for Women Th an Men 100


4.1 Self-Employed Women Are the Least Educated among Male
and Female Entrepreneurs 101


4.2 Where Married Women Have Fewer Economic Rights,
Employers Are More Likely to Be Divorcees or Widows:
Th e Case of Swaziland 102


4.3 Education Varies More by Sector Formality Th an by Gender 103
4.4 Women Entrepreneurs Tend to Be Younger Th an Th eir Male


Colleagues—Particularly in the Formal Sector 104
B4.5.1 Managers’ Education Is More Strongly Correlated with


Business Size Th an Managers’ Experience 105
4.5 Diff erences in Prior Experience Are Greater between the


Sectors Th an between Genders within Sectors 107
B4.6.1 Education and Work Experience Are Linked 108
4.6 Married People Predominate among New Entrepreneurs 109
4.7 Very Few Enterprises Are Set Up from Existing Outfi ts 110
4.8 New Businesses Started by Women Average Less Capital and


Fewer Initial Employees—Regardless of Whether the Business
Was Acquired or a Start-Up 111




CONTENTS XVII


B4.7.1 New Entrepreneurs’ Criteria for Success Diff er Only Slightly by
Gender and Registration Status 112


4.9 Prior Experience, New Market Opportunities, and Inspiring
Cases Prompt Entrepreneurs to Select Th eir Line of Business 113


4.10 Both Opportunities and Constraints Play a Role in New
Entrepreneurs’ Decision Not to Pursue Other Business Lines 114


5.1 Controlling for Enterprise Characteristics Removes the Gender
Gap in Productivity (registered fi rms) 123


5.2 New Entrepreneurs in the Formal Sector Have
Signifi cantly Higher Revenue per Worker Th an Th eir
Informal Counterparts 124


5.3 New Entrepreneurs’ Median Revenue per Worker Is Higher for
Women Th an Men in the Formal Sector 125


5.4 Median Revenue per Worker Trends Higher in Formal Sector
Industries 125


5.5 Median Revenue per Worker Tends to Be Lower in Sectors with
Greater Female Ownership 126


B5.1.1 Th e Sector-Selection Eff ects of Average Firm Size Appear
Greatest in More-Developed Countries 128


5.6 Gender Gaps in Revenue per Worker Are Aff ected by
Country Characteristics 129


6.1 Do Women Face Greater Constraints? Many Women—and
Men—Th ink So 136


6.2 Obstacles Vary More by Formality and Size of Firm Th an
by Gender (subjective responses) 137


6.3 Obstacles Facing Sole Proprietors Show Somewhat Larger
Diff erences by Gender (subjective responses) 139


6.4 Obstacles to Doing Business Vary More by Size Th an Gender
(quantitative responses) 142


6.5 Obstacles Vary More by Industry Th an Gender
(quantitative responses) 144


6.6 Male Formal Entrepreneurs Are Far More Likely to Have
Loans Th an Other Groups 146


6.7 Male Formal Entrepreneurs Had More Start-Up Capital
Th an Other Groups 147


6.8 Formality and Gender Aff ect the Time Managers Spend with
Offi cials 148




XVIII CONTENTS


6.9 Formal Firms Are Much More Likely to Make “Gift s” Th an
Informal Firms 149


6.10 Formal Entrepreneurs Believe Th ey Know How Big Th eir
“Gift s” Should Be 150


6.11 Many Formal Entrepreneurs Believe Th at Th eir “Gift s” Will
Achieve Th eir Purpose 150


6.12 Formal Firms Are More Likely to Pay for Protection Th an
Informal Firms—but Pay Less for It 151


6.13 Formal Entrepreneurs Believe Th ey Know How Big
Th eir Payments for Protection Should Be 151


6.14 Many Formal Entrepreneurs Believe Th at Th eir Payments for
Protection Will Achieve Th eir Purpose 152


6.15 When Women Borrow Money or Engage in Other Business
Transactions, Th ey May Be Asked for Sexual Favors 153


7.1 All Sub-Saharan Constitutions Enshrine the Principle of
Nondiscrimination, and Most Enshrine Gender Equality 167


7.2 Almost All Sub-Saharan Countries Are Signatories to at
Least Some International Conventions on Nondiscrimination 167


7.3 Th e Constraints Placed on Customary Law in Upholding
Nondiscrimination Vary across Countries 168


7.4 Head-of-Household Rules Provide Several Ways Husbands Can
Control Th eir Wife’s Assets 169


7.5 Inheritance Is One of the Main Ways Women Can Acquire and
Control Property—But Such Rights Vary 171


7.6 Not All Land Laws Recognize Women’s Right to Own Land 172
7.7 Restrictions on Women’s Hours and Type of Work Vary 173
8.1 Sub-Saharan Africa Lags in Access to Formal Finance,


Including Bank Accounts, Credit Lines, and Loans 185
8.2 Sub-Saharan Africa Lags in Access to Formal External Finance 186
8.3 A High Degree of Financial Exclusion Exists across Eastern


and Southern Africa 191
8.4 New Entrepreneurs Depend Primarily on Th eir Own,


or on Friends’ and Relatives’, Resources 195
8.5 Sector Matters More Th an Gender in Start-Ups’ Access to Formal


Finance—Although Some Gender Gaps Appear in the Informal
Sector 196




CONTENTS XIX


8.6 Strong Gender and Formality Diff erences Come through
for the Few New Entrepreneurs with Loans 198


8.7 Sources of Loan Guarantees Vary by Sector Formality 199
8.8 Of Firms with External Start-Up Financing, Commercial


Banks Are the Main Source of Capital for Formal Firms 200
8.9 With Twice the Money at Start-Up, Nearly All Entrepreneurs


Would Have Done Th ings Diff erently 201
8.10 Credit Constraints Appear to Be Common Among


Sub-Saharan Entrepreneurs 202
9.1 Th e Eff ect of Education on Productivity Is the Same for


Women as for Men 210
9.2 Whether Business Objectives Are Recorded in Writing Varies


Primarily by Sector and Only Secondarily by Gender 212
9.3 Formal Records Are More Likely to Be Kept among Formal


Enterprises, with Little Gender Gap 213
10.1 Public-Private Dialogue Enlarges the Reform Space 233


Tables


8.1 Once Education and Experience Are Controlled for,
Women Are No More Likely Th an Men to Use Formal
Financial Services 193


A.1 Microdata Used 251
A.2 Principal Data Sources, Uses, and Limitations 253






xxi


Foreword


Women’s economic empowerment is critical for development. Th e international
community recognizes that this agenda is important—and that more needs to
be done to further it. Expanding opportunities for women is of intrinsic value.
It is also instrumental in fostering development; realizing the potential of all
people is needed in order to ensure growth, productivity, and a vibrant society.
Enterprising Women: Expanding Economic Opportunities in Africa analyzes new
data from 41 countries in Sub-Saharan Africa to provide practical recommen-
dations on how to help more women move into higher-return activities.


Women entrepreneurs are a signifi cant resource in Sub-Saharan Africa. Th eir
eff orts and investments contribute to higher living standards for themselves and
their families. More women are already economically active in Sub-Saharan
Africa than in any other region. But these women too oft en operate in the
informal sector, in small fi rms, and in traditional sectors where profi ts and
opportunities for expansion are more limited. Th ey are not fully able to realize
their potential.


Th is book shows how economic empowerment for women is particularly
needed in Sub-Saharan Africa. Entrepreneurship can refl ect choices and the
pursuit of opportunities, but it can also refl ect necessity and a lack of alterna-
tive options. Sub-Saharan Africa has the world’s lowest nonagricultural wage
employment, oft en the alternative to entrepreneurship—and demonstrates the
largest gender gaps of any region.


Improving the prospects of existing businesses is part of the solution. And
addressing constraints in the investment climate that burden informal and
smaller enterprises will disproportionately benefi t women. But the larger goal is
to enable more women to shift the nature of what they do. Th is book outlines a
four-part agenda that can provide more women with the incentives and abilities
to run larger enterprises in the formal sector in higher-value-added industries.


Four sources of gender gaps need to be closed. Th e fi rst regards human
capital; gender gaps in education in Sub-Saharan Africa still remain, and
business training and access to networks are too oft en geared toward men.




XXII FOREWORD


Th e second involves ownership and control of assets. Th e companion to this
volume, Empowering Women: Legal Rights and Economic Opportunities in
Africa, demonstrates the extent of gender gaps in formal economic rights and
the practical constraints to accessing justice. Th ese fi rst two gaps aff ect the third
source of gender gaps: access to fi nance. With less control over collateral and
less education and training, women are seen as less attractive borrowers, and
hence are more restricted in the type of activities they can pursue. Lastly, there
is a gap in voice. Women need to be included at the table when policy reforms
are being designed and prioritized.


Th is book provides examples from countries across the region of how to
achieve success. Th e data show the gender patterns across types of entrepre-
neurial activities—but they are not uniform. Variations in these patterns and
analyses of reforms show how shift ing conditions make a diff erence. More
indeed can be done, and this book provides a roadmap of how to do it.


Ngozi Okonjo-Iweala
Coordinating Minister of Economy and


Minister of Finance for the Federal Republic of Nigeria




xxii i


Preface


Th is book is about expanding nonfarm entrepreneurship opportunities for
women in Sub-Saharan Africa. It examines the extent of gender diff erences
in economic activities pursued by female and male entrepreneurs, and the
returns they receive. It uses substantial new microevidence to examine where
and why gender gaps appear in the size, formality, and sector of women’s and
men’s enterprises, and the implications of these gaps for the performance of
these businesses. It analyzes the factors that help explain these outcomes, so
as to provide an agenda for expanding economic opportunities for women.
Key themes include the need to address continued gender gaps in access to
human capital and in access to and control of assets, and the need to increase
the effi cacy and authority of women’s voices in shaping improvements in the
business environment.


Th e book does not aim to provide a full analysis of labor markets in Africa. It
puts entrepreneurship in the broader patterns of labor market participation to
show the importance of entrepreneurship relative to other economic activities
and to demonstrate how gender patterns across employment categories in Sub-
Saharan Africa diff er from those in other regions in the world. It also explores
how prior work experience aff ects the choice of entrepreneurial activity. It
does not, however, explore directly the relative benefi ts of wage employment
versus entrepreneurship; nor does it examine individuals’ transitions across
employment categories.


Th e analysis uses many sources of microdata—household, labor force, and
enterprise surveys—to examine the full spectrum of entrepreneurial activities,
disaggregated by gender. Appendix A provides more details about each data
source and the countries covered by each type of data. Th e text and fi gures
indicate which data source is used in discussing the various results. Household
and labor force surveys provide information on entrepreneurs, particularly
those in the informal sector, the self-employed, and those running micro- and
small enterprises. Th e enterprise surveys focus primarily on formal fi rms with
employees and upper-end, market-based informal enterprises. Th e analysis




XXIV PREFACE


pays particular attention to the higher end of this spectrum—that is, larger
and market-based informal fi rms and registered fi rms, as these are both where
opportunities are greatest and where gender gaps are largest. Explanations for
the patterns documented include factors external to the enterprises, such as the
legal framework and investment climate, and the background and education
of the entrepreneurs themselves. Th e book examines entrepreneurs’ household
characteristics where available, but a full analysis of intrahousehold bargaining
or a larger time-use analysis is beyond its scope. In compiling and analyzing
new microdata and original research on 41 countries in Sub-Saharan Africa, it
provides valuable new insights, and it also makes recommendations on how to
expand economic opportunities for the region’s women entrepreneurs.




xxv


About the Author


Mary Hallward-Driemeier is a lead economist and adviser to the Chief
Economist of the World Bank. She has published articles on entrepreneurship,
fi rm productivity, the impact of the investment climate on fi rm performance,
the impact of fi nancial crises, and determinants of foreign direct investment.
She was the deputy director for World Development Report 2005: A Better
Investment Climate for Everyone. Mary helped establish the World Bank’s
Enterprise Surveys Program, now covering more than 100,000 enterprises in
100 countries. She is also a founding member of the Microeconomics of Growth
Network and is co-leading the Jobs Knowledge Platform. She received her MS
in development economics from Oxford University as a Rhodes Scholar and her
PhD in economics from the Massachusetts Institute of Technology.






xxvii


Acknowledgments


Th e principal author of this book is Mary Hallward-Driemeier. Th e book was
written with the important contributions and assistance of colleagues in the
World Bank. Ousman Gajigo oversaw the new survey work conducted for this
book and coauthored the background paper analyzing the results across fi rm
sectors, sizes, and registration status. Alejandro Rasteletti coauthored the back-
ground work on household employment dynamics and household enterprises,
building on the database assembled by Claudio Montenegro. Mark Blackden
contributed substantially to chapter 10 on public-private dialogue as well as
other chapters, and provided invaluable assistance with his introductions to
key local partners, his gift for moderating workshops, and his push to enlarge
the scope of the work. Tazeen Hasan, Jane Kamangu, and Emilia Lobti col-
lected information on the formal legal economic rights of women in the region
and assembled the Women’s Legal and Economic Empowerment Database for
Africa (Women-LEED-Africa database) discussed in chapters 3 and 7, which
also serves as the basis for the companion volume, Empowering Women: Legal
Rights and Economic Opportunities in Africa. Reyes Aterido, Th orsten Beck,
and Leo Iacovone provided the background work on household and indi-
vidual access to fi nance that contributed to chapter 8. Manju Shah used the
World Bank’s Enterprise Surveys to provide useful inputs on patterns across
formal enterprises and microenterprises.


Insightful comments and suggestions were provided by participants in
the workshops in Addis Ababa, Cape Town, Dakar, and Nairobi as well as
Washington, DC, with participants from Cameroon, the Democratic Republic
of Congo, Ethiopia, Th e Gambia, Ghana, Kenya, Malawi, Mali, Nigeria, Rwanda,
Senegal, South Africa, Sudan, Tanzania, and Uganda. Particular thanks are given
to Reena Badiani, Elena Bardasi, Laura Chioda, Aline Coudouel, Susan Deller
Ross, Asli Demirgüç-Kunt, Shanta Devarajan, Louise Fox, Anne Goldstein,
Markus Goldstein, Benjamin Herzberg, Sarah Iqbal, Sandra Joireman, Maureen
Lewis, Andrew Mason, Ana Maria Munoz Boudet, Pierella Paci, Rita Ramalho,
Ana Revenga, Bob Rijkers, Carolina Sanchez-Paramo, Sudhir Shetty, and




XXVIII ACKNOWLEDGMENTS


Sevi Simavi for their comments and suggestions. Th e text benefi ted from the
editorial services of Bruce Ross-Larson.


Financial support from the Dutch BNPP Trust Fund, Gender Action Plan,
and Africa Chief Economist Regional Studies Program is gratefully acknowl-
edged, as is the additional support from the World Bank’s Finance and Private
Sector Development Chief Economist Offi ce, Finance and Private Sector
Development Africa Department, and Research Department. Th e study was
carried out under the overall guidance of Marilou Uy, Director for Finance and
Private Sector Development in Africa, and Shanta Devarajan, Chief Economist
for the Africa Region.




xxix


Abbreviations


GDP gross domestic product
IFC International Finance Corporation
ILO International Labour Organization
OECD Organisation for Economic Co-operation and Development
PPD public-private dialogue






1


Overview


Th is book brings together new household and enterprise data from 41 countries
in Sub-Saharan Africa to inform policy makers and practitioners about ways
to expand women entrepreneurs’ economic opportunities. Women’s empow-
erment is recognized as the third Millennium Development Goal; in 2012
the World Bank dedicated its annual fl agship, the World Development Report,
to gender equality and development (World Bank 2011); and the Nobel
Prize for Peace was awarded to three pioneering women (two from Liberia)
working  for peace in their countries’ fi ghts for democracy and for greater
opportunities for women.


Th is book focuses attention on Sub-Saharan Africa, and specifi cally on
entrepreneurship in the nonagricultural sector. Th e issue of gender disparities
in economic opportunities in the region has been studied in terms of gaps in
wage income and in job sorting in wage work (Arbache, Kolev, and Filipiak
2010; Fafchamps, Söderbom, and Benhassine 2009; Kolev and Sirven 2010).
Other cross-country work has looked at entrepreneurship in Sub-Saharan
Africa, but rarely with much attention paid to gender (Bigsten and Söderbom
2006; Tybout 2000; World Bank 2004). But entrepreneurship is where women
in Sub-Saharan Africa are most active outside of agriculture. So it is critical
to look at entrepreneurship to understand the extent of gender disparities in
economic opportunities, determine the underlying reasons for these gender
patterns, and develop an agenda to enable more women to realize their full
potential.


Th is book contributes new empirical analysis in four parts.
Part I analyzes gender-disaggregated patterns of entrepreneurship in


Sub-Saharan Africa and compares them with patterns elsewhere. Th e highest
share of women entrepreneurs in the world is found in Sub-Saharan Africa, but
the women are disproportionately self-employed rather than employers. Relative
to men, women are pursuing lower-opportunity activities, with their enterprises
more likely to be smaller, informal, and in low-value-added lines of business
(see, for example, Bigsten and others 2003; ILO 2002; Liedholm and Mead 1999;




2 ENTERPRISING WOMEN


McPherson 1996; Mead and Liedholm 1998; Parker 2004; Sinha and Kanbur
2012). Th e challenge in expanding opportunities is not helping more women
become entrepreneurs, but enabling them to shift to higher-return activities.


What explains the gender sorting in the types of enterprises that women and
men run—that is, why do more women operate smaller, informal, and low-value-
added enterprises? Part II shows that many Sub-Saharan countries present a chal-
lenging environment for women (Bardasi, Blackden, and Guzman 2007). Two
dimensions of particular importance for entrepreneurs are access to and control
over assets, and the quality of human capital. Recent data from Sub-Saharan
Africa show that gender gaps along both these dimensions are still common,
and that they are associated with the gender patterns in being self-employed and
being an employer, as discussed in part I. More-detailed investigations into the
characteristics of entrepreneurs—their age, marital status, educational attain-
ment, prior work experience, and motivation for being an entrepreneur—further
explain variations in the types of business that women and men run.


Gender sorting across types of enterprises signifi cantly shapes economic
opportunities. Where women and men work helps explain much of the gender
gap in average productivity. Part III demonstrates that women’s productivity is
lower not because of their gender but because informal, smaller fi rms are less
productive—and more women run these types of businesses. Among similar
types of enterprises, little systematic gender gap is apparent in productivity or
fi rm growth. A similar fi nding holds for constraints: they vary far more by type
of enterprise than by gender (with some exceptions for dealing with red tape,
getting start-up capital, and suff ering from harassment).


Part IV examines four key areas of the agenda for expanding women’s eco-
nomic opportunities in Africa: strengthening women’s property rights and abil-
ity to control assets, improving their access to fi nance, building human capital
in business skills and networks, and strengthening women’s voices in business-
environment reform. Th ese areas are important both because they have wide
gender gaps and because they help explain gender diff erences in entrepreneurial
activities.


Why Seek to Improve Women’s Opportunities?


Th ere are several reasons why it is important to improve opportunities for
women entrepreneurs in Sub-Saharan Africa. First, simple fairness requires
letting all individuals make their own decisions in critical areas of their lives
and pursue opportunities equally. Second, realizing women’s contributions to
economic activities has an instrumental value—it unleashes the potential of
all members of society and spills over to others in the household, particularly
girls. Th ird, action will be needed to close many of the gender gaps mentioned




OVERVIEW 3


above; economic development alone is not enough to ensure women’s access to
legal and economic rights or participation in policy decisions. True, gender gaps
in education tend to close with higher incomes, but gaps in women’s property
rights do not. Such gaps are as common in middle-income countries as low-
income countries in Sub-Saharan Africa, so simply raising a country’s income
will not give women equal ability to control assets (Hallward-Driemeier and
Hasan 2012). Th is fi nding helps explain why the share of female employers in
a country is associated with equality of economic rights in the country and not
with the country’s income.


Why Focus on Sub-Saharan Africa?


Women in the region have fewer alternatives to entrepreneurship than
do women in other regions. Self-employment is higher in Sub-Saharan
Africa, and wage employment is lower, than in any other region. But these
metrics also have a stark gender dimension. Th is is the only region where
women’s self-employment is more common than their wage employment
(see fi gure O.1), and the gender gap in the share of wage employment is the
highest in the world. If wage employment is less of an option for women in
Sub-Saharan Africa, it is more important for entrepreneurial opportunities
to be fruitful—and for women to be able to pursue them to the same degree
as men.


Aggregate country data on gender equality and women’s empower-
ment suggest that many women in Sub-Saharan Africa face a particularly
challenging environment. Disparities in education and property rights
remain very high—higher than in most other regions. Gaps in formal eco-
nomic rights are oft en reinforced by the role of customary law and practice.
Many countries in the region have multiple and overlapping legal systems
that make women’s economic rights less secure. Th ese gender gaps weaken
women’s abilities and incentives to start and run the types of enterprises asso-
ciated with better outcomes—that is, enterprises with higher productivity
and profi ts.


Access to fi nance is systemically a larger issue for businesses in Sub-Saharan
Africa (whether run by males or females) than it is in other regions. Th e
region’s businesses are 40 percent less likely than those elsewhere to have any
formal fi nancial access. Although gender patterns in access to fi nance among
formal fi rms with fi ve or more employees are not that signifi cant, the share of
female entrepreneurs running such fi rms is signifi cantly lower than the overall
share of female entrepreneurs. Diff erences in access to start-up capital could
be particularly important in explaining some of the gender sorting across types
of enterprises.




4 ENTERPRISING WOMEN


Part I. Mapping Women’s and Men’s Entrepreneurial
Activities


Both men and women are active in the labor force and in entrepreneurship, but
there are important diff erences in the types of activities they engage in (fi gure O.1).
Women are far more likely to be in self-employment, as opposed to being employ-
ers or wage workers. Within entrepreneurship, the share of women who are
employers remains fairly constant across countries sorted by income level, while
the share of women in self-employment falls with income (fi gure O.2a). Looking
within employment categories at the share of women, the share of employers who
are women is similarly fairly constant even as income grows ( fi gure O.2b). Within
Sub-Saharan Africa, which dominates the right-hand side of the graphs, half of
the self-employed are women, yet only a quarter of employers are women.


Female entrepreneurs are, unsurprisingly, not distributed uniformly across
all industries. Th is uneven distribution has important ramifi cations because—
as with whether an enterprise is formal or informal (“formality”)1— industries
diff er in their size, profi tability, and opportunities for growth. Women, particu-
larly women microentrepreneurs, are more likely than men to be in services


Figure O.1 Women and Men Are Economically Active in Different Types of Employment,
with Women’s Labor Force Participation Highest in Sub-Saharan Africa


0


10


20


30


40


50


60


70


80


Pe
rc


en
ta


ge
o


f f
em


al
e


po
pu


la
ti


on


a. Where women work


Su
b-S


ah
ara


n


Af
ric


a


Ea
st


As
ia


an
d


Pa
cifi


c


Mi
dd


le
Ea


st


an
d N


ort
h A


fric
a


So
uth


As
ia


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d


the
Ca


rib
be


an




OVERVIEW 5


and in traditional lower-value-added sectors such as the garment and food-
processing sectors. Th ey are also less likely to be registered. Men are more
likely to be in metals and other manufacturing. So, among those who are
entrepreneurs, women are more likely than men to be running small informal
fi rms in lower-value-added sectors.


Expanding women’s economic opportunities is thus not so much about
expanding entrepreneurship itself; rather, it involves tackling constraints
to women’s abilities and incentives to expand their business and move into
higher-value-added activities.


Enterprise performance is markedly aff ected by size, formality, and the line
of business. Using value added per worker as the base measure of performance
for a sample of 37 countries in Sub-Saharan Africa with available data, we fi nd
that women and men have a gender gap in labor productivity of about 6 percent.
But aft er analysis controls for the size and line of business, and for the entrepre-
neur’s education, these gaps shrink and, depending on formality, can disappear
altogether. Particularly among registered enterprises, gender in itself does not


0


10


20


30


40


50


60


Pe
rc


en
ta


ge
o


f m
al


e
po


pu
la


ti
on


b. Where men work


Su
b-S


ah
ara


n


Af
ric


a


Ea
st


As
ia


an
d


Pa
cifi


c


Mi
dd


le
Ea


st


an
d N


ort
h A


fric
a


So
uth


As
ia


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d


the
Ca


rib
be


an


Employer Self-employed Wage worker


Agricultural worker Labor force nonparticipantUnpaid worker


Source: National household and labor force surveys for 101 low- and middle-income countries, most recent
years (2000–10).


Figure O.1 (continued)




6 ENTERPRISING WOMEN


0


20


40


60


80


6 7 8 9 10


Pe
rc


en
ta


ge
o


f w
om


en
in



no


na
gr


ic
ul


tu
ra


l l
ab


or
fo


rc
e


GDP per capita (log)


a. Where women work


Self-employed


Wage workers


Unpaid family workers


Employers


20


40


30


50


6 7 8 9 10


Pe
rc


en
ta


ge
t


ha
t


is
fe


m
al


e


GDP per capita (log)


b. Female share within employment category


Self-employed Wage workersEmployers


Figure O.2 Female Self-Employment Falls with Country Income, but the Share of
Employers Is Stable


Source: National household and labor force surveys for 101 low- and middle-income countries, most recent
years (2000–10).
Note: GDP = gross domestic product. Analysis excludes agriculture.




OVERVIEW 7


account for productivity diff erences. Instead, gender gaps exist because women
account for such a small share of entrepreneurs in the formal sector (fi gure O.3).


Th e way “female ownership” is defi ned also aff ects results: the gender gap in
performance is larger with a narrower defi nition that stresses who controls the
business rather than who owns it (since a business may be owned by more than
one person, not all of whom have the same role in making major decisions regard-
ing the business). If enterprises with female minority owners who do not have
decision-making power are classifi ed as female owned, the data may obscure gaps
between the genders. Th e eff ect is signifi cant because in almost half of the enter-
prises that have multiple owners, at least one of whom is female, women are not
among the decision makers. In the non-household-based informal sector, other
enterprise and entrepreneur characteristics account for most of the productiv-
ity gap. Th e type of enterprise where gender gaps persist, even controlling for other
characteristics, is informal home-based enterprises. Diff erences in hours of opera-
tion seem to account for much of these gaps (data are scarce, however).


Aft er controlling for other key enterprise characteristics—ensuring that
one is comparing like with like—it is encouraging to fi nd no or few signifi cant
diff erences in performance for female and male entrepreneurs. Th e fi nding


Figure O.3 Controlling for Enterprise Characteristics Removes the Gender Gap in
Productivity (registered firms)


–6 –4 –2 0 2


Size of enterprise, sector, capital intensity


Control for size of enterprise


Control for sector


No controls


Percentage of gender gap in average firm labor productivity


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on regressions using data from 37 Sub-Saharan African countries, with country dummies
included to capture country-invariant effects. Thus the results are all based on within-country differences.
A dummy is included for whether there is female participation in ownership.




8 ENTERPRISING WOMEN


confi rms that Sub-Saharan Africa has considerable hidden growth potential
in its women, and that tapping that potential—including improving women’s
choices of where to be active economically—can make a real contribution to
the region’s growth. Th is fi nding also underscores the need for policy makers to
understand where diff erences exist in the obstacles that men and women face,
and why the observed patterns of entrepreneurship persist.


As with performance, once the characteristics of the enterprise are controlled
for, diff erences in obstacles faced by men’s and women’s businesses are not
signifi cant. Th at is, gender gaps are largely explained once enterprise character-
istics are taken into account. Th us for businesses of similar sizes and in similar
industries, women and men report similar constraints. For example, if accessing
land is harder for women than for men, it is mainly because small fi rms report
this as a greater constraint—and women are more likely to be in smaller fi rms.


Th ree caveats apply, however. First, how “female ownership” is defi ned aff ects
the fi ndings, as pointed out above. Second, data are not available to analyze
properly how constraints aff ect the entry decision—or the size, formality, and
line of business. So, although we can look at the eff ects of gender within fi rm
size categories and conclude that size is more important than gender, we cannot
determine to what extent gender diff erences explain why women are more likely
to run smaller fi rms. Lastly, focus groups revealed that some challenges facing
female entrepreneurs are diff erent in kind (not just degree) from those facing
men. For example, women found that the “gift s” sought by some suppliers,
moneylenders, and offi cials went beyond the fi nancial to include the sexual.


Part II. Understanding Sorting


Th e greater concentration of women in smaller fi rms, in the informal sector, and
in traditional industries is important because these three dimensions are correlated
with opportunity. Larger and formal enterprises in higher-value-added lines of
business tend to be more productive and more profi table (Ayyagari, Beck, and
Demirgüç-Kunt 2007; Tybout 2000; World Bank 2012)—although, again, the
gender dimension is not examined in detail in the existing fi rm-level work on
Sub-Saharan Africa (Bigsten and Gebreeyesus 2007; Bigsten and Söderbom 2006;
Sleuwaegen and Goedhuys 2002; Söderbom 2012; Van Biesebroeck 2005). Hence it
is important to look at gender gaps across these three dimensions and to examine
why these gender-diff erentiated patterns of entrepreneurial activity exist in diff erent
countries. With gender patterns in the types of entrepreneurial activity largely driv-
ing gender diff erences in the returns to entrepreneurship, the relevant issues are
why women and men undertake diff erent economic activities, and whether they
do so through choice or necessity (see Klapper and Parker [2010] and Minniti
[2009] for reviews of the broader literature beyond just Sub-Saharan Africa).




OVERVIEW 9


Both country characteristics (income, measures of the business environment,
human capital, and property rights) and individual characteristics ( education,
marital status, age, prior work experience) are examined to understand their
impact on gender sorting and gender gaps in fi rm performance. At the country
level, many gender gaps are associated with a country’s income, but income
alone does not explain everything. Not all gaps close with income, most impor-
tantly gender gaps in property rights, which are discussed below. And some
country characteristics have an independent eff ect on gender gaps in fi rm per-
formance, even taking income into account; these characteristics include the
quality of governance, extent of corruption, political stability, and rule of law.
Better governance is generally associated with better private sector outcomes,
and better governance shows a mild gender eff ect in that the gender gap in fi rm
performance is smaller in better-governed countries.


Other aggregate measures of women’s empowerment developed by
international organizations suggest that women in Africa (Sub-Saharan Africa
and the Middle East and North Africa) face a particularly challenging environ-
ment. Indeed, countries with weaker institutions of gender inclusion or equality
tend to have slightly wider gender gaps in performance. But because many of
these aggregate measures add little information beyond what is available from
country income data, this study turns to measures of gender inequality that
are more relevant to entrepreneurship and that are not simply correlated with
income: human capital and property rights aff ecting access to assets.


As a proxy for human capital, the study examines adult literacy, since this
measure captures an important skill for the full working-age population better
than current enrollment rates, which measure the potential of the future labor
force. For a measure of property rights, the study uses the Women’s Legal and
Economic Empowerment Database for Africa (Women–LEED–Africa) devel-
oped in the companion volume.2 It groups countries in the region based on the
strength of key legal rights for women—rights that indicate whether women
have the same legal capacity as men to make independent contractual arrange-
ments and whether they have the same rights to own and control property.
Th ese rights are important because gender gaps persist precisely in these legal
areas. Th ey are also important because such rights aff ect not only the ability to
open a business, secure collateral, and make contracts, but also the ability to
keep the earnings of the business. Th us they aff ect the very incentive to be an
entrepreneur.


Grouping countries on the two dimensions of gender gaps in human capital
and economic rights sends an important message to policy makers. First, it
shows that women’s legal capacity and rights are not correlated with country
income. Changes will require active political engagement. Second, it shows
that gender gaps in these rights are of considerable importance for women’s
entrepreneurial opportunities. While larger gaps in literacy are generally




10 ENTERPRISING WOMEN


associated with larger shares of women being self-employed, greater legal
protection for women is associated with women having more opportunity to
become employers. With higher literacy, women are more likely to partici-
pate in a wider range of business lines, including higher-value-added sectors.
In low-literacy countries, women’s nonagricultural activities are much more
highly concentrated in services than even in simple manufacturing.


From the perspective of individuals, several key (usually sequential) choices
are involved in determining the type of entrepreneur one is likely to become.3
First there is the decision to participate in the nonagricultural labor force, then
to become an entrepreneur rather than a wage earner, then to operate in the
formal or informal sector. Finally there is the choice of the line of business and
scale of enterprise.


Both household and enterprise surveys show that education is a key deter-
minant in these choices, with smaller roles played by prior work experience,
marital status, age, and relevant business skills. Gender gaps in education have
been closing over time, but for middle-aged women and men they are sub-
stantial in many countries. Th us lower educational attainment for women, and
particularly for middle-aged women, is a large reason why more women operate
in smaller fi rms and in the informal sector. It is striking, however, that there
are large diff erences in educational attainment between those in the informal
and formal sectors, but little gender diff erence in education levels within each
sector (fi gure O.4).


Prior work experience is also important. Indeed, entrepreneurship-related
experience can be a bigger determinant of productivity than general formal
education, even at the tertiary level. For its part, marital status (for women)
determines legal standing, property rights, and the ability to engage in business.


Part III. Expanding Opportunities for Women
Entrepreneurs


Th e analysis addresses four factors vital for expanding opportunities for women
entrepreneurs in Sub-Saharan Africa. Th e fi rst is women’s access to and con-
trol of assets and resources required for entrepreneurship, which are aff ected
by gender diff erences in legal capacity and property rights, particularly where
married women are concerned. Th e second is education and experience, which
are important drivers of economic choice, opportunity, and performance.
Th e third is limited access to fi nance, which is a key obstacle to business devel-
opment. Th e fourth is women’s limited opportunities for networking and exclu-
sion from decision-making bodies and from policy dialogue, which (especially
in the business environment) mean that business-climate reforms rarely tackle
issues for women entrepreneurs.




OVERVIEW 11


Increasing Women’s Right to Own and Control Assets
Women—especially married women—oft en have lower legal status and fewer
property rights than men. Women–LEED–Africa shows that business regula-
tions rarely have gender-diff erentiated provisions. But their impact in practice
may not be gender neutral if women face greater time constraints, have more
limited mobility, face cultural restrictions on the transactions they can engage
in, or are perceived as soft er targets for harassment. Consequently, gender-
neutral or gender-blind regulations do not necessarily translate into gender
equality in economic rights.


Other areas of the law beyond business regulations are critical in assessing
whether women may face greater obstacles to running a business. Th e laws
that also matter include those that frame people’s economic rights, such as
family law governing marriage, divorce, and inheritance, and laws governing
land rights and labor markets. Th ese laws, rather than business regulations,
determine whether women and men can make economic decisions in their
own name, or whether there are restrictions on their ability to enter con-
tracts or to own, administer, transfer, or inherit assets and property. Family
law, seldom addressed in programs to improve the business environment,
shapes the business environment for women. Marital status, and the capaci-
ties and  limitations associated with it, determine women’s eff ective property


Figure O.4 Education Varies More by Sector Formality Than by Gender


0


20


40


60


80


100


Male Female Male Female


Formal


Pe
rc


en
t


Informal


Degree Some university education Vocational training


Primary school No schoolingSecondary school


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.




12 ENTERPRISING WOMEN


rights and economic autonomy, so that they are oft en markedly diff erent from
men’s.


Yet it is precisely these areas of the law that show gender diff erences the
most. Laws in these areas are oft en granted formal exemption from countries’
nondiscrimination provisions and are commonly subject to overlapping
legal systems in Sub-Saharan Africa, with many constitutions and statutes
explicitly recognizing marriage, inheritance, and property as domains where
formal customary or personal law applies (fi gure O.5). Th ese exemptions
are  important because diff erences in men’s and women’s legal rights con-
tribute substantially to the region’s gender-diff erentiated entrepreneurship
patterns: women are more likely to sort into self-employment in countries
with weaker legal rights and to become employers in countries with stronger
legal rights.


Practical constraints, including distance, cost, language, and bias, further
shape the ability to exercise formal economic rights, with important gender-
diff erentiated eff ects. Equally, much of the population has little to do with the
formal legal system—nor do people have much knowledge of the legal protections
it aff ords. Particularly in areas with lower incomes, lower levels of education, or
strong customary traditions—or areas that are more rural—people rarely see the
formal system as relevant for securing economic rights. Customary law, instead,
plays a signifi cant role, both as a formal source of law and as an infl uence on
informal practice, touching the lives of the majority of the population in much of
Sub-Saharan Africa (Tamanaha, Sage, and Woolcock 2012).


Figure O.5 Gender Gaps in Legal Rights Remain in Sub-Saharan Africa—and Do Not
Necessarily Close with Countries’ Income


0


25


50


75


100


Low-
income


countries


Pe
rc


en
ta


ge
o


f c
ou


nt
ri


es


Middle-
income


countries


Low-
income


countries


Middle-
income


countries


Middle-
income


countries


Low-
income


countries


Low-
income


countries


Middle-
income


countries


Man is head of
household


Husband chooses
matrimonial home


a. Head-of-household rules


Husband’s
permission


needed to open
bank account


Husband can
oppose wife's


exercise of
trade or profession


Statutes were not foundLaw affirmsNo such law




OVERVIEW 13


Figure O.5 (continued)


Sources: Hallward-Driemeier and Hasan 2012; M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and
E. Lobti, Women’s Legal and Economic Empowerment Database.
Note: Figures are based on all 47 Sub-Saharan African countries.


0


10


20


30


40


50


60


70


80


90


100


Low-income countries Middle-income countries


Pe
rc


en
ta


ge
o


f c
ou


nt
ri


es


Constitution does not recognize customary law


Constitution recognizes customary law—and
exempts it from nondiscrimination requirements


Constitution recognizes customary law—and
limits its ability to discriminate based on gender


b. Constitutional recognition of customary law


As the companion volume discusses in more detail (see Hallward-Driemeier
and Hasan 2012), three key messages on women’s legal status emerge from the
Women–LEED–Africa database. First, the principle of nondiscrimination is
recognized in all countries—in constitutions or treaties they have signed (or
both). But formal exceptions are widespread: despite recognizing nondiscrimi-
nation as a guiding principle of law, many countries’ statutes still discriminate.


Second, many of the discriminatory provisions women face apply not to
women as women, but to women as married women. From a legal standpoint,
marriage changes, in some cases radically, the legal status and rights of women,
oft en conferring legal capacities and responsibilities on husbands and remov-
ing them from wives. Th is change in women’s legal status applies particularly to
property regimes, to rights in and aft er marriage, and to rules aff ecting women’s
economic capacity and decision making within marriage (fi gure O.5b).


Th ird, the treatment of women’s economic rights is not closely related to
a country’s level of income or development (see fi gure O.5). Simply raising
national income is unlikely to improve women’s legal and economic rights—
more interventionist reforms will be needed. Some countries have expanded
national income even with gaps in women’s economic rights, while others, with




14 ENTERPRISING WOMEN


strong protection against discrimination, have not. Of course, the legal frame-
work is not the only determining factor. But the strength of legal protections
clearly aff ects women’s economic opportunities, particularly their ability to
move out of self-employment and to run larger enterprises (see box O.1).


Expanding Women’s Access to Finance
Entrepreneurs’ access to fi nancial services is crucial for three main reasons. It is key
for securing access to productive resources (internal resources are rarely suffi cient
for growth). It can smooth cash fl ow. And, in the other direction, it matters for
savings (particularly if other members of the household may divert resources).


Access to fi nance is a particularly pressing constraint in Sub-Saharan Africa:
fewer than one in fi ve households has access to formal fi nancial services. It is
a systemic issue for businesses (male or female owned), which are substan-
tially less likely than their peers in other regions to have any formal fi nancial
access. Larger companies, however, still have an advantage in accessing fi nancial
services (Bigsten and others 2003).


An analysis of individual entrepreneurs strongly suggests that women’s
lower levels of access to formal fi nancing are explained by gender diff erences
in income, education, and employment status. Women are more prominent in
borrowing informally and are more likely to be excluded from formal fi nancial
services (Fafchamps 2000). Aft er controlling for individuals’ education and
experience, the gender gap in accessing formal fi nance is largely explained,


BOX O.1


Strengthening Women’s Property Rights Affects
Opportunities Pursued
Ethiopia changed its family law in 2000, raising the minimum age of marriage for
women, removing the ability of the husband to deny permission for the wife to work
outside the home, and requiring both spouses’ consent in the administration of marital
property. While this reform now applies across the country, it was initially rolled out in
three of the nine regions and two chartered cities. Using two nationally representa-
tive household surveys, one in 2000 just prior to the reform and one fi ve years later,
we were able to carry out a difference-in-difference estimation of the impact of the
reform. Five years later, we fi nd a signifi cant shift in women’s economic activities. In
particular, women’s relative participation in occupations that require work outside the
home, full-time work, and higher skills rose relatively more where the reform had been
enacted (controlling for time and location effects).


Source: Hallward-Driemeier and Gajigo 2011.




OVERVIEW 15


although results can vary by country (Aterido, Beck, and Iacovone, forth coming;
de Mel, McKenzie, and Woodruff 2009).


Beyond acting as a potential constraint to the growth of a business, how
much does access to fi nance have a gender dimension as a barrier to entry?
Certainly among newly started enterprises, women’s businesses have less access
to fi nance than men’s. Th is gender diff erence is strongly associated with the
respective nature of their businesses (fi gure O.6). Th e data, though inconclusive,
suggest that prior to becoming entrepreneurs, women have more limited access,
consistent with their starting smaller and less-capital-intensive fi rms, which are
then less likely to get external fi nance once they are running.


Enterprises that are run by women who have successfully entered the for-
mal sector do not seem more fi nancially constrained than enterprises run by
men. Access to fi nancial resources depends more on the size and nature of the
fi rm than on the gender of the manager. But because women have such a small
proportion of large formal fi rms—precisely those with more access to fi nance—
indirect gender dynamics may be at work in access to fi nance.


0


0.5


1.0


1.5


2.0


2.5


3.0


3.5


4.0


4.5


0


2


4


6


8


10


12


14


16


Male Female Male Female


Formal Informal


St
ar


ti
ng


n
um


be
r


of
p


ai
d


w
or


ke
rs


(i
nc


lu
di


ng
o


w
ne


r)


M
ed


ia
n


st
ar


t-
up


c
ap


it
al


(U
S$


t
ho


us
an


ds
)


Start-up capital Start-up workforce


Figure O.6 Male Formal Entrepreneurs Had More Start-Up Capital Than Other Groups


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.




16 ENTERPRISING WOMEN


Enriching Managerial and Financial Skills
Th e positive eff ect of education on enterprise productivity, for women and men,
is one of the most robust fi ndings in the literature (Mead and Liedholm 1998;
Parker 2004; World Bank 2004, 2012). Th is study’s analysis also shows that
education is a signifi cant determinant of revenue per worker in enterprises.
Education can also signal other qualities such as discipline, motivation, and
versatility in dealing with new challenges (Blau 1985; Parker and van Praag
2006; Van der Sluis, van Praag, and Vijverberg 2008).


Specifi cally, entrepreneurs with at least secondary education and some
vocational training have signifi cantly higher revenue per worker than those
with no education. Primary education has no higher productivity eff ect over
no schooling. Th e diff erences in productivity associated with higher education
are not statistically diff erent for women and men. Although women in general
may have less education, those who are educated obtain more benefi t from it by
running more productive fi rms than do their male counterparts.


Four management techniques had a signifi cant eff ect on productivity
among fi rms sampled in fi ve countries (Bloom and Van Reenen 2007, 2010).
Gender diff erences were not apparent for two techniques (formal objectives
and monitoring of employee performance) but were apparent in the other two
(process innovation and participatory decision making). Male entrepreneurs
scored signifi cantly higher than female entrepreneurs in process innovation,
but the reverse was true in participatory decision making.


Education and management quality seem to have important eff ects, and
women can benefi t from them as much as men—although results can also
depend on broader business environment conditions (Bruhn and Zia 2011;
Bruhn, Karlan, and Schoar 2010; de Mel, McKenzie, and Woodruff 2009;
Mansuri and Giné 2011). Experience—through previous employment in the
formal sector, exposure to running a business, or having had a parent who
was an entrepreneur—also counts (Aterido and Hallward-Driemeier 2011;
Djankov and others 2007). Th e fact that there is a gender gap in the last area
suggests that women are less exposed to the experience of business in general,
and lack the role models and opportunities for networking available to their
male counterparts. It also suggests that as more women become successful
entrepreneurs, and as more women have the opportunity to network and
to make their voices heard in the enterprise sector, a virtuous cycle may be
created that will boost the human capital of the next generation of women
entrepreneurs.


Strengthening Women’s Voices in Business Environment Reforms
Despite the active involvement of women as entrepreneurs in Sub-Saharan
Africa, women are rarely at the table when business-related policies are
discussed, and the issues facing businesswomen as opposed to businessmen




OVERVIEW 17


are rarely debated or addressed in policy-making forums. Women are largely
excluded from policy making in the private sector and from the mechanisms
and instruments used to promote dialogue between the public and private
sectors. So although in the private sector women are important economic actors
in their own right, they lack comparable representation in policy-making and
decision-making institutions.


Women need to be active in business environment reform, not only because
they are strongly involved as entrepreneurs, but also because the obstacles and
constraints they face, and the perspectives they bring, can be and oft en are quite
diff erent from those of their male counterparts. As indicated earlier, women
are more likely to operate in the informal sector and be engaged in smaller
and lower-value-added sectors. Even where men’s and women’s businesses
share similar characteristics, women are likely to have diff erent experiences
of legal, regulatory, and administrative barriers to business than their male
counterparts.


Business associations, including those focusing on women’s businesses,
provide an important platform for promoting women’s business interests. But
women are oft en poorly represented in mainstream business associations. Many
women’s business associations are not centrally involved in mainstream dia-
logue and advocacy—and lack the capacity and experience to pursue their work
eff ectively. Th is study identifi es some useful experiences of promoting business-
women’s associations, and some important new initiatives to amplify the voices
of women entrepreneurs in policy making and in investment-climate reform.
Th e recent establishment of the Africa Businesswomen’s Network is a case in
point.


Women consistently raise as challenges their lack of voice in decision making,
the absence of opportunities for networking, the lack of appropriate role models
and mentors, and the lack of business skills. In some countries there are additional
challenges to increasing women’s involvement with business associations. Cultural
and social imperatives can discourage women from mixing freely with men, espe-
cially those from outside their families. In such circumstances, the presence of
a specialized women’s business association makes sense. Such networks provide
women business owners with support. Th ey also help spread new business ideas,
facilitate making business contacts, and provide avenues for larger-scale market-
ing and distribution.


Th e eff ectiveness of women’s voices will depend in part on the extent to
which there are solid gender-informed and sex-disaggregated analyses available
to inform policy making. Advocacy for policy reforms needs to be grounded
in solid country-specifi c analysis of the opportunities and constraints in the
business environment—and, specifi cally, of the ways they diff er for men and
women. A gender-informed analysis of investment-climate obstacles provides
the essential underpinning needed to identify, and advocate for, needed legal




18 ENTERPRISING WOMEN


and regulatory reforms. In recent years, there have been several country-specifi c
gender-focused analyses of investment-climate obstacles in Africa. Drawing on
broader analysis of the legal environment and links between gender inequal-
ity and economic growth, these assessments focused on regulatory and
administrative barriers to business registration, operation, and closing; business
licensing and taxation; access to land and fi nance; access to justice; and issues of
concern in particular sectors. Th e studies identifi ed gender-based diff erences in
application of business regulations, and proposed regulatory reforms to address
them (see Simavi, Manuel, and Blackden 2010).


In parallel, recent studies capturing the voices of women entrepreneurs
in Africa provide valuable insights into how women perceive the busi-
ness environment and what obstacles and challenges they face. Th ey reveal
both the importance attached to networking and the problems women face
in participating eff ectively in associations and networks. Th ese problems
make the task of developing new opportunities, building a customer base,
and expanding markets all the more diffi cult. Consistent across all countries
are issues associated with balancing work and family obligations, the com-
plexity of (and the time involved in complying with) regulations, the higher
probability that women will be the subject of harassment and discrimination
by public servants and offi cials in positions of power, and the problems with
access to fi nance already mentioned.


Any approach to bringing more women to the table, and to ensuring that
issues important to women are on the agenda, needs to address the under-
lying questions of whether it is better for women to work through parallel
structures focused on women, or to seek stronger integration into “main-
stream” mechanisms of policy dialogue and business associations. Th at is,
is it better to encourage more women’s business associations, or to promote
greater female participation within existing business associations? A related
question is whether eff orts should focus on issues specifi c to women in busi-
ness (a gender perspective) or should expand the ways in which women par-
ticipate in, and contribute to, advocacy on issues that are not gender-specifi c
but are of importance to business more generally. Th e study suggests that
there is no simple answer—and that in many instances a dual-track approach,
involving both separate women’s mechanisms and better integration into the
mainstream, is required.


Investment-climate reform that enables women, as well as men, to become
more eff ective participants in business and in stimulating economic develop-
ment must address challenges faced by both men and women. Th is approach
is more likely to be followed if women are full participants in policy dis-
cussions and reform eff orts. One mechanism examined here is the process
of public- private dialogue (PPD), supported by the International Finance
Corporation. PPD is regarded as an important means of enlarging the “reform




OVERVIEW 19


space” by ensuring greater inclusion of stakeholders in reform deliberations
and facilitating greater local ownership of reform measures (Herzberg and
Wright 2006). While early eff orts did not include a focus on gender inclusion,
PPD programs now promote greater gender inclusion and make space for
identifying and tackling business environment issues of particular interest
to women.


Policy makers, researchers, and members of the development community
are paying more attention to understanding and addressing the gender dimen-
sions of the business environment, and developing practical steps to tackle
gender issues in investment climate reform. Th e importance of evidence-
based research and analysis, as the foundation for eff ective lobbying for policy
change, cannot be overstated, and this study aims to fi ll some important gaps
in this area. It is still necessary to persuade policy makers and practitioners that
addressing women’s issues in business is important in its own right—and that
doing so can have valuable payoff s for the business sector and the economy as
a whole.


Part IV. Toward an Action Agenda


Th is book outlines policy reforms that can improve women’s opportunities for
entrepreneurship in Africa and enable women to engage in larger, formally
registered businesses in higher-value-added areas.


Reforming the Business Environment
Reforming the business environment expands opportunities for growth, higher
productivity, and employment—for all. Broader reforms, such as improving
the infrastructure, tax administration, and regulations, are likely to benefi t
both women and men. Th e extent of indirect gender eff ects depends on the
types of enterprises that benefi t most from reform. For example, lift ing con-
straints on smaller fi rms and encouraging formalization should help women
disproportionately.


Constraints to entrepreneurship that aff ect women more than men—as the
analysis here shows, they are strongest in areas of property rights, access to
fi nance, and harassment—reduce half the population’s potential to participate
and compete equally in productive activities, thereby lowering aggregate eco-
nomic growth. Th ey have a broader eff ect on stunting competitive pressures,
lowering innovation, and cutting aggregate productivity growth, particularly
if they distort fi nancial markets, so that capital is not allocated to the most
productive activities. And they restrict higher-potential women’s enterprises the
most. Th us there is an intrinsic and instrumental case for removing gender-
based constraints to entrepreneurship.




20 ENTERPRISING WOMEN


Increasing Women’s Right to Own and Control Assets
Th e Women–LEED–Africa database shows in which countries and in which
areas of the law reforms are still needed to close gender gaps in legal capacity and
property rights. To close these gaps, governments need to ratify, “domesticate,”
and then enforce international treaties and conventions, including the Maputo
Protocol, the Convention on the Elimination of all Forms of Discrimination
against Women, and key International Labour Organization conventions.
Within a coherent international framework, they need to examine their con-
stitutions to address discriminatory provisions, enhance provisions for gender
equality, review the ways the legal system recognizes customary law, and ensure
that constitutional nondiscrimination provisions are applied in family law and
property rights in marriage. Governments also have to make particular eff ort to
address contradictory and inconsistent provisions in the law.


To strengthen women’s legal and property rights, the following key items
should be addressed:


• Giving women equal say over the administration and transfer of marital
property


• Limiting or removing head-of-household laws that allow husbands to deny
permission to their wives to engage in a trade or profession, or to choose the
marital home


• Removing provisions requiring a husband’s signature to enter into contracts
or open a bank account


• Enabling married women to testify equally in court
• Recognizing women’s rights to marital property upon divorce or in


inheritance
• Applying constitutional provisions of nondiscrimination in areas of


marriage, property, and inheritance
• Building awareness of gender bias, and measures to counteract such bias,


among judges and within the broader legal community


Reforms in the administration of law and in the institutions responsible for
delivering justice can really help improve women’s access to justice and the
capacity of the system to respond to women’s concerns. Measures include facili-
tating physical access to justice, through more, and more appropriately focused,
courts (such as for family matters and small claims); increasing the participa-
tion and representation of women throughout the justice system; and enabling
those administering and dispensing justice at all levels to respond to the diff er-
ent constraints and priorities of men and women. Such action requires political
will and the determination to address the power relations and abusive practices
that can undermine the eff ectiveness of the legal system.




OVERVIEW 21


Expanding Women’s Access to Finance
A repeated fi nding in this book is that the line of business, its size, and its
formality are more important drivers than gender in access to formal fi nance.
Of real concern is the extent to which access to fi nance constrains choice—not
only the choice to become an entrepreneur, but the choice of business line, size,
and formality. With access to collateral, education, and prior work experience
as signifi cant predictors of initial bank loans, women are at a disadvantage.
Th is cycle can then perpetuate itself: if women are less likely to get loans, they
may be more likely to enter less-remunerative lines of business, and so will be
less likely to get credit and less likely to expand their business. In the longer
term, breaking the cycle involves tackling underlying gaps in legal rights and
in access to human capital, but some more-immediate steps can also benefi t
women.


Measures to improve women’s access to fi nance include the following:


• Enriching women’s human capital. Th is underlies the agenda of expanding
women’s access to fi nance.


• Improving property rights for women. Th is will strengthen women’s control
over assets and their capacity to provide collateral for bank loans.


• Building property registries that include movable property. Th is will also
strengthen women’s ability to use movable property as collateral.


• Setting up credit registries that capture women’s credit history and repay-
ment records in microfi nance. Th is will benefi t women disproportionately,
given their greater reliance on microfi nance.


• Directing fi nancing mechanisms to women, including microfi nance and
mobile banking.


Enriching Managerial and Financial Skills
Formal education is important for building women’s human capital, but
other dimensions also matter, especially in building business-specifi c skills
and capacity. Schooling and management training are eff ective in raising
the  productivity of both women’s and men’s enterprises, though the ben-
efi ts of a more entrepreneurial background appear greater for men. Much
work is still needed to expand even rudimentary knowledge of fi nancial
concepts to the wider population, who could benefi t from them in running
businesses.


Key activities to build managerial and fi nancial skills among women include
the following:


• Encouraging opportunities for sharing experiences among businesswomen
• Developing a stronger cadre of female role models in business




22 ENTERPRISING WOMEN


• Strengthening women’s management training and access to consulting
services


• Pairing fi nancial literacy and business skills training with access to fi nance;
tailoring programs to increase women’s participation (for example, choice of
time, location, provision of child care services)


• Promoting mentoring and other networking opportunities to facilitate the
development of business contacts, marketing opportunities, and product
development


Strengthening Women’s Voices in Business Environment Reforms
Measures to strengthen women’s voices in business-climate reform include the
following:


• Animating women business owners and associations to join PPDs
• Encouraging greater participation of women in business associations
• Building the capacity of business associations to provide better services to


members and to contribute more to advocacy for policy reforms
• Carrying out a systematic, gender-informed analysis of business environ-


ment obstacles to highlight issues of concern to businesswomen, and then
integrating this analysis into dialogue and policy making


• Strengthening the presence of women in PPD institutions and structures,
and building the capacity of women to infl uence the agenda of the PPD itself


Areas for Research
Gaps in the data hamper researchers’ ability to undertake gender-disaggregated
analyses. Two gaps are particularly relevant. Th e fi rst relates to the need to
know more about how constraints in the investment climate, particularly in
access to fi nance, shape the entry decision. Data at the individual (as opposed
to household) level on constraints facing those who do not decide to become
entrepreneurs are scarce. One solution would be to add relevant questions to
household surveys.


Th e second relates to transitions between entrepreneurship and wage
employment. Research done on Latin America shows that there can be a fair
amount of mobility between the two, for men and single women. Much less
is known about these transitions in Sub-Saharan Africa. Panel surveys of
individuals and their labor force decisions could signifi cantly contribute to
narrowing this gap.


Notes
1. See ILO 2002 for a broader discussion of defi nitions and data availability on work in


the informal sector.




OVERVIEW 23


2. The companion volume is Empowering Women: Legal Rights and Economic
Opportunities in Africa (Hallward-Driemeier and Hasan 2012). Th e database, cited
in the overview below and throughout the volume, is M. Hallward-Driemeier,
T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


3. Some of these decisions may not actually represent true “choices”; where wage
employment is scarce, entrepreneurship may be the only realistic option.


References
Arbache, J. S., A. Kolev, and E. Filipiak, eds. 2010. Gender Disparities in Africa’s Labor


Market. Washington, DC: World Bank.
Aterido, R., T. Beck, and L. Iacovone. Forthcoming. “Gender and Finance in Sub-Saharan


Africa: Are Women Disadvantaged?” World Development.
Aterido, R., and M. Hallward-Driemeier. 2011. “Whose Business Is It Anyway?” Small


Business Economics 37 (4): 443–64.
Ayyagari, M., T. Beck, and A. Demirgüç-Kunt. 2007. “Small and Medium Enterprises


across the Globe.” Small Business Economics 29: 415–34.
Bardasi, E., M. Blackden, and J. C. Guzman. 2007. “Gender, Entrepreneur-


ship, and Competitiveness.” In Africa Competitiveness Report 2007, edited by
World Economic Forum, African Development Bank, and World Bank, 69–86.
Washington,  DC:  World Economic Forum, African Development Bank, and
World Bank.


Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. W. Gunning, A. Oduro,
R. Oostendorp, C. Patillo, M. Söderbom, F. Teal, and A. Zeufack. 2003. “Credit
Constraints in Manufacturing Enterprises in Africa.” Journal of African Economies
12 (1): 104–25.


Bigsten, A., and M. Gebreeyesus. 2007. “Th e Small, the Young, and the Productive:
Determinants of Manufacturing Firm Growth in Ethiopia.” Economic Development
and Cultural Change 55 (4): 813–40.


Bigsten, A., and M. Söderbom. 2006. “What Have We Learned from a Decade of
Manufacturing Enterprise Surveys in Africa?” World Bank Research Observer 21 (2):
241–65.


Blau, D. 1985. “Self-Employment and Self-Selection in Developing Country Labor
Markets.” Southern Economic Journal 52 (2): 351–63.


Bloom, N., and J. Van Reenen. 2007. “Measuring and Explaining Management
Practices Across Firms and Countries.” Quarterly Journal of Economics 122 (4):
1351–408.


. 2010. “Why Do Management Practices Diff er across Firms and Countries?”
Journal of Economic Perspectives 24 (1): 203–24.


Bruhn, M., D. Karlan, and A. Schoar. 2010. “What Capital Is Missing in Developing
Countries?” American Economic Review 100 (2): 629–33.


Bruhn, M., and B. Zia. 2011. “Stimulating Managerial Capital in Emerging Markets: Th e
Impact of Business and Financial Literacy for Young Entrepreneurs.” Working Paper,
World Bank, Washington, DC.




24 ENTERPRISING WOMEN


de Mel, S., D. McKenzie, and C. Woodruff . 2009. “Are Women More Credit Constrained?
Experimental Evidence on Gender and Microenterprise Returns.” American Economic
Journal: Applied Economics 1 (3): 1–32.


Djankov, S., Y. Qian, G. Roland, and E. Zhuravskaya. 2007. “What Makes a Successful
Entrepreneur? Evidence from Brazil.” Working Paper 104, Center for Economic and
Financial Research, Moscow.


Fafchamps, M. 2000. “Ethnicity and Credit in African Manufacturing.” Journal of
Development Economics 61(1): 205–35.


Fafchamps, M., M. Söderbom, and N. Benhassine. 2009. “Wage Gaps and Job Sorting in
African Manufacturing.” Journal of African Economies 18 (5): 824–68.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among
New  Entrepreneurs.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and O. Gajigo. 2011. “Strengthening Economic Rights and
Women’s Occupational Choice: Th e Impact of Reforming Ethiopia’s Family Law.”
Paper presented at Centre for the Study of African Economics annual conference,
St. Catherine’s College, Oxford, March 20–22.


Hallward-Driemeier, M., and T. Hasan. 2012. Empowering Women: Legal Rights and
Economic Opportunities in Africa. Washington, DC: World Bank and Agence Française
de Développement.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Herzberg, B., and A. Wright. 2006. Th e PPD Handbook: A Toolkit for Business Environment
Reformers. Washington, DC: World Bank.


ILO (International Labour Organization). 2002. “Women and Men in the Informal
Economy: A Statistical Picture.” Gender and Employment Sector, ILO, Geneva.


Klapper, L., and S. Parker. 2010. “Gender and the Business Environment for New Firm
Creation.” World Bank Research Observer 26 (2): 237–57.


Kolev, A., and N. Sirven. 2010. “Gender Disparities in Africa’s Labor Markets:
A  Cross-Country Comparison Using Standardized Survey Data.” In Gender Dispari-
ties in Africa’s Labor Market, edited by J. S. Arbache, A. Kolev, and E. Filipiak, 23–54.
Washington, DC: World Bank.


Liedholm, C., and D. Mead. 1999. Small Enterprises and Economic Development:
Th e Dynamics of Micro and Small Enterprises. London: Routledge.


Mansuri, G., and X. Giné. 2011. “Money or Ideas? A Field Experiment on Constraints to
Entrepreneurship in Rural Pakistan.” Working paper, World Bank, Washington, DC.


McPherson, M. A. 1996. “Growth of Micro and Small Enterprises in Southern Africa.”
Journal of Development Economics 48 (March): 235–77.


Mead, D. C., and C. Liedholm. 1998. “Th e Dynamics of Micro and Small Enterprises in
Developing Countries.” World Development 26 (1): 61–74.


Minniti, Maria. 2009. “Gender Issues in Entrepreneurship.” Foundations and Trends in
Enterpreneurship 5 (7–8): 497–621.


Parker, S. C. 2004. Th e Economics of Self-Employment and Entrepreneurship. Cambridge:
Cambridge University Press.




OVERVIEW 25


Parker, S. C., and M. van Praag. 2006. “Schooling, Capital Constraints, and Entrepreneurial
Performance.” Journal of Business and Economic Statistics 24 (4): 416–31.


Simavi, S., C. Manuel, and M. Blackden. 2010. Gender Dimensions of Investment Climate
Reform: A Guide for Policy Makers and Practitioners. Washington, DC: World Bank.


Sinha, A., and R. Kanbur. 2012. “Informality: Concepts, Facts, and Models.” Journal of
Applied Economic Research 6 (2): 91–102.


Sleuwaegen, L., and M. Goedhuys. 2002. “Growth of Firms in Developing Countries,
Evidence from Côte d’Ivoire.” Journal of Development Economics 68 (June): 117–35.


Söderbom, M. 2012. “Firm Size and Structural Change: A Case Study of Ethiopia.” Jour-
nal of African Economies 21: 126–51.


Tamanaha, B., C. Sage, and M. Woolcock, eds. 2012. Legal Pluralism and Development:
Scholars and Practitioners in Dialogue. New York: Cambridge University Press.


Tybout, J. R. 2000. “Manufacturing Firms in Developing Countries: How Well Do Th ey
Do, and Why?” Journal of Economic Literature 28 (March): 11–44.


Van Biesebroeck, J. 2005. “Firm Size Matters: Growth and Productivity Growth in
African Manufacturing.” Economic Development and Cultural Change 53 (3): 545–83.


Van der Sluis, J., M. van Praag, and W. Vijverberg. 2008 “Education and Entrepreneur-
ship Selection and Performance: A Review of the Literature.” Journal of Economic
Surveys 22 (5): 795–841.


World Bank. 2004. World Development Report 2005: A Better Investment Climate for
Everyone. New York: Oxford University Press.


. 2011. World Development Report 2012: Gender Equality and Development.
New York: Oxford University Press.


. 2012. World Development Report 2013: Jobs. New York: Oxford University Press.






Part I


Where Women and
Men Work
We start with the facts—laying out the patterns of where women and
men work. Th e fi rst chapters put entrepreneurship in the context of
other employment categories across regions. Th ey also examine the
gender patterns across types of enterprises, showing the extent to
which each gender operates in larger fi rms, the formal sector, and
higher-value-added activities. Women are disproportionately active
in the informal sector, smaller fi rms, and traditional sectors. But
there is signifi cant variation in these patterns across countries and
across groups of women within a country. Th ese gender patterns,
and their variation, need to be explained, with an eye to enabling
more women to shift into higher-value-added activities.






29


Chapter 1


Self-Employed, Employers,
and Wage Earners in the
Formal and Informal Sectors


Development is about realizing potential. Yet too oft en, obstacles or a lack of
access to key resources makes realizing potential impossible. Th e problem is
compounded when some groups face greater systemic hurdles than others. Th e
group of interest in this book is women, but there are others as well.1


Not all women are disadvantaged. It is precisely by seeing how and where
women succeed and by looking at variations in gender gaps that we can
identify the conditions and policy levers to expand women’s opportunities
more broadly.


Women’s economic empowerment is a central development goal. Women
have been working to expand their ability to earn and control assets, individu-
ally and collectively, for a very long time. Th ese eff orts gained a boost from
the international community in recent years. Women’s empowerment is rec-
ognized as the third Millennium Development Goal; in 2012, the World Bank
dedicated its annual fl agship, the World Development Report, to gender equality
and development (World Bank 2011);2 and the Nobel Prize for Peace was
awarded to three pioneering women (two from Liberia) working for peace in
their countries’ fi ghts for democracy and for greater opportunities for women.


Th is book focuses attention on Sub-Saharan Africa, and specifi cally on entre-
preneurship in the nonagricultural sector. Th e issue of gender disparities in
economic opportunities in the region has been studied in terms of gaps in wage
income and in job sorting in wage work (Arbache, Kolev, and Filipiak 2010;
Fafchamps, Söderbom, and Benhassine 2009; Kolev and Sirven 2010). Other
cross-country work has looked at entrepreneurship in Sub-Saharan Africa, but
rarely with much attention paid to gender (Bigsten and Söderbom 2006; Nichter
and Goldmark 2009; Tybout 2000; World Bank 2004). But entrepreneurship
is where women in Sub-Saharan Africa are most active outside of agriculture.
So it is critical to look at entrepreneurship to understand the extent of gender




30 ENTERPRISING WOMEN


disparities in economic opportunities, determine the underlying reasons for
these gender patterns, and develop an agenda to enable more women to realize
their full potential (see box 1.1).


Gender Patterns in Entrepreneurship: Laying Out the Facts


To expand women’s economic opportunities in Sub-Saharan Africa, we have to
know where women are currently economically active. Th is chapter describes
how many women work (box 1.2) in the region and where, comparing the
patterns with men. It also compares Sub-Saharan Africa with other regions. Two
broad sets of patterns are examined. Th e fi rst concerns employment categories:
in the labor market, unemployed, wage earner, self-employed, or employer.
Th e focus of this book, nonagricultural entrepreneurship (self-employed plus
employer), is oft en discussed relative to wage employment. Th e second set of
patterns, discussed in chapter 2, concerns the types of enterprises run by entre-
preneurs such as their formality, size, and industry. Mapping the gender gaps in


BOX 1 . 1


Expanding Opportunities
Strengthening women’s economic opportunities has both an inherent value—all
people should have the same chance to reap the rewards of their efforts and invest-
ments and be able to pursue income-generating opportunities—and an instrumental
value. Realizing the potential of all people contributes to higher standards of living and
productivity, and to a vibrant society.


This book is about entrepreneurs, the self-employed as well as employers. Expanding
their opportunities could mean improving the returns in their current business and
helping them move into higher-return businesses, but might also mean moving out
of entrepreneurship into other types of employment, namely wage employment.
Transitions into and out of entrepreneurship are beyond the scope of this book, but the
book does compare patterns of entrepreneurship with those of wage earners to show
the likely trade-offs and ability to move from one to the other.


Some entrepreneurs seek to work independently, see opportunities in new ways
of doing business, and want to be their own boss. Indeed, such entrepreneurs are an
important source of innovation and productivity growth—and a source of employment
for others. Providing an enabling environment for these entrepreneurs is indeed part
of the agenda. However, for those who are entrepreneurs out of necessity rather than
choice, the need to succeed is also great. Addressing their constraints and expanding
their access to higher-return activities will also impact poverty reduction and job
creation.




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 31


participation rates helps identify the constraints that women face and the scope
for expanding their opportunities.


Th e data show, overwhelmingly, that women in Sub-Saharan Africa are active
in the labor force, and that their participation rates are higher than in any other
region. And most women working outside of agriculture are entrepreneurs.


Is this good news? Does it signal that the private sector is dynamic or that
few alternative opportunities are available? It is critical to look within entrepre-
neurial activities to answer these questions.3


Several gender-disaggregated patterns hold across almost all the region’s
countries: women are far more likely to be self-employed than to be either
employers or wage earners (and less likely than men to be employers or wage
earners). Among entrepreneurs, the share of employers remains fairly constant
across countries, as does the share of women among employers. Across the
Sub-Saharan African region, fully half of those who are self-employed are
women, yet only a quarter of employers are women. Of entrepreneurs, women
are more likely to be running small informal fi rms in lower-value-added
activities.


BOX 1 .2


Types of “Work”
The International Labour Organization has developed standardized defi nitions of six
categories to capture people’s employment status. The fi rst distinction is whether or not
someone is “in the labor force,” referring to all those who are engaged in economic
activities. Among those participating in the labor force, there are fi ve key categories:
the self-employed, employers, wage earners, unpaid workers, and the unemployed.
“Entrepreneurs” are the self-employed and the employers.


We follow this classifi cation, with one exception. We make a distinction between
agricultural and nonagricultural employment activities, focusing on the latter. Thus we
make no distinctions between those in the agriculture sector (combining those who are
wage earners, unpaid workers, self-employed, and employers). The categories used in
this book are shown in fi gure B1.2.1.


Working-age population
Not in


labor force
Employed Agriculture
Nonagricultural labor force Self-employed Employers Wage workers Unpaid workers Unemployed


Nonagricultural labor force


Labor force


Entrepreneurs


Figure B1.2.1 Typology of Employment Status Categories




32 ENTERPRISING WOMEN


Th ese patterns strongly suggest that strengthening women’s economic
opportunities is not about expanding entrepreneurship. Instead it is about tack-
ling constraints on women’s abilities and incentives to expand their businesses
and move into higher-value-added activities—in short, the agenda is about
shift ing the composition of entrepreneurial activities.


A variety of country studies fi nds similar patterns of women’s relative
concentration in smaller fi rms, in the informal sector, and in traditional
activities (for example, Bigsten and others 2003; ILO 2002; Mammen and
Paxon 2000; McPherson 1996; Mead 1991, 1994; Mead and Liedholm 1998;
Parker 2004; Sinha and Kanbur 2012). Th is fi nding is important because, if one
is to be self-employed or an employer, further characteristics of the enterprise
are correlated with opportunity. Larger enterprises, formal enterprises, and
higher-value-added industries tend to be more productive—including in devel-
oping countries and in Sub-Saharan Africa (Bigsten and Söderbom 2006; Tybout
2000; World Bank 2004, 2012). Th us it is important to look at gender gaps across
these three dimensions—size, formality, and industry—and to examine why
these gender- diff erentiated patterns of entrepreneurial activity exist. At the same
time, diff erent ways of defi ning and measuring women’s ownership of enterprises
aff ect the results and have diff erent policy implications.


A central challenge in examining entrepreneurship is that entrepreneurs
compose a wide spectrum of individuals in their abilities, motivations, and
outside options, and that entrepreneurs are engaged in a large gamut of types
of enterprises.


Some women are entrepreneurs by choice, pursuing an opportunity with
a goal of expanding their business. Others are entrepreneurs by default
or necessity. Faced with the need for income and the inability to fi nd wage
employment, they run their own business as an option of last resort. Th ey
may not have any particular aptitude in running a business or any motivation
beyond meeting subsistence needs. Th e data do not make it easy, however, to
distinguish “opportunity” from “necessity” entrepreneurs.4


To set the stage for understanding the key stylized facts about the
opportunities being pursued, this chapter presents labor force participation
rates by region, including agriculture, and then looks at the prevalence of
the self-employed, employers, and wage earners in nonagricultural activities.
Both the self-employed and employers can include necessity and opportunity
entrepreneurs—and can represent successful and unsuccessful enterprises.
But employers are more likely to be opportunity entrepreneurs and possess a
demonstrated ability to expand a business; the self-employed are more likely to
have a larger share of necessity entrepreneurs, particularly in countries at lower
levels of development.


Within these two groups, further characteristics of the enterprise are
correlated with opportunity. Larger enterprises, formal enterprises, and




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 33


higher-value-added sectors tend to be more productive. Th e next chapter
focuses on gender gaps by type of enterprise along three dimensions: size,
formality, and industry.


Th is mapping exercise then sets up the rest of the book, which examines
what factors, at the country or individual level, can help explain these gender-
diff erentiated patterns of entrepreneurship.


Th e early chapters draw primarily on enterprise and household surveys
to provide a map of women’s and men’s involvement as self-employed
entrepreneurs, as employers, or as wage earners (box 1.3 and appendix A). Later
chapters use this information to examine the factors associated with the gender
patterns of entrepreneurship discussed here. One aim is to illuminate the policy
levers that could shift these patterns of what women entrepreneurs do, so as to
expand economic opportunities for women.


BOX 1 .3


Primary Sources of Data Used in This Book
Four types of surveys of enterprises are included in this work. All were administered
by the World Bank, with respondents sampled on the basis of the population of
enterprises.


Enterprise Surveys.a The Enterprise Surveys cover stratifi ed random samples of
registered fi rms in key industrial centers in a country. They also cover both manufac-
turing and services, including information on the owner of the enterprise, enterprise
performance measures, and measures of constraints facing the enterprise. There are
Enterprise Survey data for 37 countries in Sub-Saharan Africa.


Enterprise Surveys—microenterprises. Very similar to the previous instrument,
they cover 25 countries in Sub-Saharan Africa. The sampling differs in that it targets
microfi rms that are generally not registered; 98 percent of the fi rms sampled have fi ve
employees or fewer. In the analysis, the data are labeled “informal.”


Enterprise Surveys—gender module. The gender module was one of two new
surveys carried out for this study. For fi ve countries that had completed an Enterprise
Survey (Ghana, Mali, Mozambique, Senegal, and Zambia), we fi elded an additional
module to capture more information on the background of the entrepreneur, the moti-
vation for starting a business, the means of starting or acquiring a business, and indica-
tors of management techniques. The module also refi ned measures for the gender of
both the principal owner and the person running the business, with this measure (but
not the whole module) available for a sixth country, South Africa.


Surveys of new entrepreneurs. The second new survey carried out for this study was
administered to new entrepreneurs in four countries (Côte d’Ivoire, Kenya, Nigeria, and
Senegal). The survey covered fi rms in the formal and informal sectors (distinguished by


—Continued




34 ENTERPRISING WOMEN


Gender Differences in Labor Force Participation
by Region


Th is section looks at household data to examine gender-disaggregated rates of
entrepreneurship and to explore how entrepreneurship fi ts into the broader
patterns of labor force participation. It begins by examining how Sub-Saharan
Africa compares with other regions, and then examines how patterns vary by
income.


Labor force participation is subdivided into fi ve employment categories, with
a sixth variable refl ecting nonparticipation in the labor force. All the data look
at individuals of working age, 16–60 years old, and give, for women and men,
the average share of the population in each geographic region that is in each of
the major employment categories (fi gure 1.1).5 Employers are clearly a small
share of the overall population for both women and men. Self-employment
represents a larger share.


whether the enterprise is registered, not the extent of its compliance with tax laws or
other regulations). It collected detailed background information on the entrepreneur,
as well as the motivation for starting a business, the means of starting or acquiring a
business, and the indicators of management techniques used. It also included some
additional measures on the constraints of setting up a business.


The book also draws on two sets of surveys that sampled households and that were
administered by national statistical offi ces.


Household surveys and labor force surveys. These have been compiled for
39  countries in Sub-Saharan Africa and 101 globally, drawing from each country’s own
national survey. They are not strictly comparable, because countries use different ques-
tionnaires (though most adhere to the International Labour Organization defi nitions of
labor) and somewhat different sampling strategies. But they have been standardized for
a core set of questions to allow cross-country patterns to be examined. These data pro-
vide the information of individuals’ participation in the different employment categories.


Household surveys—enterprise modules. Those in the household who say they have
an enterprise were asked additional questions in 20 Sub-Saharan African countries.
These data can be used to examine fi rm performance (particularly for more informal busi-
nesses, such as those operating out of the house and those with household members
working in them). The name does not mean that all the enterprises are run out of the
home; indeed, many are not. It means that the basis for the sampling is the household.


Appendix A provides more details, including country coverage, and outlines the
strengths and limitations of the different data sets.


a. “Enterprise Surveys” refers to the specifi c set of enterprise surveys run by the World Bank
(see http://www.enterprisesurveys.org), and the term is therefore capitalized throughout.


BOX 1 .3 con t i nued




35


Figure 1.1 Women’s Participation Rates Are Highest in Sub-Saharan Africa


0


10


20


30


40


50


60


70


80
Pe


rc
en


ta
ge


o
f f


em
al


e
po


pu
la


ti
on


a. Where women work


Su
b-S


ah
ara


n


Af
ric


a


Ea
st


As
ia


an
d


Pa
cifi


c


Mi
dd


le
Ea


st


an
d N


ort
h A


fric
a


So
uth


As
ia


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d


the
Ca


rib
be


an


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).


0


10


20


30


40


50


60


Pe
rc


en
ta


ge
o


f
m


al
e


po
pu


la
ti


on


b. Where men work


Su
b-S


ah
ara


n


Af
ric


a


Ea
st


As
ia


an
d


Pa
cifi


c


Mi
dd


le
Ea


st


an
d N


ort
h A


fric
a


So
uth


As
ia


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d


the
Ca


rib
be


an


Employer Self-employed Wage worker


Agricultural worker Labor force nonparticipantUnpaid worker




36 ENTERPRISING WOMEN


Entrepreneurship rates are aff ected by the overall shares of the population in
agriculture or not participating in the labor force. Women are less likely than
men to be in the labor force in every region. Men’s labor force participation
both is higher than women’s and exhibits less variation across regions. Women’s
participation is highest in Sub-Saharan Africa (equivalently, nonparticipation is
lowest there), and the gender gap in participation is lowest.


Agriculture is the most common labor activity in Sub-Saharan Africa, with
little diff erence by gender. Excluding agricultural activities sees labor force
participation fall the most there, to 25  percent for women (fi gure  1.2). In
nonagricultural labor, only South Asia and the Middle East and North Africa
have lower rates of female participation, and Sub-Saharan Africa no longer has
the smallest gender gap in participation.


Entrepreneurship: Sub-Saharan Africa in a Global Context


Within nonagricultural employment, in the categories of self-employment,
being an employer, or wage employment, Sub-Saharan Africa shows the highest


0


10


20


30


40


50


60


70


80


Pe
rc


en
ta


ge
o


f f
em


al
e


(m
al


e)
p


op
ul


at
io


n
(a


ve
ra


ge
o


f c
ou


nt
ri


es
in


t
he


r
eg


io
n)


a. Labor force participation (population)


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Figure 1.2 Sub-Saharan Africa Has the Biggest Difference between Women’s Overall Labor
Force Participation and Women’s Nonagricultural Labor Force Participation




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 37


self-employment rate and the lowest wage employment rate of all regions.6
Th ree patterns of gender diff erences emerge:
• Sub-Saharan Africa is the only region where women’s self-employment is


more common than wage employment.
• The gender gap in the share in wage employment is the highest in


Sub- Saharan Africa.
• Rates of being an employer are low across all regions, with variations greater


for men than women. Among employers, the female share is generally
25–30 percent.


Self-Employment
Within nonagricultural employment, women’s participation in self-employment
is by far the highest in Sub-Saharan Africa (fi gure 1.3). Just more than half of all
women are self-employed there.


Women represent half of those among the nonagricultural self-employed in
Sub-Saharan Africa and the East Asia and Pacifi c region, but only 20 percent
in the Middle East and North Africa (fi gure 1.4).7


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).


Figure 1.2 (continued)


0


10


20


30


40


50


60


70


80
b. Labor force participation in nonagricultural activities


Female Male


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Pe
rc


en
ta


ge
o


f f
em


al
e


(m
al


e)
p


op
ul


at
io


n
(a


ve
ra


ge
o


f c
ou


nt
ri


es
in


t
he


r
eg


io
n)




38


0


10


20


30


40


50


70


80


90


60


Pe
rc


en
ta


ge
o


f f
em


al
e


(m
al


e)


no
na


gr
ic


ul
tu


ra
l l


ab
or


fo
rc


e


Female self-employed
Male self-employed


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Figure 1.3 Women’s Nonagricultural Self-Employment Rate Is Highest in Sub-Saharan Africa


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: The figure shows the share within the nonagricultural labor force that is self-employed.


0


10


20


30


40


50


60


Pe
rc


en
ta


ge
o


f s
el


f-
em


pl
oy


ed


w
ho


a
re


fe
m


al
e


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


La
tin


Am
eri


ca
an


d t
he


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: Analysis excludes agriculture.


Figure 1.4 The Sub-Saharan Africa Region Leads in the Share of Nonagricultural Self-
Employed Who Are Women




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 39


Employers
Th e rates of being an employer are far smaller than those of self-employment
(fi gure 1.5, which is not to scale with the previous charts). Th ey vary consider-
ably for men across regions (the rates in Latin America and the Caribbean and
in the Middle East and North Africa are around twice those in Sub-Saharan
Africa and East Asia and Pacifi c). For women the share is oft en half that of men,
with less variation across regions.


A smaller share of employers is made up of women (25–30 percent); there
is relatively little variation in this pattern except for in the Middle East and
North Africa, where the share is 9 percent (fi gure 1.6).


Wage Employment
Th e share of wage employment, particularly for women, is lower in Sub-Saharan
Africa than in any other region (fi gure 1.7). Th e share for women is more than
twice as high in Europe and Central Asia as in Sub-Saharan Africa. Th e gender


Figure 1.5 Globally, Far Fewer Entrepreneurs Are Employers Than Are Self-Employed


0


10


20


30


40


50


60


70


80


90


Pe
rc


en
ta


ge
o


f f
em


al
e


(m
al


e)
n


on
ag


ri
cu


lt
ur


al


la
bo


r
fo


rc
e


Female employer Male employer


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: Analysis excludes agriculture.




40 ENTERPRISING WOMEN


Figure 1.6 The Share of Female Employers Is Lower Than for Self-Employment, but with Very
Similar Rates for Five of the Six Regions


0


5


10


15


20


25


30


35


40


45


50


55


60
Pe


rc
en


ta
ge


o
f e


m
pl


oy
er


s
w


ho
a


re
fe


m
al


e


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: Analysis excludes agriculture. See figure 1.4 for the comparison with the self-employed.


gap is also widest in Sub-Saharan Africa. (Capturing gender gaps is discussed
in box 1.4.)


Women are also a smaller share of wage earners than men, although wide
variation exists across regions (fi gure 1.8).


Th e data show that the need to expand opportunities for entrepreneurs is
particularly pressing in Sub-Saharan Africa. Entrepreneurship plays a bigger
role in Sub-Saharan Africa than in any other region. Th us improving oppor-
tunities for entrepreneurs would aff ect a large portion of the population—
many of whom do not have alternative forms of employment available. It is the
region where the smallest share of the labor force is in nonagricultural wage
employment. Th e gender dimension is also particularly striking, with gender
gaps in wage employment the highest in Sub-Saharan Africa. If wage employ-
ment is scarce, running a business is the primary way of earning income.


“Running a business” encompasses a large range of activities, some of which
are more likely to be successful and to earn higher returns than others. Th us it
is important to look at the microdata on the types of enterprises women and
men run. Th ese data are discussed in the next chapter.




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 41


Figure 1.7 Of All Regions, Sub-Saharan Africa Has the Lowest Rate and Widest Gender Gap
for Wage Employment


0


10


20


30


40


50


60


70


80


90
Pe


rc
en


ta
ge


o
f f


em
al


e
(m


al
e)


w
ag


e
ea


rn
er


s
in


n
on


ag
ri


cu
lt


ur
al


la
bo


r
fo


rc
e


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


Female wage earner Male wage earner


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: Analysis excludes agriculture.


Figure 1.8 The Regions Show a Wide Variation in the Share of Female Wage Earners


0
5


10
15
20
25
30
35
40
45
50
55
60


Pe
rc


en
ta


ge
o


f w
ag


e
ea


rn
er


s
w


ho
a


re
fe


m
al


e


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al


As
ia


La
tin


Am
eri


ca
an


d t
he


Mi
dd


le
Ea


st
an


d


No
rth


Af
ric


a


So
uth


As
ia


Ca
rib


be
an


Source: National household and labor force surveys for 101 low- and middle-income economies, most recent
years (2000–10).
Note: Analysis excludes agriculture.




42 ENTERPRISING WOMEN


Figure B1.4.1 Gender Gap in Self-Employment


MUS
NAM


GAB


SWZ
MDG


BDI
CPV


ETH NER
LBR


CIV


SEN


CMR
SLE


ZAR


NGA


TCD
COO


GHA
IOO


CIN
GZA


GMB


ZMBKEN
ODM


100


80


60


40


20


0


Pe
rc


en
ta


ge
o


f m
en


in
s


el
f-


em
pl


oy
m


en
t


Percentage of women in self-employment


20 40 60 80 100


Source: National household and labor force surveys for 34 countries in Sub-Saharan Africa, most recent years
(2000–10).
Note: Analysis excludes agriculture.


BOX 1 .4


How to Capture Gender Gaps
The gap of gender concentration within employment categories looks at the share of
women compared with the share of men in that employment category.


For example, the gap of gender concentration within self-employment equals



Self employed women


All women in nolabor force
Self employed men


All men in nolabor force
--


,−

⎝⎜



⎠⎟


where nolabor stands for nonagricultural labor.
Figure B1.4.1 graphs the share of men against the share of women in self-employment.


If women and men sorted in the same proportions into the employment categories, the
countries would line up along the 45 degree line. To the extent countries are below the
line, women sort disproportionately into that employment category (and above the line,
men). Figures B1.4.2 and B1.4.3 show the differences in the shares of women and shares
of men as employers and as wage earners—or the vertical distance from the 45 degree line
(those above the line are “negative” gaps, that is, women’s shares are lower than men’s).


In all three categories almost all countries are skewed the same way: there is a
higher share of women among the self-employed, and higher shares of men among
employers and wage earners.




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 43


Figure B1.4.2 Gender Gap in Being an Employer


8


6


4


2


0


Pe
rc


en
ta


ge
o


f m
en


a
s


em
pl


oy
er


s


Percentage of women as employers


SLE
TCD


TZA
GHA COI


KENMUS CMR
NERAGO


COG
GMB


GIN


ZMB
SWZ
NGA


BDI
ETH MWI


SENGAB
NAM


CPV


ZARMDG LBR


20 40 60 80


Source: National household and labor force surveys for 34 countries in Sub-Saharan Africa, most recent years
(2000–10).
Note: Analysis excludes agriculture.


Figure B1.4.3 Gender Gap in Wage Workers


MUS
NAM


GAB


SWZ


MDG


BDI
CPV


ETHNER
NGA


MWI


LBR
AGO


CIV
SEN


CMR
SLE


ZAR
NGA


TCD
COG


GHA


TZA
GMB


ZMB
KENCOM


100


80


60


40


20


0


Pe
rc


en
ta


ge
o


f m
en


a
s


w
ag


e
w


or
ke


rs


Percentage of women as wage workers
20 40 60 80 100


Source: National household and labor force surveys for 34 countries in Sub-Saharan Africa, most recent years
(2000–10).
Note: Analysis excludes agriculture.


—Continued




44 ENTERPRISING WOMEN


BOX 1 .4 con t i nued


But if one compares the fi rst two categories—that is, the gap in gender shares
in self-employment versus the gender gap in being an employer—there does not
appear to be a striking pattern (fi gure B1.4.4). It is not the case that, where there is a
larger gender gap in self-employment, there is a larger—or smaller—gap in being an
employer. This fi nding is important to the discussion in chapter 3, because it indicates
that the two types of entrepreneurship are being driven by different sets of factors.


Figure B1.4.4 Degree of Correlation in Self-Employed and Employers


Source: National household and labor force surveys for 34 countries in Sub-Saharan Africa, most recent years
(2000–10).
Note: Analysis excludes agriculture.


–5


–4 SLE
TZA


GMB


ZAR


TCD
GIN


AGO
GHA


COGCMR
BFA


MDG


NERMWI
CPV


LBR


BDI


NAM ETH


GAB


MLI
NGA
UGA


KEN


MOZ


CIV SEN
ZMB


SWZCOM


MUS


–3


–2


–1


0


1


–20 –10 10 20 30 40 50


G
en


de
r


ga
p


fo
r


em
pl


oy
er


s


Gender gap for self-employed


Notes
1. Other groups can be disadvantaged because of race, ethnicity, religious affi liation,


disability, language, geographic location, sexual orientation, and so forth. Studies
oft en fi nd that women within these groups face particularly diffi cult challenges.


2. Th at work builds on a World Bank (2002) report, which provides a detailed review
of the literature on gender equality and development, focusing on women’s rights,
access to resources, and voice.


3. Th ere is a further debate as to the broader prospects for Africa’s growth. Th e literature
from the 1980s and 1990s was largely pessimistic. Higher growth rates in recent
years have served to raise expectations, although growth rates vary across the region




SELF-EMPLOYED, EMPLOYERS, AND WAGE EARNERS 45


and diversifi cation remains a major challenge in most countries ( Chuhan-Pole and
Angwafo 2011; Collier and Gunning 1999; Tybout 2000; World Economic Forum,
African Development Bank, and World Bank 2011).


4. More-recent survey data on backgrounds and motivations of entrepreneurs provide
some insights, however (see chapter 3).


5. “Unemployed” is the omitted category. It is negligible in Sub-Saharan Africa.
6. We look at paid employment rather than labor force participation, as we cannot


determine what sector the unemployed may be seeking work in. Unpaid workers
are also not included.


7. Th e diff erence between fi gures 1.3 and 1.4 shows the stark eff ect of relative gender
diff erences in nonagricultural labor force participation rates. For the Middle East and
North Africa, for example, almost equal shares of men and women are self-employed
(fi gure 1.3), but this translates into women being only a fi ft h of all the self-employed
in the region (fi gure 1.4), given the region’s wide gender gap in participation.


References
Arbache, J. S., A. Kolev, and E. Filipiak, eds. 2010. Gender Disparities in Africa’s Labor


Market. Washington, DC: World Bank.
Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. W. Gunning, A. Oduro,


R. Oostendorp, C. Patillo, M. Söderbom, F. Teal, and A. Zeufack. 2003. “Credit
Constraints in Manufacturing Enterprises in Africa.” Journal of African Economies
12 (1): 104–25.


Bigsten, A., and M. Söderbom. 2006. “What Have We Learned from a Decade of
Manufacturing Enterprise Surveys in Africa?” World Bank Research Observer 21 (2):
241–65.


Chuhan-Pole, P., and M. Angwafo, eds. 2011. Yes Africa Can: Success Stories from a
Dynamic Continent. Washington, DC: World Bank.


Collier, P., and J. W. Gunning. 1999. “Explaining African Economic Performance.”
Journal of Economic Literature 37 (1): 64–111.


Fafchamps, M., M. Söderbom, and N. Benhassine. 2009. “Wage Gaps and Job Sorting in
African Manufacturing.” Journal of African Economies 18 (5): 824–68.


ILO (International Labour Organization). 2002. “Women and Men in the Informal
Economy: A Statistical Picture.” Gender and Employment Sector, ILO, Geneva.


Kolev, A., and N. Sirven. 2010. “Gender Disparities in Africa’s Labor Markets: A Cross-
Country Comparison Using Standardized Survey Data.” In Gender Disparities in
Africa’s Labor Market, ed. J. S. Arbache, A. Kolev, and E. Filipiak, 23–45. Washington,
DC: World Bank.


Liedholm, C., and D. Mead. 1999. Small Enterprises and Economic Development:
Th e Dynamics of Micro and Small Enterprises. London: Routledge.


Mammen, K., and C. Paxon. 2000. “Women’s Work and Economic Development.”
Journal of Economic Perspectives 14: 141–64.


McPherson, M. A. 1996. “Growth of Micro and Small Enterprises in Southern Africa.”
Journal of Development Economics 48 (March): 235–77.




46 ENTERPRISING WOMEN


Mead, D. C. 1991. “Review Article: Small Enterprises and Development.” Economic
Development and Cultural Change 39 (January): 409–20.


. 1994. “Th e Contribution of Small Enterprises to Employment Growth in
Southern and Eastern Africa.” World Development 22 (December): 1881–94.


Mead, D. C., and C. Liedholm. 1998. “Th e Dynamics of Micro and Small Enterprises in
Developing Countries.” World Development 26 (1): 61–74.


Nichter, S., and L. Goldmark. 2009. “Small Firm Growth in Developing Countries.”
World Development 37 (9): 1453–64.


Parker, S. C. 2004. Th e Economics of Self-Employment and Entrepreneurship. Cambridge:
Cambridge University Press.


Sinha, A., and R. Kanbur. 2012. “Informality: Concepts, Facts and Models.” Journal of
Applied Economic Research 6 (2): 91–102.


Tybout, J. R. 2000. “Manufacturing Firms in Developing Countries: How Well Do Th ey
Do, and Why?” Journal of Economic Literature 28 (March): 11–44.


World Bank. 2002. Engendering Development: Th rough Gender Equality in Rights,
Resources and Voice. Policy Research Report. Washington, DC: World Bank.


. 2004. World Development Report 2005: A Better Investment Climate for Everyone.
New York: Oxford University Press.


. 2011. World Development Report 2012: Gender Equality and Development.
Washington, DC: World Bank.


. 2012. World Development Report 2013: Jobs. Washington, DC: World Bank.
World Economic Forum, African Development Bank, and World Bank. 2011. African


Competitiveness Report. Geneva: World Economic Forum, African Development
Bank, and World Bank.




47


Chapter 2


The Size, Formality, and
Industry of Enterprises


Beyond knowing the rates of entrepreneurship and the breakdown of the
self-employed and employers, it is important to understand the characteristics
of enterprises run by women and by men. Clearly the eff orts of the individual
entrepreneurs aff ect the success of a business, but there are nonetheless very
strong patterns of average returns and growth by types of enterprises. In this
chapter we look at three dimensions: the size (number of employees) of the
enterprise, the share of enterprises that are in the formal or informal sector, and
the industry in which the enterprise operates.


For information on these dimensions we turn to microdata and the rich-
ness of the complementary enterprise and household surveys available. Th e
analysis of these data sets corroborates the literature’s fi ndings:1 women are
more likely to be in small, informal fi rms and in traditional low-value-added
industries.


Before showing the extent of gender sorting, however, there is a challenge of
defi nition: identifying a “female” (or “women’s”) enterprise is not easy. “Female”
could mean that the enterprise has one female owner among several owners,
even though the woman may have no control; or that the enterprise has several
owners, men and women, and a woman is the prime decision maker; or that the
enterprise has a sole female proprietor.


Th e Enterprise Surveys focus on ownership rather than control, defi n-
ing as female those enterprises where “any of the owners are female,” not
those where women are decision makers. Data from the six countries whose
surveys included a specifi c gender module (see box  1.3) supplement this
defi nition, as they identify fi rms where a woman is the main decision maker
with certainty and so can fl esh out the Enterprise Survey fi ndings. Another
approach to defi nition is to limit the sample to sole proprietors, on the
assumption that single owners identifi ed as women are most likely managers
as well (box 2.1).




48 ENTERPRISING WOMEN


BOX 2 .1


How to Designate “Female” and “Male” Enterprises:
Ownership, Control, or a Mixture?
Identifying which enterprises are “female” is diffi cult because the data sets use differ-
ent criteria.


Enterprise Surveys ask “Are any of the owners female?” and thus capture whether
there is any female participation in ownership. But this is a very broad measure. In
the fi ve countries with a follow-up gender module, the data show the discrepancies
between female participation in ownership and female decision making (fi gure B2.1.1).
One-third of fi rms with some female ownership do not have women sharing in
decisions, and one-half do not have women as the main decision maker.


For the vast majority of small fi rms, the same person is the owner, manager, and key
decision maker, so knowing the gender of that person is suffi cient. It is the larger, more
productive multiple-owner businesses that tend to have women among the owners,
but not as decision makers.


Sources: Enterprise Surveys’ gender module, World Bank, http://www.enterprisesurveys.org; Aterido and
Hallward-Driemeier 2011.
Note: Data are from 2010 for Sub-Saharan Africa. The figure shows a subset of firms in the gender module data
that are not sole proprietorships, that have been identified as female using the definition “any female owner,”
and for which information is available on the decision makers.


Figure B2.1.1 Up to Half of Firms with Some Female Ownership Are Not Run by Women


0


25


50


75


Small
1–10 employees


Medium
11–100 employees


Large
100+ employees


Number of employees in firm


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


w
it


h
at


le
as


t
on


e
fe


m
al


e
ow


ne
r


Woman is a decision maker


Woman is the decision maker




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 49


We thus present results using three different measures of female enterprises:


• Female participation in ownership. This is the measure available for the larger Enter-
prise Survey sample of countries. Using it will likely make it harder to distinguish
differences in either the constraints to or performance of businesses controlled by
women, as many fi rms controlled by men but with at least one female partial owner
will be included as female. As this measure may obscure potential gender gaps, it
probably provides a lower bound on what gender gaps are likely to be found; but
any gender gaps it captures are likely to be signifi cant.


• Women as prime decision maker. This measure is available for a subset of six coun-
tries that have data about both ownership and the control of decisions.


—Continued


Figure B2.1.2 Share of Formal Female Firms in Sub-Saharan Africa


0


10


20


30


40


50


Ni
ge


r


Mo
roc


co


Ma
law


i


Ma
uri


tan
ia


Ma
li


Co
ng


o,
De


m.
Re


p.


Gu
ine


a-B
iss


au


Eg
yp


t, A
rab


Re
p.


Ga
mb


ia,
Th


e


Ni
ge


ria


So
uth


Af
ric


a


Bu
rki


na
Fa


so


An
go


la


Mo
za


mb
iqu


e


Gu
ine


a


Ta
nz


an
ia


Se
ne


ga
l


Sw
az


ila
nd


Na
mi


bia


Ug
an


da


Bu
run


di


Ca
me


roo
n
Ke


ny
a


Rw
an


da


Za
mb


ia


Ca
pe


Ve
rde


Bo
tsw


an
a


Gh
an


a


Pe
rc


en
t


a. Formal firms with female participation in ownership firms




50 ENTERPRISING WOMEN


• Women as sole owner and decision maker. This approach restricts the sample to sole
proprietorships where the owner and decision maker are the same person. It makes
distinctions along gender lines much clearer, but the fi rms in the sample are often
smaller than in the Enterprise Surveys.


The larger Enterprise Surveys’ sample shows that the share of formal enterprises with
female participation in ownership is higher than the share of sole proprietors who are
women (fi gure B2.1.2). Averaging more than 25 percent in the region, female par-
ticipation in ownership has wide variation across countries, from Niger (10 percent) to
Ghana (nearly 50 percent).


Source: Aterido and Hallward-Driemeier 2011.


0


10


20


30


40


50


Ni
ge


r


Ma
uri


tan
ia


Bu
rki


na
Fa


so


So
uth


Af
ric


a


Co
ng


o,
De


m.
Re


p.


Ma
law


i


Mo
za


mb
iqu


e


Gu
ine


a-B
iss


au


Ug
an


da


Se
ne


ga
l


Na
mi


bia


Bu
run


di


Ke
ny


a


Za
mb


ia


Pe
rc


en
t


b. Formal sole proprietors with female participation in ownership firms


Figure B2.1.2 (continued)


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.


BOX 2 .1 con t i nued




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 51


Enterprise Size


Th e size of an enterprise is at once a signal of past success and an indicator
of future potential. Enterprises with many employees must have generated the
revenue to pay their wages. Larger fi rms are more likely to be realizing econo-
mies of scale and thus to be more effi cient. Larger fi rms are also likely bet-
ter positioned to weather shocks; adjustments can be made that change the
size of the fi rm, though not necessarily whether the fi rm remains in business
(Bigsten and Gebreeyesus 2007; Bigsten and Söderbom 2006; Frazer 2005;
Harding, Söderbom, and Teal 2006; Nichter and Goldmark 2009; Sleuwaegen
and Goedhuys 2002; Söderbom and Teal 2004; Van Biesebroeck 2005). As an
economy’s income rises, the share of output and employment accounted for by
larger fi rms rises. While larger fi rms are not necessarily likely to generate high
rates of further employment growth, the number of jobs created can be substan-
tial (Bartlesman, Haltiwanger, and Scarpetta, forthcoming).2


Th ere are a number of key thresholds where size matters. Th e fi rst is the basic
move from having no employees to having at least one employee—that is, the move
from self-employment to being an employer. Th is threshold is not merely an indi-
cation of scale; it involves a new set of processes and relationships—including the
need to monitor eff orts of employees and to specialize activities (Fafchamps and
others 2010). Another important threshold is determined by a country’s regula-
tory policies; an enterprise must register workers and meet certain other require-
ments (health and safety inspections, and so on) depending on the number of its
employees. For many countries this threshold is 10 employees. A third threshold
is somewhat more arbitrary, but tries to distinguish larger fi rms from smaller fi rms
by looking at whether processes are automated or have dedicated staff s (such as
inventory systems, marketing, human resources, and the like) and whether fi rms
are more likely to be accessing larger markets. We have used 100 employees as the
cutoff for this threshold (and occasionally use 500 to indicate the very largest fi rms).


On the broad criterion of female participation in ownership, Sub-Saharan
Africa has lower female participation than other regions at all fi rm sizes, averag-
ing 28 percent versus 39 percent—with the gap even greater among larger fi rms
(fi gure 2.1). Within Sub-Saharan Africa, the gender composition of enterprises
shows little diff erence by size until fi rms become fairly large.3


For sole proprietorships, the share of female enterprises is still lower in
Sub-Saharan Africa than elsewhere, but the gaps with other regions are less
pronounced (fi gure 2.2). Now the share of female enterprises declines with fi rm
size, not simply among the largest fi rms, but even among smaller fi rms, too.


Th e enterprise module data from the household surveys show similar
patterns of women tending to run smaller enterprises. Do the similarities stem
from industry selection? With women tending to be concentrated in more labor-
intensive activities, one might expect women’s fi rms to be larger, since size is




52 ENTERPRISING WOMEN


Figure 2.1 Firms with Some Female Ownership Are Smaller in Sub-Saharan Africa Than in
Other Regions


0


10


20


30


40


50


1–10 employees 11–100 employees 101–500 employees 500+ employees


Pe
rc


en
ta


ge
o


f f
em


al
e


ow
ne


rs
hi


p
(m


ea
n)


Sub-Saharan AfricaOther regions


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.


Figure 2.2 The Gender Ownership Gaps with Other Regions Are Smaller for Sole
Proprietorships Than for All Firms


0


10


20


30


40


1–10 employees 11–100 employees 100+ employees


Pe
rc


en
ta


ge
o


f f
em


al
e


so
le



pr


op
ri


et
or


sh
ip


(m
ea


n)


Sub-Saharan AfricaOther regions


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 53


measured by the number of employees. So to control for the role of diff erent
labor intensity across industries, average deviations from the industry mean were
calculated (fi gure 2.3). Even then, women’s fi rms are smaller, in all countries.


Enterprise Formality


Th e standard used here for determining whether a fi rm is “formal” is its registration
status. Whether a fi rm is registered does not only imply whether a fi rm pays taxes.
It indicates whether it is protected by the formal system of property rights and the
court system. It also indicates the market it operates in, the type of competition
it faces, and thus the quality standards it is likely to meet. Formal fi rms are more
likely to use contracts, thereby widening the extent of the market, as transactions
do not need to be based on relationships. While some unregistered businesses have
the potential to formalize, many others do not (de Mel, McKenzie, and Woodruff ,
forthcoming; La Porta and Shleifer 2011; McKenzie and Sakho 2010). While some
informal fi rms are dynamic and profi table, formal fi rms are more likely to be so
(Bigsten and Söderbom 2006; Falco and others 2009; Tybout 2000).


Figure 2.3 Women’s Firms Are Smaller Than Men’s (after controls for labor intensity)


Source: Hallward-Driemeier and Rasteletti 2010.
Note: The relative size of firms is with respect to mean size in the sector. Data are from national representative
household and labor force surveys in selected countries, most recent year (2000–10).


0


25


50


75


100


Ma
law


i
Gh


an
a



te


d’I
vo


ire


Ni
ge


ria


Ca
me


roo
n


Rw
an


da


Bu
rki


na
Fa


so
Ke


ny
a


Ni
ge


r


Sw
az


ila
nd


Sie
rra


Le
on


e


Ug
an


da


Co
mo


ros


Bu
run


di


Ga
mb


ia,
Th


e


Za
mb


ia


Re
la


ti
ve


s
iz


e
of


w
om


en
’s


fi
rm


s
to


m
en


’s




54 ENTERPRISING WOMEN


Figure 2.4 Informal Firms in Sub-Saharan Africa Are Often Female Run


0


10


20


30


40


50


60


70


Gu
ine


a-B
iss


au
Se


ne
ga


l
M


au
rit


an
ia


Gu
ine


a
Ga


mb
ia,


Th
e


Bu
ru


nd
i


So
ut


h A
fri


ca
M


oz
am


biq
ue


Co
ng


o,
De


m.
Re


p.
Ug


an
da


An
go


la
Ta


nz
an


ia
Ke


ny
a


Rw
an


da
Gh


an
a


Na
mi


bia
Bo


tsw
an


a
Sw


az
ila


nd


Pe
rc


en
ta


ge
o


f f
em


al
e


in
fo


rm
al


fi
rm


s
(m


ea
n)


a. All informal


In all countries, the share of informal fi rms run by women is higher than the
share of formal fi rms run by women; compare fi gure 2.4 and fi gure B2.1.2 in
box 2.1 (see also Bardasi, Blackden, and Guzman 2007; ILO 2002; Liedholm and
Mead 1999). Th ese data use the criteria of female participation in ownership.
Looking at sole proprietorship in the informal sector, the share that are run by
women mirrors the share of women in the informal sector overall.


Similarly, according to the survey of new entrepreneurs (see box 1.3), women
are more likely to be active in the informal sector: in the four countries sampled,
women ran 27 percent of the informal fi rms and only 18 percent of the formal ones.


Th is diff erence persists even aft er distinguishing between entrepreneurs who
are employers and those who are not. Employers are more likely to be registered
than nonemployers, but no clear pattern emerges to show that the gender gap
is signifi cantly wider for either group (fi gure 2.5).


Enterprise Industry


Industries diff er in their profi tability, size, and opportunities for growth. Some
industries earn higher profi ts than others; some industries are riskier than
others, with greater swings in likely profi ts. It can be relatively easy to start




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 55


Figure 2.4 (continued)


0


10


20


30


40


50


60


70


Pe
rc


en
ta


ge
o


f f
em


al
e


in
fo


rm
al


s
ol


e
p


ro
pr


ie
to


rs
hi


p
(m


ea
n)


b. Informal sole proprietors


Gu
ine


a-B
iss


au


Se
ne


ga
l


Ma
uri


tan
ia


So
uth


A
fric


a


Ga
mb


ia,
Th


e


Bu
run


di


Ug
an


da


Co
ng


o,
De


m.
Re


p.


An
go


la
Ke


ny
a


Ta
nz


an
ia


Rw
an


da


Gh
an


a


Na
mi


bia


Sw
az


ila
nd


Bo
tsw


an
a


Mo
za


mb
iqu


e


Gu
ine


a


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.


Figure 2.5 More Male-Owned Firms Are Registered—but with No Clear Difference in the
Gender Gaps between the Self-Employed and Employers


0


Ca
me


roo
n


Rw
an


da
Gh


an
a


Ke
ny


a


Co
mo


ros


Sie
rra


Le
on


e


Ma
law


i


Ni
ge


ria
Ni


ge
r


25


Pe
rc


en
ta


ge
o


f s
el


f-
em


pl
oy


ed
t


ha
t


a
re


r
eg


is
te


re
d 50


75


a. Registered self-employed


—Continued




56 ENTERPRISING WOMEN


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Registration is as reported in national representative household and labor force surveys for the most recent
year (2000–10).


0


Ca
me


roo
n


Rw
an


da


Za
mb


ia
Gh


an
a


Ke
ny


a


Co
mo


ros


Sie
rra


Le
on


e


Ma
law


i


Ni
ge


ria
Ni


ge
r


25


Pe
rc


en
ta


ge
o


f e
m


pl
oy


er
s


th
at



ar


e
re


gi
st


er
ed


50


75


b. Registered employers


Female Male


Figure 2.5 (continued)


a business in some industries, but diffi cult in others. Th ese features are oft en
related. Higher-return activities are oft en harder to enter; if entry was easy
the competition would increase and drive down profi ts. Factors that infl uence
the ease of entry include the amount of capital that is needed in an industry,
which aff ects the up-front investment needed to begin or expand operations.
Th e availability of capital is also related to the effi cient scale of operation and
whether a small business is likely to be feasible or not. Industries also vary in
the degree of specifi c knowledge that is needed to operate in them; a soft ware
designer, a tailor, and a metalworker have diff erent skills that require diff erent
amounts time and eff ort to acquire (Tybout 2000; World Bank 2012).4 Here, we
look at broad groupings of industries, from garments, food preparation, retail,
and other services that tend to be labor intensive and operate at small scale, to
various metalwork, machinery, chemicals, and other kinds of manufacturing
that tend to be capital intensive, formal, and larger scale. To the extent there is
gender sorting across industries, on average, women and men are likely to earn
diff erent returns and face diff erent prospects.


Unsurprisingly, female fi rms are not distributed uniformly across industries
(fi gure 2.6). Women more than men concentrate in services and traditional,
lower-value-added sectors such as the garment and food-processing sectors.




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 57


Figure 2.6 In Sub-Saharan Africa, Female-Owned Firms Are More Concentrated Than Men’s
in Lower-Value-Added Industries (formal sector)


0


10


20


30


40


50


Garment Food Services Metal Other
manufacturing


Pe
rc


en
ta


ge
a. Firms with female participation in ownership, all formal firms


0


10


20


30


40


50


Garment Food Services Metal Other
manufacturing


Pe
rc


en
ta


ge


b. Firms with female participation in ownership, all formal sole
proprietorships


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.




58 ENTERPRISING WOMEN


0


20


40


60


80


100


D
eg


re
e


of
fo


rm
al


it
y


an
d


fe
m


al
e


pa
rt


ic
ip


at
io


n
in


s
ec


to
r


(p
er


ce
nt


)


Tex
tile


s a
nd


ga
rm


en
ts


Re
tai


l sa
le


in
no


ns
pe


cia
lty


st
ore


s


Re
tai


l sa
le


of
tex


tile
s, c


lot
hin


g,
an


d f
oo


tw
are


Wh
ole


sal
e


Re
tai


l sa
le


of
foo


d,
be


ve
rag


es,
an


d t
ob


ac
co


Ot
he


r s
erv


ice
s


Ot
he


r m
an


ufa
ctu


rin
g


Ho
tel


an
d r


est
au


ran
t


Ot
he


r re
tai


l


Co
ns


tru
cti


on


Ch
em


ica
ls,


pla
sti


cs,
an


d r
ub


be
r


Tra
ns


po
rt


Fo
od


Ma
ch


ine
ry,


eq
uip


me
nt,


an
d e


lec
tro


nic
s


Ba
sic


m
eta


ls a
nd


m
eta


l p
rod


uc
ts


Formality Female


Figure 2.7 The Degree of Formality Is a Good Predictor of Women’s Participation in
an Industry


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


Men concentrate more in other manufacturing and metals. Female sole propri-
etors show similar patterns.


Th e likely degree of formality within a sector can itself be a predictor of
women’s participation (fi gure 2.7). Th e industry with the lowest share of  formal
entrepreneurs (42 percent) is the textile and garment industry, with a female
share of 35 percent. By contrast, the industry with the highest share of for-
mal entrepreneurs is basic metal and metal products (85 percent), where the
female share is only 3 percent.


Data from the household survey enterprise modules show similar trends of
women concentrated in sectors with lower barriers to entry and higher labor
intensity. In retail the share of female-headed fi rms tends to be much larger than
that of male-headed fi rms (fi gure 2.8). Th e position is reversed for construction,
transportation, and other services. Although in manufacturing the share of female-
headed fi rms is relatively high, most female-headed businesses are clustered in
food preparation, textiles, and garments—activities with low profi t margins.


With women disproportionately running smaller, more informal enter-
prises in lower-value-added industries, women’s economic opportunities are




59


Figure 2.8 Retail, Food, and Textiles Attract Female Entrepreneurs


0


10


20


30


40


Pe
rc


en
t


50


60


70


80


90


100


a. Female entrepreneurs—industry distribution


Bu
run


di


Bu
rki


na
Fa


so



te


d’I
vo


ire


Ca
me


roo
n
Co


ng
o


Co
mo


ros


Gh
an


a


Ga
mb


ia,
Th


e
Ke


ny
a


Ma
da


ga
sca


r


Ma
law


i


Rw
an


da


Sie
rra


Le
on


e


Sw
az


ila
nd


Ug
an


da


Za
mb


ia


0


10


20


30


40


Pe
rc


en
t


50


60


70


80


90


100


b. Male entrepreneurs—industry distribution


Bu
run


di


Bu
rki


na
Fa


so



te


d’I
vo


ire


Ca
me


roo
n
Co


ng
o


Co
mo


ros


Gh
an


a


Ga
mb


ia,
Th


e
Ke


ny
a


Ma
da


ga
sca


r


Ma
law


i


Rw
an


da


Sie
rra


Le
on


e


Sw
az


ila
nd


Ug
an


da


Za
mb


ia


Other services Retail


Construction Transportation


Manufacturing


—Continued




60 ENTERPRISING WOMEN


Figure 2.8 (continued)


0


10


20


30


40


50


60


70


80


Pe
rc


en
t


90


100


Bu
run


di


Bu
rki


na
Fa


so



te


d’I
vo


ire


Co
mo


ros


Gh
an


a


Ga
mb


ia,
Th


e
Ke


ny
a


Ma
law


i
Ni


ge
r


Ni
ge


ria


Rw
an


da


Sie
rra


Le
on


e


Ug
an


da


Za
mb


ia


c. Female-headed household enterprises—industry distribution


Source: Household surveys’ enterprise modules, selected countries, various years (2000–10).


0


10


20


30


40


50


60


70


80


90


100


d. Male-headed household enterprises—industry distribution


Other manufacturing Textile Food


Bu
run


di


Bu
rki


na
Fa


so



te


d’I
vo


ire


Co
mo


ros


Gh
an


a


Ga
mb


ia,
Th


e
Ke


ny
a


Ma
law


i
Ni


ge
r


Ni
ge


ria


Rw
an


da


Sie
rra


Le
on


e


Ug
an


da


Za
mb


ia


Pe
rc


en
t




THE SIZE, FORMALITY, AND INDUSTRY OF ENTERPRISES 61


more limited than men’s. Improving the conditions that face their existing
businesses may help, but a more promising agenda is to enable more women
to move into higher-return activities. Looking at how the extent of gender
sorting in entrepreneurship varies across countries and by characteristics of
the entrepreneur provides insights into what the constraints are and how they
can be overcome.


Notes
1. See, for example, Mead and Liedholm (1998) and World Bank (2004).
2. Th e donor community traditionally focuses attention on small enterprises, heralding


them as signifi cant job creators. As the data here and in chapter 1 have demonstrated,
micro and small enterprises can employ large numbers of people, but their potential
to grow and become large fi rms is far more limited. See Page and Söderbom (2012)
for a discussion.


3. For a discussion of women’s enterprises in a diff erent region, see Bruhn’s (2009)
analysis of women’s enterprises in Latin America.


4. Industries can also vary in the extent of product diff erentiation, the importance of
quality, the range of products within an industry, the importance of branding, and
so on—issues for which we do not have good proxies in the available data.


References
Aterido, R., and M. Hallward-Driemeier. 2011. “Whose Business Is It Anyway?” Small


Business Economics 37 (4): 443–64.
Bardasi, E., M. Blackden, and J. C. Guzman. 2007. “Gender, Entrepreneurship, and


Competitiveness.” In Africa Competitiveness Report 2007, edited by World Economic
Forum, African Development Bank, and World Bank. Washington, DC: World
Economic Forum, African Development Bank, and World Bank.


Bartlesman, E., J. Haltiwanger, and S. Scarpetta. Forthcoming. “Cross Country
Diff erences in Productivity: Th e Role of Allocative Effi ciency.” American Economic
Review.


Bigsten, A., and M. Gebreeyesus. 2 007. “Th e Small, the Young, and the Productive:
Determinants of Manufacturing Firm Growth in Ethiopia.” Economic Development
and Cultural Change 55 (4): 813–40.


Bigsten, A., and M. Söderbom. 2006 . “What Have We Learned from a Decade of
Manufacturing Enterprise Surveys in Africa?” World Bank Research Observer 21 (2):
241–65.


Bruhn, M. 2009. “Female-Owned Firms in Latin America: Characteristics, Perfor-
mance, and Obstacles to Growth.” Policy Research Working Paper 5122, World Bank,
Washington, DC.


de Mel, S., D. McKenzie, and C. Woodruff . Forthcoming. “Th e Demand for, and
Consequences of, Formalization among Informal Firms in Sri Lanka.” AEJ: Applied
Economics.


Fafchamps, M., D. McKenzie, S. Quinn, and C. Woodruff . 2010. “When Is Capital
Enough to Get Female Microenterprises Growing? Evidence from a Randomized




62 ENTERPRISING WOMEN


Experiment in Ghana.” NBER Working Paper 17207, National Bureau of Economic
Research, Cambridge, MA.


Falco, P., A. Kerr, N. Rankin, J. Sandefur, and F. Teal. 2009. “Th e Returns to Formality
and Informality in Urban Africa.” CSAE Working Paper Series 2010-03, Centre for the
Study of African Economies, Oxford, U.K.


Frazer, G. 2005. “Which Firms Die?: A Look at Exit from Manufacturing in Ghana.”
Economic Development and Cultural Change 53 (3): 585–617.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Harding, A., M. Söderbom, and F. Teal 2006. “Th e Determinants of Survival among
African Manufacturing Firms.” Economic Development and Cultural Change 54 (3):
533–56.


ILO (International Labour Organization). 2002. “Women and Men in the Informal
Economy: A Statistical Picture.” Gender and Employment Sector, ILO, Geneva.


La Porta, R., and A. Shleifer. 2011. “Th e Unoffi cial Economy in Africa.” NBER Working
Paper 16821, National Bureau of Economic Research, Cambridge, MA.


Liedholm, C., and D. Mead. 1999. Small Enterprises and Economic Development: Th e
Dynamics of Micro and Small Enterprises. London: Routledge.


McKenzie, D., and Y. S. Sakho. 2010. “Does It Pay Firms to Register for Taxes? Th e Impact
of Formality on Firm Profi tability.” Journal of Development Economics 91: 15–25.


Mead, D. C., and C. Liedholm. 1998. “Th e Dynamics of Micro and Small Enterprises in
Developing Countries.” World Development 26 (1): 61–74.


Nichter, S., and L. Goldmark. 2009. “Small Firm Growth in Developing Countries.”
World Development 37 (9): 1453–64.


Page, J., and M. Söderbom. 2012. “Is Small Beautiful? Small Enterprise, Aid and Employ-
ment in Africa.” Working paper, Brookings Institutions, Washington, DC.


Sleuwaegen, L., and M. Goedhuys. 2002. “Growth of Firms in Developing Countries,
Evidence from Côte d’Ivoire.” Journal of Development Economics 68 (June): 117–35.


Söderbom, M., and F. Teal. 2004. “Size and Effi ciency in African Manufacturing Firms:
Evidence from Firm-Level Panel Data.” Journal of Development Economics 73 (Febru-
ary): 369–94.


Tybout, J., R. 2000. “Manufacturing Firms in Developing Countries: How Well Do Th ey
Do, and Why?” Journal of Economic Literature 28 (March): 11–44.


Van Biesebroeck, J. 2005. “Firm Size Matters: Growth and Productivity Growth in
African Manufacturing.” Economic Development and Cultural Change 53 (3): 545–83.


World Bank. 2004. World Development Report 2005: A Better Investment Climate for
Everyone. New York: Oxford University Press.


. 2012. World Development Report 2013: Jobs. New York: Oxford University Press.




Part II


Why Women Work
Where They Do
Th e gender sorting across types of entrepreneurial activities laid
out in Part I is not uniform across countries or across all women
within a country. Th is section looks at the factors associated with
variations in the extent to which women operate enterprises that
are smaller, more informal, and in traditional sectors. It examines
key characteristics, both at the level of the country and of the
individual. Two dimensions are particularly important: gender
gaps in human capital, particularly access to managerial and busi-
ness skills, and the ability to own and control assets. Th e entrepre-
neur’s age, marital status, and prior work experience matter too.






65


Chapter 3


Effect of Country Patterns in Income,
Human Capital, and Assets on
Where Women Work


This chapter examines what contributes to the gender-differentiated
patterns of entrepreneurship across countries. It analyzes how much of the
variation in women’s overrepresentation in self-employment and relative
underrepresentation among employers can be explained simply by a country’s
level of income. Do relatively more women move from self-employment to
being an employer—or move into wage employment—as a country develops?


Beyond income, a range of country characteristics has been proposed to
explain diff erences in income and growth, from geography to social capital to
rule of law (see for example Acemoglu, Johnson, and Robinson 2002; Acemoglu
and Johnson 2005; Hall and Jones 1999; Rodrik, Subramanian, and Trebbi 2004).
Increasing attention is being paid to the magnitude and sources of frictions that
lead to a misallocation of resources and thus reduce productivity (Hsieh and
Klenow 2009); a range of empirical studies in Sub-Saharan Africa looks at the
roles of the availability of infrastructure services, fi nance, the quality of gover-
nance, and business regulations in explaining diff erences in fi rm performance
between and within countries (Aterido and Hallward-Driemeier 2010; Bigsten
and Söderbom 2006; Bigsten and others 2003; Dollar, Hallward-Driemeier,
and Mengistae 2005; World Bank 2004).1 Many of these frictions or constraints
in the investment climate are examined in the next chapters, but this chapter
argues for the importance of looking at indicators of two critical inputs in run-
ning a business: human capital, and access to and control over assets.


Th e analysis here, using data from 37 Sub-Saharan African countries, fi nds
that while country income is associated with some trends in entrepreneurship,
it alone cannot explain all the diff erences in patterns across countries; there
is a great deal of country variation in women’s entrepreneurship at any given
income level. Using adult literacy as a measure of basic human capital shows
that where gender gaps in adult literacy are large, so too is the relative share of
women in self-employment. Higher shares of female employers, on the other




66 ENTERPRISING WOMEN


hand, are associated with greater legal protection of women’s economic rights.
What is particularly striking about this fi nding is that gender gaps in these legal
protections are as prevalent in Sub-Saharan Africa’s middle-income countries as
low-income countries; closing the gender gaps in legal protections and strength-
ening women’s property rights in particular will thus require active engagement
and will not simply follow from increases in countries’ income.


Th e discussion brings to the fore the importance of women’s legal rights,
and in particular, secure property rights, for women entrepreneurs ( examined
further in chapter  7) and the importance of human capital for expanding
opportunity for women entrepreneurs (chapter 9). Th ese factors, along with
improved access to fi nance (chapter  8) and a greater voice for women in
infl uencing the business environment (chapter 10), have a vital contribution to
make in expanding opportunities for women entrepreneurs.


The Importance of Income: A Cross-Country Perspective


Th e next few fi gures are constructed using country data rather than regional
averages. Th e patterns of entrepreneurship across income levels are traced
out based on cross-country variations, not on changes in entrepreneurship as
countries develop. Th us as any given country develops, it will not necessarily
follow the relationships described here.


Putting Nonagricultural Employment in Context
Diff erences in income help explain much of the interregional variation in labor
force participation and sector of employment (agriculture or nonagriculture) as
described in chapter 1.2 Th e share of women not in the labor force is lowest
in low-income countries, rises with country income, and then declines a little
(fi gure 3.1). For men the pattern is more muted (fi gure 3.2). Th us higher gross
domestic product (GDP) per capita is associated with greater feminization of
those not in the labor force (fi gure 3.3); among those not in the labor force, a
higher share is female as incomes rise. Even taking into account Sub-Saharan
Africa’s many low-income countries, the region still has high rates of female labor
force participation, so many of its countries actually lie below the fi tted curve.


Female and male employment outside agriculture rises with income.
Although the gap between them remains higher at higher incomes, the relative
share of women among those in nonagricultural employment does not exhibit
signifi cant variation by income.


Th e rise in women’s participation in nonagricultural employment is primarily
driven by a steep decline in the share of women in agriculture—and despite a
rising share of women not in the labor force, it rises until it reaches middle levels
of income before fl attening and then declining a little at higher levels of income.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 67


Figure 3.1 Initially, the Share of Women Not in the Labor Force Rises Steeply with Country
Income


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle-income economies,
most recent years (2000–10).


0


20


40


60


80


Pe
rc


en
ta


ge
o


f f
em


al
e


po
pu


la
ti


on


6 7 8 9 10
GDP per capita (log)


Not in labor forceNonagricultural labor force Agriculture


0


20


40


60


80


Pe
rc


en
ta


ge
o


f m
al


e
po


pu
la


ti
on


6 7 8 9 10
GDP per capita (log)


Not in labor force Nonagricultural labor force Agriculture


Figure 3.2 The Share of Men Not in the Labor Force Shows Little Change as Country Income
Climbs


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle-income economies,
most recent years (2000–10).




68 ENTERPRISING WOMEN


Men’s participation in agriculture is lower than women’s at low incomes,
and declines with income, but less steeply. Fewer men are not in the labor
force, and the rate does not change much with income. Th e share of men in
nonagricultural employment rises with income, proportionately faster than
the comparable share for women, so the share of women in nonagricultural
employment changes little, remaining at around 40 percent (fi gure 3.3).


Overall, therefore, as GDP per capita rises, the share of women falls in
agriculture but shows little change in nonagricultural employment. Th ese
patterns also mask much variation among countries at any given level of GDP
per capita. Clearly income does not explain the whole story.


Looking within Nonagricultural Employment
Within nonagricultural employment, self-employment generally falls as income
increases, particularly for women (fi gure 3.4). At the lowest income levels, more
than 60 percent of women are self-employed, and fewer than 20 percent are
wage earners. At middle incomes the shares are closer to equal. Th e share of
employers always tends to be low, changing little with country income.


Figure 3.3 The Share of Women in Nonagricultural Employment Changes Little as Country
Income Rises


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle- income economies,
most recent years (2000–10).


30


40


50


60


70


Pe
rc


en
ta


ge
t


ha
t


is
fe


m
al


e


6 7 8 9 10


GDP per capita (log)


Nonagricultural labor force Agriculture Not in labor force




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 69


Among men at low incomes, roughly equal shares are self-employed and wage
earners, with the gap quickly widening to favor wage earners as incomes climb. As
with women, a small but fairly consistent share consists of employers (fi gure 3.5).


Th e patterns in fi gures 3.4 and 3.5 are consistent and include a relatively
large share of self-employed who are necessity entrepreneurs: where wage jobs
are scarce, there are few alternatives to self-employment (chapter 1). Strikingly,
even with such a large pool of self-employed at lower country incomes, the
total share of those working outside agriculture who become employers climbs
little as income rises. At higher incomes wage employment is more plentiful,
self-employment is lower, and the share of necessity entrepreneurs is lower as
employers represent a growing share of the self-employed.


By employment category, the share of self-employed who are women starts
at nearly 50 percent at lower incomes, then falls approaching middle incomes
(fi gure 3.6). Th e female share of wage earners, in contrast, starts low but rises
smoothly with income. Th is pattern is consistent with self-employment falling,
and wage employment rising, faster for women than men as income rises (see
fi gures 3.4 and 3.5).


0


20


40


60


80


6 7 8 9 10


Pe
rc


en
ta


ge
o


f w
om


en
in



no


na
gr


ic
ul


tu
ra


l l
ab


or
fo


rc
e


GDP per capita (log)


Where women work


Self-employed Unpaid family workers


Wage workers Employers


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle-income economies,
most recent years (2000–10).


Figure 3.4 Female Self-Employment Falls with an Increase in Country Income
(nonagricultural employment)




70 ENTERPRISING WOMEN


0


20


40


60


80


6 7 8 9 10


Pe
rc


en
ta


ge
o


f
m


en
in



no


na
gr


ic
ul


tu
ra


l l
ab


or
f


or
ce


GDP per capita (log)


Where men work


Self-employed Wage workers


Unpaid family workers Employers


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle-income economies,
most recent years (2000–10).


Figure 3.5 Male Wage Earners Gain as Income Improves (nonagricultural employment)


20


40


30


50


6 7 8 9 10


Pe
rc


en
ta


ge
t


ha
t


is
fe


m
al


e


GDP per capita (log)


Self-employed Wage workersEmployers


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on national household and labor force surveys for 101 low- and middle-income economies,
most recent years (2000–10).


Figure 3.6 Women Account for around a Quarter of Employers, Irrespective of
Country Income (nonagricultural employment)




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 71


A striking point is that the share of women as employers changes little as GDP
climbs, with women representing just over a quarter of employers (fi gure 3.6).


Again, income accounts for some of the variation in labor force activities,
but not all.3 Th e next section looks at other country-level explanations. Th e next
chapter then looks at factors at the individual level.


Cross-Country Patterns of Entrepreneurship: Human
Capital (Literacy) and Access to Assets (Property Rights)


Various international organizations have computed composite indicators that
try to capture gender equality and women’s opportunities. Th ese indicators
show wide variation among countries, with some countries—including many in
Sub-Saharan Africa—presenting substantial gender inequalities. Th e indicators
also rank countries diff erently (though general correlations emerge) because
each indicator focuses on diff erent dimensions of gender equality, and country
performance varies by dimension. A country may have low adult female literacy
or high maternal mortality, for example, but also have high female political
participation. Gender equality (or inequality) in one dimension does not
necessarily imply gender equality (or inequality) across other dimensions.


Some of these dimensions are more relevant to entrepreneurship than others.
Most relevant are measures of human capital and of access to and control over
assets. But while almost all indicators include dimensions of human capital, not
all of them have variables for access to and control over assets. To fi ll this gap,
this chapter uses the Women’s Legal and Economic Empowerment Database for
Africa (Women–LEED–Africa).4 Th at database contains information on consti-
tutional provisions, ratifi ed international conventions, and statutes (particularly
family, inheritance, and land legislation) to capture where women’s economic
rights diff er from men’s.


Using female literacy as a measure of human capital and Women–LEED–
Africa indicators, the chapter divides countries into four categories: small gen-
der gaps in literacy, large gender gaps in literacy, small gaps in women’s legal and
economic rights, and large gaps in women’s legal and economic rights. Th ese
four categories become a means of examining how country characteristics help
explain variations in sorting and performance.


Indicators of Gender Equality and Opportunity—
From International Organizations
Th e organizations that compute indicators of gender equality and opportunity
include the Economist Intelligence Unit, Organisation for Economic Co-operation
and Development (OECD), United Nations Development Programme,
World Bank, and World Economic Forum (figure  3.7 and appendix  B).




72 ENTERPRISING WOMEN


a. Inverse of the Gender Inequality Index


In
de


x
va


lu
e


(2
00


8)


Su
b-S


ah
ara


n A
fric


a


So
uth


As
ia


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d N
ort


h A
fric


a


0.2


0.4


0.6


0.8


Figure 3.7 Indicators of Equality and Opportunity Vary, but Most Show Sub-Saharan Women
in a Challenging Environment


Su
b-S


ah
ara


n A
fric


a


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d N
ort


h A
fric


a


So
uth


As
ia


In
de


x
va


lu
e


b. Global Gender Gap Index


0.55


0.60


0.65


0.70


0.75




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 73


Figure 3.7 (continued)


c. Country Policy and Institutional Assessments Gender Equality Rating
In


de
x


va
lu


e


Su
b-S


ah
ara


n A
fric


a


So
uth


As
ia


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d N
ort


h A
fric


a


2


3


4


5


d. Social Institutions and Gender Index


In
de


x
va


lu
e


(2
00


9)


Su
b-S


ah
ara


n A
fric


a


So
uth


As
ia


Ea
st


As
ia


an
d P


aci
fic


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d N
ort


h A
fric


a


0.6


0.7


0.9


1.0


0.8


—Continued




74 ENTERPRISING WOMEN


e. Women’s Economic Opportunity Index
In


de
x


va
lu


e


Su
b-S


ah
ara


n A
fric


a


So
uth


As
ia


Ea
st


As
ia


an
d P


ac
ific


Eu
rop


e a
nd


Ce
ntr


al
As


ia


La
tin


Am
eri


ca
an


d t
he


Ca
rib


be
an


Mi
dd


le
Ea


st
an


d N
ort


h A
fric


a


20


40


60


80


Figure 3.7 (continued)


Sources: Figure 3.7a: United Nations Development Programme, Gender Inequality Index, 2010, http://hdr.undp
.org/en/statistics/gii/NDP; figure 3.7b: World Economic Forum, Global Gender Gap Index, http://www.weforum
.org/issues/global-gender-gap; figure 3.7c: World Bank, Country Policy and Institutional Assessments Gender
Equality Rating, http://www.worldbank.org/ida; figure 3.7d: OECD, Social Institutions and Gender Index,
http://www.oecd.org/dataoecd/52/33/42289479.pdf; figure 3.7e: Economist Intelligence Unit, Women’s Economic
Opportunity Index, http://www.eiu.com/sponsor/WEO.
Note: As drawn, a higher index score indicates greater equality. See appendix B for descriptions of the indexes.
Figure 3.7e excludes outside values.


Th eir  methodologies diff er, providing an array of approaches and country
rankings. For example, indicators that emphasize levels of education or health
outcomes tend to rank low-income countries near the bottom—and Sub-Saharan
Africa performs poorly. Th ose with measures of political participation throw up
diff erent rankings, given a weaker correlation between the number of women par-
liamentarians and economic development, gender gaps in health, or education.


Th ese composite indicators are instructive in that they off er evidence of con-
tinuing gender gaps in constraints and opportunities across countries. But none
is fully appropriate for isolating the eff ects of particular dimensions of gender
inequality. Some include measures that are not of fi rst-order importance to entre-
preneurship. Female maternal mortality or gender gaps in child mortality may
indicate women’s broader place in society, but they are not of direct relevance here.
Some measures do include labor force participation—that is, the share of women
in the nonagricultural labor force. Th ere are two concerns about these measures.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 75


First, it is unclear whether high rates of participation constitute a positive
indicator—high rates of necessity entrepreneurs, for example, are not always a sign
of women’s empowerment. Second and more important, labor force participation
rates are one of the outcomes we want to explain. So the outcome measure cannot
be used as a source of the explanation for its variation across countries.


Another shortcoming of some measures is country coverage. Some institu-
tions have greater coverage of Sub-Saharan Africa than others. Th e World Bank’s
Country Policy and Institutional Assessment covers 34 countries, the United
Nations Development Programme’s Gender Inequality Index 31, the World
Economic Forum’s Global Gender Gap Index 25, and the Women’s Economic
Opportunity Index of the Economist Intelligence Unit 22. Th e OECD’s Social
Institutions and Gender Index has 39 countries and thus the widest coverage,
making it of particular interest. It also includes a wider set of measures that
contain information about social institutions and women’s rights, which could
be relevant for entrepreneurship. Its measures are, however, based on largely
subjective responses of experts in each country, rendering it harder to judge the
comparability across countries and over time.


Two Indicators of Gender Equality and Opportunity:
Women’s Literacy, and Legal and Economic Rights
Given the foregoing limitations, we developed a diff erent set of indicators to
capture women’s equality, using fi ve criteria to select a narrower set of dimensions.
Th e most important criterion was to capture the factors most relevant for entrepre-
neurship. Entrepreneurs run a business, and an enterprise’s output is based on the
quality and quantity of human capital and on the enterprise’s assets.5 Th e ability to
control these resources and any resulting profi ts provide the incentives to grow. So,
measures of human capital and measures of property rights are of prime interest.


Th e second criterion was to select measures that are not overly correlated with
each other, because it is highly unlikely that a single dimension fully explains
variations in country outcomes. Th e third was to preserve simplicity. Rather than
use multiple dimensions to construct a single composite indicator, the aim was
to have only a limited number of dimensions that could be examined together.
Th e fourth criterion was to have adequate country coverage. Th e fi ft h was to have
objective measures as much as possible rather than subjective assessments, which
might refl ect biases due to respondent selection or might be diffi cult to replicate.


Following these criteria, we selected two measures: adult female literacy, and
a measure of gender gaps in women’s legal and economic rights.


We opted for adult female literacy (among the potential human capital vari-
ables) because it is more appropriate for our purposes than current educational
enrollment rates. Given the huge increase in enrollment in recent years, current
enrollment levels or educational attainment of recent graduates is likely to be
much higher than levels for older generations that are still economically active.




76 ENTERPRISING WOMEN


Adult literacy rates thus better capture the level of human capital across the full
age spectrum of potential entrepreneurs.


Of the measures of female literacy, we had two choices. One was to look at
female literacy within the adult population.6 Th is approach measures the basic
human capital available, but it does not capture a sense of potential gender gap.
An alternative was to look at the gender gap between female and male literacy.
Th ese two measures have an extremely high correlation (fi gure 3.8).


In countries where women’s literacy is high, gender gaps are quite small.
Where female literacy is low, male literacy is generally not as low and
the  percentage gap between men and women is high. But the linearity of the rela-
tionship between the female level and gender gaps breaks down at the extreme
low end, where Niger and Guinea-Bissau, and to a lesser extent Ethiopia, have
low female literacy and particularly large gender gaps.


Th e choice of the measure for gender gaps in women’s legal and economic
rights raised more questions. Because we were interested in variables that
were not simply correlated with income or the human capital measure, we
reexamined indicators from international organizations (fi gure  3.9). Aft er
we controlled for GDP per capita, variation beyond literacy remained, so the
indexes are capturing other sources of variation that could be meaningful.


0


20


40


60


80


100


120


140


160


180


200


20 40 60 80 100


Pe
rc


en
ta


ge
g


ap
in


w
om


en
’s


a
nd


m
en


’s
li


te
ra


cy


Percentage of adult women who are literate


Figure 3.8 The Correlation Is High between Low Levels of Women’s Literacy and Large
Gender Gaps in Literacy


Source: World Bank, World Development Indicators database, http://data.worldbank.org/indicator.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 77


–0.2
MLI


TCD


ETH
GIN


BFA
NER


BEN
MOZ


NGA


SEN
CIV


GMB
CAF


MRT


GHATZA
BDI


MDG


TUN
MUS


SWZ


GNQ ZWE


GAB


BWA
NAM


ZAF


KENMWI


RWA
UGA
LBR


OMRZMB


TGO


ZAR


ERT


SLE


–60 –40 –20 0 20 40


–0.1


0


0.1


a. Social Institutions and Gender Index


In
de


x
va


lu
e


Adult female literacy


Figure 3.9 Variation beyond Literacy Remains after GDP per Capita Is Controlled for
(using indicators from international organizations)


Sources: Author’s calculations using the database of national household and labor force surveys for 101 low-
and middle-income economies, most recent years (2000–10); OECD, Social Institutions and Gender Index,
2010, http://www.oecd.org/dataoecd/52/33/42289479.pdf (figure 3.9a); and United Nations Development
Programme, Gender Inequality Index, http://hdr.undp.org/en/statistics/gii/ NDP (figure 3.9b).
Note: Analysis controls for GDP per capita. See appendix B for more information on the indexes used.


–60 –40


CIV
ZAR


SDN ZMB


LBRTODCAF
MAT


MOZ


BDI
RWA


ZAF


BWA
SAB


NAM
SWZ


ZWE
LSO


TUN


MUS


BEN


SEN


NER


SLB


CMR
CMB MOM KEN


–20 0 20 40


–0.2


–0.4


0


0.2


0.4


b. Inverse of the Gender Inequality Index


In
de


x
va


lu
e


Adult female literacy




78 ENTERPRISING WOMEN


Th ese indicators were not, however, specifi cally focused on measures of
property rights or the ability to own and control assets. Indicator subcomponents
that had this focus were based on subjective rather than objective assessments
(in, for example, the Social Institutions and Gender Index, the Gender Inequality
Index, and the Women’s Economic Opportunity Index).


Th e Women, Business, and the Law database, launched by the World Bank
in March 2010, provided part of the answer (see appendix C). It assessed legal
rights for 28 Sub-Saharan African countries, looking at whether property rights
and women’s legal capacity were the same as men’s. But it did not go far enough.
Th is study mainly used Women–LEED–Africa, which covers all 47 countries in
the region.7 It provides more-detailed indicators of where women’s economic and
legal rights can diff er from men’s, and it explicitly includes formal customary law.
Because the indicators are based on the constitutions and laws on the books in these
countries,8 the measures are not subjective assessments or qualitative rankings. Th e
categorization of countries can be replicated—and tracked consistently over time.9


Women–LEED–Africa focuses on constitutional protections of
nondiscrimination based on gender. Every country in the region espouses
this principle. However, despite the inclusion of nondiscrimination as one of
the framing principles of each country’s legal system, the majority of coun-
tries have formally recognized exceptions in key areas of women’s economic
rights. Twelve countries recognize in their constitution that customary law
prevails over issues of marriage, property, and inheritance—and explicitly
exempt customary law from nondiscrimination provisions. Twenty-two coun-
tries have head-of- household statutes that give husbands the legal authority to
stop their wives from working outside the home or opening a bank account.
Married women’s ability to testify in court or to initiate legal proceedings can
also be limited. Finally, some countries provide no statutory protections for
women to keep a share of marital property on divorce or inheritance.


Some countries have only one such provision, some have several. To keep the
groupings simple, we divided countries by whether they had any of these provi-
sions.10 Th e division is not quite equal: more countries have legal gaps in women’s
property and legal rights than have no or limited gender gaps in these rights.


It is particularly striking that the division has no link to income or female
literacy—women’s legal rights are not proxies for them (fi gures 3.10 and 3.11).
Higher-income or more-developed countries—or ones that have closed the
gender literacy gap—are not less likely to have gender gaps in legal rights. Th is
fi nding implies that income growth alone is insuffi cient to close these legal gaps.
More active measures are needed.


It is encouraging for this analysis that women’s legal and economic rights
do not appear correlated with income or literacy. It validates the selection of
this indicator, as it means that the variation in rights is capturing a distinct
dimension that should have explanatory power independent of income.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 79


0


1


2


3


4


5


6


7


8


9


10


Co
ng


o,
De


m.
Re


p.


Bu
run


di
Ni


ge
r


Sie
rra


Le
on


e


Rw
an


da
To


go


Gu
ine


a
Ma


li


Ma
da


ga
sca


r


Ta
nz


an
ia
Za


mb
ia
Gh


an
a


Ga
mb


ia,
Th


e


Le
so


tho
Ke


ny
a


Ni
ge


ria


Ma
uri


tan
ia



te


d’I
vo


ire


Ca
me


roo
n


Co
ng


o,
Re


p.


Sw
az


ila
nd


Ma
uri


tiu
s


Ga
bo


n


G
D


P
pe


r
ca


pi
ta


(l
og


)


a. Weak legal rights for women


Figure 3.10 The Distribution of Income Is Very Similar across Countries with Weaker and
Stronger Rights for Women


Sources: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Eco-
nomic Empowerment Database; World Bank, World Development Indicators database, http://data.worldbank
.org/indicator.


0


1


2


3


4


5


6


7


8


9


10


Lib
eri


a


Mo
za


mb
iqu


e


Eth
iop


ia


Ma
law


i


Ug
an


da


Bu
rki


na
Fa


so


Co
mo


ros
Be


nin


Se
ne


ga
l


Ca
pe


Ve
rde


An
go


la


Na
mi


bia


So
uth


Af
ric


a


G
D


P
pe


r
ca


pi
ta


(l
og


)


b. Strong legal rights for women




80 ENTERPRISING WOMEN


0


10


20


30


40


50


60


70


80


90


100


Ma
li


Ni
ge


r


Sie
rra


Le
on


e


Ga
mb


ia,
Th


e



te


d’I
vo


ire


Ma
uri


tan
ia


Ni
ge


ria


Bu
run


di
To


go
Gh


an
a
Co


ng
o


Ta
nz


an
ia


Za
mb


ia


Ca
me


roo
n


Rw
an


da


Ma
da


ga
sca


r


Ke
ny


a


Sw
az


ila
nd


Ma
uri


tiu
s


Ga
bo


n


Le
so


tho


A
du


lt
fe


m
al


e
lit


er
ac


y
ra


te


a. Weak legal rights for women


Figure 3.11 The Distribution of Female Literacy Is Very Similar across Countries with Weaker
and Stronger Rights for Women


0


10


20


30


40


50


60


70


80


90


100


Bu
rki


na
Fa


so


Eth
iop


ia
Be


nin


Mo
za


mb
iqu


e


Se
ne


ga
l


Lib
eri


a


An
go


la


Ug
an


da


Ma
law


i


Co
mo


ros


Na
mi


bia


Ca
pe


Ve
rde


So
uth


Af
ric


a


A
du


lt
fe


m
al


e
lit


er
ac


y
ra


te


b. Strong legal rights for women


Sources: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database; World Bank, World Development Indicators database, http://data.worldbank.org/indicator.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 81


Th at some countries have raised their incomes in a context of less secure
legal and economic rights for women does not mean that women have benefi ted
equally from higher incomes. Indeed, what is precisely of interest is to examine
the eff ects that legal and economic rights have on the extent and composition
of women’s entrepreneurship.


Th e claim is not that formal laws are determinative, or that they are the only
factor shaping how property rights are protected in practice. Th e institutional
capacity of the legal system to enforce laws varies across all countries, and prac-
tical constraints to accessing the formal system can deter many ( particularly
poorer, less educated) women, from seeking the rights they have. Customs
and traditions also set expectations for how property and other assets are to be
controlled and passed on, regardless of formal laws. But the law still provides
the fi nal say in formal disputes, and the nature of the protections it provides
aff ects people’s ability to access and control resources and their incentives to
expand their business. Particularly as economies develop and third-party trans-
actions become a larger part of how business is conducted, the role of formal
rules becomes all the more important.


Link between Entrepreneurship and Access to Human
Capital and Assets


Th e chapter now develops country groups based on female literacy and mea-
sures of gender gaps in legal and economic rights. Using these two measures,
countries are divided into four categories based on whether they have small or
large gender literacy gaps and small or large gender gaps in legal and economic
rights. We fi rst compare gender gaps among these country groupings within
each employment category, then across categories.


Gender Gaps in Participation within Employment Categories
For the self-employed there are clear patterns across higher and lower literacy
groups, for both women and men (fi gure 3.12). Where gender literacy gaps
are large, close to 60  percent of women are self-employed, compared with
near 40  percent for men. Where gender literacy gaps are smaller, women’s
rates are now near 40 percent, while men’s rates have fallen to 25–30 percent.
Th e diff erences by legal status are much less signifi cant. Strikingly, while the
rates of self-employment are lower for both women and men in countries with
higher rates of literacy, there is little diff erence in the percentage gap in rates
between women and men across the four country groups. Women are more
than 30  percent more likely to be in self-employment than men.


In contrast, when looking at gender gaps among employers, one fi nds the
results are more sensitive to the extent of gaps in women’s legal and economic




82 ENTERPRISING WOMEN


Sources: Women’s Legal and Economic Empowerment Database; World Bank, World Development Indicators
database, http://data.worldbank.org/indicator.


0


10


20


30


40


50


60


70


Weaker


rights


Stronger


rights


Weaker


rights


Stronger


rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
o


f
se


lf
-e


m
pl


oy
ed


w
om


en
(m


en
)


a. Self-employment


Women Men


Figure 3.12 Gender Gaps in Literacy Are Correlated with Patterns in Self-Employment


0


5


10


15


20


25


30


35


40


45


Weaker
rights


Stronger
rights


Weaker
rights


Stronger
rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
g


ap
o


f w
om


en
o


ve
r


m
en


b. Gender gap among self-employed




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 83


rights (fi gure 3.13). Th e share of women who are employers is about 1 percent
where there are large literacy gaps, with the rate increasing by more than one-
third in countries with smaller literacy gaps, and tripling where both literacy
gaps and legal gaps are small. For men the rates of being an employer are much
the same where there are legal gaps, lower where literacy gaps are large and legal
gaps smaller (a bit of a puzzle), and larger again where literacy and legal gaps are
both small. However, the changes are proportionally larger for women, so the
gaps in fi gure 3.13b show how literacy and particularly greater legal protections
close the gender gap in participating as an employer.


For wage earners, there are diff erences across all four groups (fi gure 3.14).
Participation rates for women rise with smaller literacy gaps and with legal gaps,
as do those for men. For both women and men, there is not a further increase
associated with smaller gaps on both dimensions. However, looking at the
proportional changes in fi gure 3.14b, the gender gaps decline as the diff erences
in literacy and legal rights close (that is, moving to the right in the fi gures).


Gaps in Women’s Participation across Employment Categories
Female shares in self-employment are signifi cantly larger than female shares
of employers in all four country categories, particularly where both rights
and literacy are weaker (fi gure 3.15). Higher literacy rates close the gap
between women who are self-employed and those who are employers, as
do stronger women’s legal rights. Th e eff ect of stronger legal rights is particu-
larly noticeable where literacy is weaker.


For employers and wage earners, what is striking is that there is no average
participation gap for women in countries with stronger literacy, though
the extent of legal protection plays a signifi cant role where larger literacy gaps
exist (fi gure 3.16). Where gaps in rights are larger, women’s share in wage earning
is higher. Where gaps in rights are smaller, women’s share as employers is higher.


So, legal rights are important not only in the trade-off s between being
self-employed and being an employer, but also in the trade-off s between being
an employer and being a wage earner.


To sum up, larger gender gaps in adult literacy are generally associated with
women’s greater involvement in self-employment, while greater legal protection
is more associated with women having more opportunity to become employers.
Th ese results are consistent with self-employment relying mostly on the skills
and human capital of the entrepreneur; they are also consistent with employers’
need to sign contracts and have better control over assets, such that legal and
economic rights are important.


Th ese results rely on cross-country variation. Evaluations of legal reforms
within a country also demonstrate the importance of stronger legal and
economic rights on economic activities that are pursued. Box 3.1 discusses the
case of Ethiopia. Chapter 7 provides additional discussion of these issues.




84 ENTERPRISING WOMEN


Weaker
0


1


2


3


4


5


6


rights


Stronger


rights


Weaker


rights


Stronger


rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
o


f
w


om
en


(m
en


)


a. Employer


Women Men


–300


–150


–100


–50


0


Weaker
rights


Stronger
rights


Weaker
rights


Stronger
rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
g


ap
o


f w
om


en


ov
er


m
en


b. Gender gap among employers


Figure 3.13 Gender Gaps among Employers Are Sensitive to Gaps in Women’s Economic
and Legal Rights


Sources: Women’s Legal and Economic Empowerment Database; World Bank, World Development Indicators
database, http://data.worldbank.org/indicator.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 85


0


10


20


30


40


50


60


70


80


Weaker rights Stronger rights Weaker rights Stronger rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
o


f
w


om
en


(m
en


)


a. Wage earners


Women Men


Figure 3.14 More Women Become Wage Earners Where Gaps in Literacy and Legal Rights
Are Smaller


–100


–90


–80


–70


–60


–50


–40


–30


–20


–10


0


Weaker
rights


Stronger
rights


Weaker
rights


Stronger
rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
g


ap
o


f w
om


en
o


ve
r


m
en


b. Gender gap among wage earners


Sources: Women’s Legal and Economic Empowerment Database; World Bank, World Development Indicators
database, http://data.worldbank.org/indicator.




86 ENTERPRISING WOMEN


Figure 3.15 Stronger Literacy Closes the Employer–Self-Employed Participation Gap


0


5


10


15


20


25


30


Weaker rights Stronger rights Weaker rights Stronger rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
p


oi
nt


g
ap


fo
r


se
lf-


em
pl


oy
ed


v
er


su
s


em
pl


oy
er


Sources: Women’s Legal and Economic Empowerment Database; World Bank, World Development Indicators
database, http://data.worldbank.org/indicator.


Sources: Women’s Legal and Economic Empowerment Database; World Bank, World Development Indicators
database, http://data.worldbank.org/indicator.


Figure 3.16 Stronger Literacy Shows Virtually No Employer–Wage Earner Participation Gap
for Women


–1


–5


–4


–3


–2


0


1


2


3


4


5


Weaker rights Stronger rights Weaker rights Stronger rights


Weak literacy Strong literacy


Pe
rc


en
ta


ge
p


oi
nt


g
ap


fo
r


se
lf-


em
pl


oy
ed



ve


rs
us


e
m


pl
oy


er




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 87


Notes
1. Klapper and Parker (2010) provide a review of the broader literature on women’s


entrepreneurship and the business environment, but do not focus on Sub-Saharan
Africa per se. Ayyagari, Beck, and Demirgüç-Kunt (2007) provide data and analysis
of the share of fi rms around the world that are considered small and medium enter-
prises, but do not have information on the gender of the entrepreneur.


2. As in chapter 1, the fi gures do not include the shares of unemployed—shares that are
very low in Sub-Saharan Africa.


3. Other authors also analyze how patterns of entrepreneurship vary across countries by
income, but not disaggregated by gender (Bartlesman, Haltiwanger, and Scarpetta,
forthcoming; Klapper, Amit, and Guillén 2008; Lerner 2007; Tybout 2000.)


4. M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s
Legal and Economic Empowerment Database. Th e database was developed for the
companion volume (Hallward-Driemeier and Hasan 2012) and is further elaborated
in chapter 7.


5. Access to technology could be a third dimension, but given the diffi culty in
measuring it, and the additional challenge of having an objective way to quantify
gender diff erences in access to technology, we do not include it.


6. An alternative to using current literacy rates is to look at education completion rates
of an earlier generation. Indeed, girls’ completion of primary education in 1980 is
very closely correlated with current literacy. However, as data on historical rates of
girls’ completion of primary education are available only for a few countries, we use
the literacy rates here.


7. Note, however, that we could not fi nd all the relevant family codes or land statutes
for the Central African Republic, Chad, Equatorial Guinea, and São Tomé and
Príncipe and so did not categorize them.


BOX 3 .1


Strengthening Women’s Property Rights Affects
the Opportunities Women Pursue
Ethiopia changed its family law in 2000, raising the minimum age of marriage for women,
removing the ability of the husband to deny permission for the wife to work outside
the home, and requiring both spouses’ consent in the administration of marital  property.
This reform, initially rolled out in selected regions and cities, now applies across the country.


Using two nationally representative household surveys, one in 2000 just prior to
the reform and one fi ve years later, we fi nd a substantial shift in women’s economic
activities. In particular, women’s relative participation in occupations that require work
outside the home, full-time work, and higher skills rose more where the reform had
been enacted (controlling for time and location effects).


Source: Hallward-Driemeier and Gajigo 2011.




88 ENTERPRISING WOMEN


8. One exception is Kenya, whose new constitution came into force in August 2010.
For categorizing the current situation, Kenya’s new constitution provides the basis
of the indicators. But in the analysis, the older constitution is used because it was in
eff ect when the household and enterprise data were collected.


9. For more-detailed information on its construction, see Hallward-Driemeier and
Hasan (2012). As a follow-up to the Women–LEED–Africa project, eff orts are under
way to build the database back over time to off er historical coverage of how countries
have reformed laws aff ecting women’s economic rights.


10. Th e one household-head provision we did not include was the right for the husband
to choose the location of the marital domicile. If this involved moving, it could
separate the wife from her business or client base. For three countries this is the only
source of gender gaps in the categories we considered: Benin, Burkina Faso, and
Senegal. Th e fi rst two have made considerable progress in recent years, reforming
their family codes to greatly strengthen women’s rights. If this provision was the
only source of gaps, the countries were not placed in the “weaker women’s property
rights” group.


References
Acemoglu, D., and S. Johnson. 2005. “Unbundling Institutions.” Journal of Political


Economy 113 (5): 949–95.
Acemoglu, D., S. Johnson, and J. Robinson. 2002. “Reversal of Fortune: Geography and


Institutions in the Making of the Modern World Income Distribution.” Quarterly
Journal of Economics 117: 1231–94.


Aterido, R., and M. Hallward-Driemeier. 2010. “Th e Impact of the Investment Climate
on Employment Growth: Does Sub-Saharan Africa Mirror Other Low-Income
Regions?” Policy Research Working Paper 5218, World Bank, Washington, DC.


Ayyagari, M., T. Beck, and A. Demirgüç-Kunt. 2007. “Small and Medium Enterprises
across the Globe.” Small Business Economics 29: 415–34.


Bartlesman, E., J. Haltiwanger, and S. Scarpetta. Forthcoming. “Cross Country Diff er-
ences in Productivity: Th e Role of Allocative Effi ciency.” American Economic Review.


Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. Gunning, A. Oduro,
R.  Oostendorp, C. Pattillo, M. Söderbom, F. Teal, and A. Zeufack. 2003. “Credit Constraints
in Manufacturing Enterprises in Africa.” Journal of African Economies 12 (1): 104–25.


Bigsten, A., and M. Söderbom. 2006. “What Have We Learned from a Decade of Manu-
facturing Enterprise Surveys in Africa?” World Bank Research Observer 21 (2): 241–65.


Dollar, D., M. Hallward-Driemeier, and T. Mengistae. 2005. “Investment Climate and
Firm Performance in Developing Economies.” Economic Development and Cultural
Change 54 (1): 1–32.


Hall, R., and C. Jones. 1999. “Why Do Some Countries Produce So Much More Output
per Worker Th an Others?” Quarterly Journal of Economics 114: 83–116.


Hallward-Driemeier, M., and O. Gajigo. 2011. “Strengthening Economic Rights and
Women’s Occupational Choice: Th e Impact of Reforming Ethiopia’s Family Law.”
Paper presented at Centre for the Study of African Economics annual conference,
St. Catherine’s College, Oxford, March 20–22.




EFFECT OF COUNTRY PATTERNS IN INCOME, HUMAN CAPITAL, AND ASSETS 89


Hallward-Driemeier, M., and T. Hasan. 2012. Empowering Women: Legal Rights and
Economic Opportunities in Africa. Washington, DC: World Bank and Agence Française
de Développement.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Hsieh, C.-T., and P. J. Klenow. 2009. “Misallocation and Manufacturing TFP in China
and India.” Quarterly Journal of Economics 124 (4): 1403–46.


Klapper, L., R. Amit, and M. F. Guillén. 2008. “Entrepreneurship and Firm Formation
across Countries.” Working paper, World Bank, Washington, DC.


Klapper, L., and S. Parker. 2010. “Gender and the Business Environment for New Firm
Creation.” World Bank Research Observer 26 (2): 237–57.


Lerner, J., ed. 2007. International Diff erences in Entrepreneurship. Chicago: University of
Chicago Press.


Rodrik, D., A. Subramanian, and F. Trebbi. 2004. “Institutions Rule: Th e Primacy of
Institutions Over Geography and Integration in Economic Development.” Journal of
Economic Growth 9 (2): 131–65.


Tybout, J. R. 2000. “Manufacturing Firms in Developing Countries: How Well Do Th ey
Do, and Why?” Journal of Economic Literature 28 (March): 11–44.


World Bank. 2004. World Development Report 2005: A Better Investment Climate for
Everyone. Washington, DC: World Bank.






91


Chapter 4


Sorting into Entrepreneurial
Activities: Individual Patterns


Th e earlier chapters emphasize the gender patterns across employment catego-
ries and types of enterprise. A key fi nding here is that enterprise characteristics
oft en swamp gender diff erences within similar types of activities; formal fi rms
share more characteristics, regardless of the gender of the entrepreneur, than
do formal and informal women’s enterprises. Th e same is largely true of large
and small enterprises, and high- and low-value-added lines of business. So the
question becomes, what accounts for individuals’ choice of enterprise?


Chapter 3 points to some broad features of the economy that can matter,
including average income and (to a greater degree) gender gaps in access
to education and property rights. Th is chapter examines diff erences among
entrepreneurs themselves, focusing on individual characteristics and how
they aff ect the choice of activity (box 4.1). Studies that look at women entre-
preneurs have raised several issues as being important, from the division of
household responsibilities, to diff erences in risk taking, to diff erences in “entre-
preneurial spirit,” to diff erences in ability to navigate the business environ-
ment; for reviews of the literature see Klapper and Parker (2010); Mammen
and Paxon 2000; Minniti (2009); and Parker (2004). Th e emphasis here is on
more observable characteristics of age, education, marital status, prior work
experience, and family background. Measures of motivations and attitudes
are included, but are not found to have much explanatory power, particularly
once the observable characteristics are taken into account. Th is fi nding is
also consistent with those of other authors, such as Blanchfl ower and Oswald
(1998), who emphasize that access to capital rather than personality is the best
predictor of whether an individual will become an entrepreneur, or Djankov
and others (2005 and 2006), who emphasize the importance of a tradition of
entrepreneurship within the family.


Deciding whether to be an entrepreneur and what type of business to run is
a multistage process, discussed here as consisting of four choices: participating
in the nonagricultural labor force, becoming an entrepreneur, operating in the
formal or informal sector, and choosing the line of business.




92 ENTERPRISING WOMEN


In examining these choices, this chapter analyzes individuals of working
age (16–60 years) who are not attending school. Th e analysis mostly considers
individuals making autonomous decisions, but also allows that some deci-
sions are made jointly with the spouse—and that decisions may not represent a
choice if there are no alternatives available. Th e analysis requires comparisons
with people who are not in business (unlike many of the comparisons in the
earlier chapters). Th us it looks at household surveys from 39 countries in Sub-
Saharan Africa, comparing the characteristics of those who did and did not
become entrepreneurs. Th ere is room, though, for strengthening data collection
(box 4.2).


Education is a key determinant in these choices, with smaller roles played
by prior work experience, marital status, motivation, age, and relevant busi-
ness skills. More specifi cally, education, prior experience, and age help predict
whether an individual joins the formal or informal sector and the size of the
enterprise. Th is holds for women and men. But while the eff ect of education
on entrepreneurial performance is almost always positive, its eff ect on selec-
tion into entrepreneurship is more ambiguous (given the high variability in
returns not only within the entrepreneurial sector but also within competing
occupations in the wage sector).


Strikingly, characteristics of female and male entrepreneurs within a sector
are much more similar than characteristics of female or male entrepreneurs
across sectors. Th us many of the observed gender gaps in entrepreneurship
stem from deeper gender gaps in education and access to alternative wage
employment.


BOX 4.1


Choice of Activity—Externally Constrained or Internally
Preferred?
One of the central debates in the sociological literature on women’s entrepreneurship
is whether different outcomes between men and women refl ect different constraints
or different preferences. Unfortunately, no defi nitive answer has appeared.


Legal restrictions on women’s participation in certain activities are an obvious con-
straint on options. But different responsibilities outside work (for example, care within
the home) or differences in preferences may also reduce options, as may cultural norms.


In this chapter, to see how much “choice” women actually have, we draw on
surveys that ask entrepreneurs what motivated them to become an entrepreneur and
why they chose the activity they did.




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 93


Prior work experience is important, particularly with respect to the
performance of the enterprise. Indeed, entrepreneurship-related experience
can be a bigger determinant of productivity than nonspecialized formal edu-
cation. Th e sector (formal or informal) in which the prior work experience
occurred matters—most individuals open their business in the same sector they
had worked in before. Th is fi nding has a gender dimension: because women are
more likely to work in the informal sector, they are more likely to run informal
enterprises if they become entrepreneurs.


Marital status, more for women than men, determines legal standing,
property rights, and ability to engage in business (as discussed further in
chapter 7). Th e time demands for men and women at home can also vary, lead-
ing to diff erent elasticities of labor supply. Th e eff ect of marital status is greatest
for women’s decision to participate in the labor force and for their decision to
operate in the informal or formal sector.


In a few of the reasons for going into entrepreneurship cited by survey
respondents there are discernible gender and sector diff erences. Among those
who cite the possession of business skills as an important motivation for becom-
ing an entrepreneur, the proportions of male and formal entrepreneurs are
higher than those of female and informal entrepreneurs. A similar pattern is
evident for those who profess to have knowledge about their particular line of
business. Th is diff erence likely refl ects the higher average human capital of male
entrepreneurs, who also dominate in the formal sector.


BOX 4.2


Strengthening Data Collection
This chapter’s analysis could be improved in two ways, but both would require more
data.


The fi rst would be to track individuals over time. Such panel data sets allow use
of more-sophisticated estimation methods and can take into account how changing
conditions affect decisions. Unfortunately, the household surveys are repeat cross-
section surveys. National statistical offi ces should be encouraged to collect more
panel data.


The second would be to collect more information on types of constraints that might
affect decisions. More information on access to assets, control of income, and time
use, for example, would enable us to examine how decisions are made in the house-
hold and in turn how this process affects outcomes. A few countries collect data on
these variables, but the data are rarely comparable across countries.




94 ENTERPRISING WOMEN


Choice 1: Participating in the Nonagricultural Labor Force


Five individual or household characteristics weigh heavily in the initial decision
to join the nonagricultural labor force:


• Age. Th e probability of participating increases with age, if at a decreasing
rate.1


• Education. Th ose with more education are more likely to join. Th e eff ect is
much stronger for women than men.


• Head-of-household status. Heads of household are more likely to participate,
particularly women.


• Marital status. Married women are much less likely to participate than either
married men or unmarried women.


• Urban-rural location. Living in an urban area increases the chances of
participating. Th e eff ect is larger for men than women.


To explore some of the cross-country variation in the eff ects of individual char-
acteristics on a person’s decision to participate, we now allow some of the eff ects
of certain characteristics to matter more in some environments than others. Th e
results thus combine diff erences within and across countries.


We focus on the eff ects of gross domestic product (GDP) per capita, higher
education, property rights, and governance. We focus on the Organisation
for Economic Co-operation and Development’s Gender-related Development
Index, with its relative weight on human capital, and the Worldwide Governance
Indicators (WGI) project’s overall indexes as our measures for social inclusion
and governance quality, respectively. Given that the literature highlights the
importance of ownership rights and corruption for economic outcomes, we also
present results using the Social Institutions and Gender Index subindicator on
ownership rights and the WGI indicator on control of corruption (for more on
the indexes see appendix B).2


With respect to the eff ects of GDP per capita, most of the eff ects of workers’
characteristics on participation in the nonagricultural labor force tend to be
smaller in absolute terms in countries with higher GDP per capita. Specifi cally,
being older, more educated, and married have a smaller impact on the decision
to participate in the nonagricultural labor force in more-developed economies.


Greater female education and property rights and the quality of governance
also play important roles. Th ey are associated with higher rates of women’s
participation in the nonagricultural labor force. In addition to this level eff ect,
these country characteristics also aff ect the relative importance of an individu-
al’s education and marital status. Th e eff ect of an individual’s level of education
on participation in the nonagricultural labor force is larger in those countries
with smaller gender gaps in education and property rights and where there is




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 95


better governance. Women married to a working spouse are also more likely
to participate in the nonagricultural sector in environments with larger gender
gaps and stronger governance.


Choice 2: Becoming an Entrepreneur
(Self-Employed or Employer)


Within the nonagricultural labor force, individuals have various options
(boxes 4.3 and 4.4): entrepreneurship (self-employment or being an employer),
wage work, unpaid work, and (perhaps less of a free choice) unemployment.
Some of these types of employment are not always available; they may not be
“options” or “choices” in many cases (Banerjee and Newman 1993; Iyer and
Schoar 2010). At issue here are the prevalence of the categories and the types
of individuals most likely to be working in each one. Again, our population of
interest consists of those ages 16–60 who are not currently attending school. Th e
two characteristics most strongly associated with choosing entrepreneurship are
education and marital status.


Education
Earlier studies have found that education has a signifi cant eff ect both on the
decision to become an entrepreneur and on the level of entrepreneurial pro-
ductivity once an entrepreneur has started a business (Blau 1985; Parker and
van Praag 2006; Van der Sluis, van Praag, and Vijverberg 2008). Th e latter eff ect
is almost invariably positive. Th e former eff ect is more ambiguous, given the
high variability in returns not only within entrepreneurship but also within
competing occupations in wage work. More-educated workers are more likely
to take wage jobs (usually in urban areas) than to become an entrepreneur, and
entrepreneurship is likely to be more attractive where the main alternative liveli-
hood is farming. Th ese trade-off s vary by level of income, with the gap between
the attractiveness of wage earning relative to entrepreneurship being highest in
Sub-Saharan Africa’s low-income countries.


Th ree patterns emerge in most countries for education among male and
female entrepreneurs. First, men tend to be more educated than women.
Second, employers are more educated than the self-employed. Th ird, the second
pattern is particularly true within gender (that is, male employers are more
educated than male self-employed, and women employers are more educated
than female self-employed), but not between genders. In some countries, female
employers on average have less education than self-employed men; these are
countries with more pronounced gender gaps in education and adult literacy.
Self-employed women are almost always the least educated (fi gure 4.1).




96 ENTERPRISING WOMEN


Source: Gajigo and Hallward-Driemeier 2010; see also Aterido and Hallward-Driemeier 2011.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


Figure B4.3.1 The Reason for Starting a Business Varies Little by Gender or Formality


Percentage of entrepreneurs citing
factor as reason for starting business


Loss of job as employee


Other household shock


Family tradition


Work flexibility


New/additional income


Possession of business skills


Knowledge of this business


Desire for stable income


Desire to be own boss


Market opportunity


High chance of profit


Female Male Informal Formal


0 20 40 60 80 100


Absence of alternative jobs


BOX 4.3


Motivation: Necessity or Opportunity?
Does the motivation of the entrepreneur matter—beyond the gender patterns across
types of activities seen in enterprises’ external characteristics? Are those individuals
who claim that they are pursuing an opportunity different from those who claim to be
default or necessity entrepreneurs?


The gender module of existing formal enterprises and the survey of new
entrepreneurs (see box  1.3) asked questions to capture the motivation for becom-
ing an entrepreneur. Some respondents were entrepreneurs who had been “pulled”
into starting a business to take advantage of an opportunity, while others had been
“pushed” into it out of necessity, perhaps for lack of alternative wage jobs, loss of a
job, or household shocks (such as illness, death, or divorce). These two broad lines have
long been recognized in the enterprise literature.


The survey data fi nd job loss, household shock, family traditions, or unavailability
of attractive wage jobs signifi cantly less common than other reasons (fi gure B4.3.1).




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 97


This is unlike fi ndings in the literature, which cites household shocks as a frequent
reason for becoming an entrepreneur. It may be that the entrepreneurs in this
sample— completely urban—are less likely to go into entrepreneurship out of necessity
than rural entrepreneurs. The sample also has few household-based enterprises, again
likely affecting the share of reported necessity entrepreneurs. Of less interest here is
the comparison of necessity and opportunity entrepreneurs per se; of more interest is
whether there are any signifi cant gender differences in the reasons given for starting
a business.


When one divides answers depending on whether necessity or opportunity is most
important, the clearest pattern is that all four groups of respondents tend to track each
other relatively well. Motivation does not differ dramatically for women versus men, or
for those in the informal versus the formal sector.


No tight relationships are evident between education and motivation, although
those who had no better alternative jobs, had lost their job, were in business to follow
family tradition, or had felt a shock were less likely to have high education (university
and graduate school). Similarly, differences across motivations for starting a business
are not large for work experience.


Using the above motivations, the analysis shows that around 60 percent of new
entrepreneurs in the four countries surveyed (Côte d’Ivoire, Kenya, Nigeria, and
Senegal) are necessity entrepreneurs (fi gure  B4.3.2). The informal sector shows
no gender difference, but the formal sector has more female than male necessity
entrepreneurs.


—Continued


0


10


20


30


40


50


60


70


Male Female Male Female
Formal Informal


Pe
rc


en
ta


ge
o


f n
ec


es
si


ty


en
tr


ep
re


ne
ur


s


Figure B4.3.2 Gender Plays Some Role among Necessity Entrepreneurs in the Formal Sector


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.




98 ENTERPRISING WOMEN


Th e probability of being an entrepreneur has an inverted-U relationship
with education; individuals are more likely to become an entrepreneur as their
education increases, but at a certain level of education, the probability starts to
decline. For age, the probability is increasing and concave: it rises with age, but
at a decreasing rate.


These patterns show some variation by income. At higher incomes,
more-educated women are more likely to become entrepreneurs, particularly
employers. Th e marginal eff ect of additional education in encouraging women’s
entrepreneurship is also larger in countries that have lower gender gaps in
property rights and stronger governance.


Marital status
Women could also face constraints arising from their marital status. Women’s
marital status, more so than men’s, determines their legal standing, property
rights, and ability to engage in business activity (discussed further in
chapter 7). For example, a married woman could be more restricted than a
single woman in her ability to be an entrepreneur, because, under the law,
she may be unable to access or control assets, or make autonomous business


Regression results (probit) for the determinants of necessity entrepreneurs show
that on average, females are more likely to be necessity entrepreneurs. However, once
we control for previous employment background, the signifi cance level for this result
disappears. Among previous employment experiences, having been a worker in a
nonenterprise organization reduces the likelihood of being a necessity entrepreneur
for men but increases it for women. By marital status, married women are signifi -
cantly less likely to become a necessity entrepreneur. Educational level is a strong pre-
dictor of opportunity entrepreneurship, especially at the highest levels (university and
graduate school). More–highly educated individuals would have the opportunity to
engage in highly remunerative and less risky wage employment. Other characteristics
that reduce the likelihood of being a necessity entrepreneur are having a background
as an employee in a nonbusiness entity and being fi nancially literate. Older entrepre-
neurs are more likely to be necessity entrepreneurs.


Note: Because of the gender division of labor, even female entrepreneurs are responsible for most
household work. Thus for a woman who also does signifi cant household work, entrepreneurship is
preferable to wage work, since it does not require such regular working hours. In analyzing job growth
among Guatemalan entrepreneurs, Kevane and Wydick (2001) found that young female entrepreneurs
are especially constrained in generating employment compared to young males and older women, and
they attribute this gender difference to the higher opportunity time cost for younger women during their
childbearing years.


BOX 4.3 con t i nued




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 99


BOX 4.4


Entrepreneurship: An Opportunity That Varies with Income
and Education
Among entrepreneurs the average education of employers is higher than that of the
self-employed, though to a striking degree the gap closes as national income rises.
Wage earners are more educated than the self-employed in almost all countries—that
is, the education gap on the y-axis is almost always positive (fi gure B4.4.1 shows this
for women; the pattern is similar for men). The gap in education for wage earners
and the self-employed is greatest in low-income countries and where self-employment
is higher.


In low-income Sub-Saharan African countries, wage earners are more educated
than employers—thus in fi gure B4.4.2, most of the diamonds are in the upper right
quadrant. In higher-income countries, many employers are more educated than
wage earners—that is, the squares are primarily in the bottom left quadrant. The gap


Figure B4.4.1 Gaps in Education for Female Wage Earners versus Female Self-Employed Rise
as the Share of Women in Self-Employment Rises


Source: Based on national household and labor force surveys for 101 low- and middle-income economies, most
recent years (2000–10).


–2


0


2


4


6


8


10


10 20 30 40 50 60 70 80 90 100


G
ap


in
w


om
en


’s
e


du
ca


ti
on


,
w


ag
e


ea
rn


er
v


s.
s


el
f-


em
pl


oy
ed


(y
ea


rs
)


Percentage of women in self-employment


Higher-income countries Lower-income countries


—Continued




100 ENTERPRISING WOMEN


decisions. Among self-employed women, on average, more than 60 percent
are married, 15  percent are single, and 10 percent are widowed or divorced.
Female employers are twice as likely to be divorced or widowed as women
overall.3


Married women are 55 percent of the female population, and they make
up 50 percent of wage earners and more than 60  percent of female self-
employed and employers.4 However, for divorced women, the distribution
across activities is more dramatic. While 5 percent of women are divorced,
they make up 10 percent, or twice as large a share, of female employers,


Figure B4.4.2 Gap in Education for Wage Earners versus Employers Is Higher for Women
Than Men


Source: Based on national household and labor force surveys for 101 low- and middle-income economies, most
recent years (2000–10).


A
ve


ra
ge


g
ap


in
w


om
en


’s
e


du
ca


ti
on


,
w


ag
e


ea
rn


er
v


s.
e


m
pl


oy
er


(y
ea


rs
)


Average gap in men’s education, wage earner vs. employer (years)
–6


–4


–2


2


4


6


8


–4 –3 –2 –1 0 1 2 3 4 5


Higher-income countriesLower-income countries


in education for female wage earners and employers is greater than that for male
wage earners and employers in low-income countries (the diamonds are above the
45 degree line).


BOX 4.4 con t i nued




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 101


self-employed, and wage earners. Some of the jump is clearly due to divorced
women’s increased need to earn income (since they generally no longer have
the income contributions of their spouse to their household). However, the
variation in the extent of concentration of divorced versus married women in
entrepreneurship varies by certain country characteristics, in particular the
extent of gaps in legal capacity and property rights for married and nonmar-
ried women. Figure 4.2 shows one of the more extreme examples: Swaziland.
It is among the most restrictive countries where rights for married women
are concerned.


Switching the perspective to look within each marital status category at
the shares of entrepreneurs, we see that rates of self-employment and rates
of being an employer are highest among divorced women. It is also well
established that marital status has a signifi cant eff ect in the labor market:
one of the most consistent fi ndings is that married men have higher returns
(Goldin 1990). Another important gender diff erence is that female divorced
and widowed entrepreneurs are more common than male, especially in infor-
mal activities, suggesting that they face much higher barriers to entry into the
formal sector than other categories of marital status (Gajigo and Hallward-
Driemeier 2010).


Figure 4.1 Self-Employed Women Are the Least Educated among Male and Female
Entrepreneurs


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Data are from enterprise modules of household surveys in selected countries, various years (2000–10).


0


2


4


6


A
ve


ra
ge


y
ea


rs
o


f e
du


ca
ti


on


8


10


12


Bu
run


di


Bu
rki


na
Fa


so



te


d’I
vo


ire


Ca
me


roo
n


Co
mo


ros


Gh
an


a


Ga
mb


ia,
Th


e
Ke


ny
a


Ma
law


i
Ni


ge
r


Ni
ge


ria


Rw
an


da


Female self-employed Male self-employed


Female employer Male employer




102 ENTERPRISING WOMEN


The occupation of the spouse also shows a pattern. Those with a
wage- earning spouse are less likely to be entrepreneurs. Th ose married to an
entrepreneur are more likely to be entrepreneurs themselves, which could be
because many household enterprises engage multiple members of the same
family. Th ese two eff ects are particularly large for women relative to men,
consistent with women being more likely to help operate their husband’s enter-
prises than vice versa.


Choice 3: Formal or Informal Sector


A strong predictor of an enterprise’s productivity and size is whether the enter-
prise is registered or is operating in the informal sector (ILO 2002). Th is section
looks in more detail at individual characteristics and how they correlate with
choice of sector. It should be kept in mind that working in the informal sector
may be seen as more desirable for some entrepreneurs, particularly if fl exible
hours or the ability to work close to home are valued (Heintz 2012; Maloney
2004). At the same time, for many, the option to operate in the formal sector
may not be feasible given the resources available.


Education
Patterns of education are far more similar for women and men within the
informal (or formal) sector than they are between the sectors, based on data
from surveys of new entrepreneurs in Côte d’Ivoire, Kenya, Nigeria, and
Senegal (fi gure  4.3). Among informal entrepreneurs, only 17–18  percent


Figure 4.2 Where Married Women Have Fewer Economic Rights, Employers Are More Likely
to Be Divorcees or Widows: The Case of Swaziland


Source: Gajigo and Hallward-Driemeier 2010.


0


5


10


15


20


25


All
women


Single
women


Married
women


Divorced
women


Widows


Pe
rc


en
ta


ge
o


f w
om


en
w


ho
a


re


em
pl


oy
er


s
(b


y
m


ar
it


al
s


ta
tu


s)




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 103


have some postsecondary education, compared with more than 40 percent
of  formal entrepreneurs (almost 50  percent of women and 40  percent of
men).


Still, some gender diff erences emerge, more so in the formal sector.
Female entrepreneurs are more likely to have completed or to have had some
university education, and men are more likely to have completed vocational
or secondary school. Th is fi nding would indicate that women who have
made it into the formal sector are on average more educated than their male
counterparts.


Age
Enterprise modules in household surveys indicate that the average age of entre-
preneurs is 35 for the self-employed and 37 for employers. Employers also tend
to be older than wage employees. Gender diff erences within a sector are smaller
than the diff erences across sectors.


Age is also a signifi cant predictor of productivity, using revenue per worker
as the metric. Th is diff erence is robust to controlling for education, sector
( formal sector), country, and industry dummies. Th e eff ect does not increase
monotonically—the positive eff ect does not persist past age 30. Further, there is
no gender gradient to the eff ect of age on productivity when the above variables
are controlled.


Figure 4.3 Education Varies More by Sector Formality Than by Gender


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


20


40


60


80


100


Male Female Male Female
Formal


Pe
rc


en
t


Informal


Degree Some university education Vocational training


Primary school No schoolingSecondary school




104 ENTERPRISING WOMEN


Th e fi nding that age is a signifi cant predictor of productivity is not new.
While numerous studies have shown negative association between age and pro-
ductivity among workers (including Aubert, Cavoli, and Rogers 2006; Behagel
and Greenan 2005; Haltiwanger, Lane, and Spletzer 1999), some have shown
that older managers (a category more comparable to the entrepreneurs in our
sample) do better on some practical management skills than younger workers
(Colonia-Willner 1998).


Th e age of the entrepreneur could be a proxy for experience. Th e data from
the surveys of new entrepreneurs allow us to explore this possibility in more
detail because we know both the years of prior experience and the sector in
which the experience was gained. Among new entrepreneurs from Côte
d’Ivoire, Kenya, Nigeria, and Senegal, men in the formal sector are distinctly
older than men in the informal sector and are older than women in both the
formal and informal sectors (fi gure 4.4). And these older entrepreneurs who are
starting new businesses tend to show better performance. However, age itself is
not the reason: older individuals who start a business tend to come from back-
grounds that allowed them to accumulate more experience. Th e selection eff ect
is at work: former employees who saw an opportunity and left their job to start
a business have a higher likelihood of running a productive fi rm than those who


Figure 4.4 Women Entrepreneurs Tend to Be Younger Than Their Male Colleagues—
Particularly in the Formal Sector


Source: Gajigo and Hallward-Driemeier 2010.
Note: Kernel = Epanechnikov; bandwidth = 2.0347. Data are for newly established enterprises in Côte d’Ivoire,
Kenya, Nigeria, and Senegal, 2010.


0.06


0.04


0.02


0


20 40 60 80 100


D
en


si
ty


Age in years


Male, formal sectorFemale, formal sector


Female, informal sector Male, informal sector




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 105


started a business many years earlier (for opportunity or necessity) and are still
in business years later. And many of the older entrepreneurs starting businesses
came from the public sector or formal private sector.


Prior Labor Market Experience
Beyond education, experience is another important human capital variable in
the choice of formal or informal sector work. (Experience matters for enterprise
size, too; see box 4.5.) Gender is likely to aff ect work experience, since the time
demand for men and women at home can vary, leading to diff erent elasticities of


BOX 4.5


Scale of Enterprise
The measures of human capital most strongly correlated with business size are the
education and the experience of the senior manager. The more-educated and more-
experienced managers are more likely to be in the formal sector and run a large business.
The patterns by education are stronger than those by experience ( fi gure B4.5.1). While
there is little difference in education between women and men in the informal sector
and in smaller formal fi rms, women who run fi rms with 50 or more employees are
progressively more educated than their male counterparts.


0


20


40


60


80


100


Pe
rc


en
ta


ge
o


f m
an


ag
er


s
w


it
h


sp
ec


ifi
ed


e
du


ca
ti


on


1–10 employees


Male Female


a. Managers’ Education and Firm Size


11–50 employees


Male Female


51–200 employees


Male Female


+200 employees


Male Female


Less than secondary educationSecondary education


Vocational trainingUniversity education


Figure B4.5.1 Managers’ Education Is More Strongly Correlated with Business Size Than
Managers’ Experience


—Continued




106 ENTERPRISING WOMEN


labor supply. Consequently, both the duration and type of experience may diff er
by gender (Dessing 2002; Grossbard-Shechtman and Neuman 1998).


Roles within the family can also aff ect the extent to which a family
background of entrepreneurship helps predict whether individuals become
entrepreneurs. In our samples, having a father who was an entrepreneur was a
strong predictor, particularly for men. Men were more likely to have worked in
the enterprise, reinforcing family and prior labor experience in entrepreneur-
ship (Aterido and Hallward-Driemeier 2011).


Heterogeneity in prior work experience is likely to be important in infl uencing
the choice of sector. Two entrepreneurs may each have 10 years of work experi-
ence, one in the formal sector, one in the informal. Th ese diff erent backgrounds
have diff erent eff ects on the probability of entrepreneurship and thus on the
relative representation of diff erent backgrounds among current entrepreneurs.


Th e surveys of new entrepreneurs show that the owners of formal and
informal enterprises are heavily drawn from former employees of fi rms within
the same sector. More than half of all formal entrepreneurs (57 percent) were
wage-earning, formal enterprise workers before starting their current enter-
prises. Similarly, the most common former employment type among informal


BOX 4.5 con t i nued


Source: Enterprise Surveys, World Bank, various years (2006–10), http://www.enterprisesurveys.org.
Note: Percentages are means for each group.


0


20


40


60


80


100


Pe
rc


en
ta


ge
o


f m
an


ag
er


s
w


it
h


sp
ec


ifi
ed


e
xp


er
ie


nc
e


1–10 employees 11–50 employees


Male Female Male Female


Less than 1 year1–5 years


6–15 yearsMore than 15 years


51–200 employees


Male Female


+200 employees


Male Female


b. Managers’ Experience and Firm Size


Figure B4.5.1 (continued)




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 107


entrepreneurs (29 percent) is as paid workers in other informal fi rms. Th e vast
majority of individuals do not move between sectors.


Th us, like education, the background of the entrepreneur is a strong
predictor of whether the enterprise will be formal or informal, and, again, the
diff erences between men and women within each sector are much smaller than
the diff erences between the sectors (fi gure 4.5).


Despite the greater degree of diff erence by sector, some gender diff erence in
background is apparent, especially in the informal sector (see box 4.6). Women
there are much more likely than informal sector males to have been looking
for a job in the months before they became entrepreneurs (29  percent versus
16 percent). And the 50 percent share of men in the informal sector who used
to be paid employees (formal and informal, signifi cantly exceeds the 39 percent
of women in the informal sector who used to be paid employees.


Marital Status
Signifi cantly independent of gender and sector is the predominance of married
people among the ranks of new entrepreneurs surveyed in the four countries


Figure 4.5 Differences in Prior Experience Are Greater between the Sectors Than between
Genders within Sectors


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


20


40


60


80


100


Male Female Male Female


Formal Informal


Not in labor force Unemployed


Employee in a
nonbusiness


Paid employee in an
informal firm


Paid employee in a
formal firm


Unpaid employee


Pe
rc


en
ta


ge
h


av
in


g
sp


ec
ifi


ed


pr
io


r
ex


pe
ri


en
ce




108 ENTERPRISING WOMEN


BOX 4.6


Relationship between Education and Work Experience
The type of experience that is most correlated with work in the formal sector is previous
working experience with a formal sector fi rm (fi gure B4.6.1).


Entrepreneurs with this background are among the most educated group. About
42 percent of the entrepreneurs in this group have at least some university education—
a proportion superseded only by individuals who used to be employees in nonbusiness
areas (for example, teachers and nurses).


At the other end of the spectrum, entrepreneurs who used to work as paid
employees for informal fi rms have educational attainment very similar to that of unpaid
workers in general.


Even though previous work experience in the formal sector is a strong predictor of
formal sector entrepreneurship, a nontrivial percentage of formal entrepreneurs used
to work in the informal sector. The entrepreneurs who made this transition tend to be
divorced and men, and to have larger start-up capital. They also depend heavily on
trade credit and microfi nance institutions relative to other sources at start-up.


Figure B4.6.1 Education and Work Experience Are Linked


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


25


50


75


100


Paid
employee in
public sector


Paid
employee in


formal
sector


Paid
employee in


informal
sector


Unpaid
employee


Unemployed


Pe
rc


en
ta


ge
h


av
in


g
sp


ec
ifi


ed
e


du
ca


ti
on


Degree Some university education Vocational training


Primary school No schoolingSecondary school




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 109


(fi gure 4.6). Th is is unsurprising because the average age of entrepreneurs is far
higher than that of the general population. Over half of male and female entre-
preneurs are married. For both genders, the share of married people is higher
among those in the formal sector.


Along gender lines, one diff erence is that the share of men in the formal
sector is higher than that of women. Given that the time demand of entrepre-
neurship is likely to be higher in the formal sector than in the informal sector,
the relatively higher presence of married men than of married women likely
refl ects the greater time demand on women at home. One further diff erence
is that, in the formal sector, the share of single women is higher than that of
single men.


Another important gender diff erence is that the divorced and widowed
are more represented among female than male entrepreneurs, especially in
the informal sector. Th eir informal sector prevalence suggests that they face
particularly high barriers to entering the formal sector.


Enterprise Formation
Th e four-country survey of entrepreneurs who recently started a business shows
that 86 percent of enterprises are newly created, rather than old enterprises in a
diff erent guise. Th is dominance holds true for male and female entrepreneurs,


Figure 4.6 Married People Predominate among New Entrepreneurs


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


20


40


60


80


100


Male Female Male Female
Formal Informal


Marital status by gender and formality
Pe


rc
en


ta
ge


h
av


in
g


sp
ec


ifi
ed


m
ar


it
al


s
ta


tu
s


Widowed Divorced Married Cohabiting Single




110 ENTERPRISING WOMEN


and for the formal and informal sectors (fi gure 4.7). Most of the diff erence is
along sector lines (formal or informal) rather than gender lines.


Th ose starting a new enterprise tend to have diff erent prior work
experience from those acquiring or expanding an existing family business.
Th ose who had previously been unpaid, unemployed, or not in the labor
force were twice as likely to start a new business as those who had been paid
employees.


Gender diff erences as well as sector diff erences are apparent in acquiring or
expanding an existing enterprise—or creating a new one. For men, newly cre-
ated businesses tend to be smaller (in terms of employees or start-up capital)
than those created from an existing enterprise. For women the two types of
businesses showed much less diff erence (fi gure 4.8).


What about diff erences in how women and men see “success”? Women in the
formal sector appear to place more value on remaining in business and expand-
ing their customer base than in raising profi ts per se (see box 4.7).


Choice 4: Line of Business


All entrepreneurs face the twin decisions—whether sequential or simulta-
neous—of starting a business and choosing a line of business. Th e choice
of business line is aff ected by profi t opportunities and by limitations stem-
ming from, for example, time, expertise, and access to fi nance (Jones and
Barr 1996). Familiarity with a business line gained from prior work experi-
ence or a prior family enterprise can also be infl uential. So too can cultural


Figure 4.7 Very Few Enterprises Are Set Up from Existing Outfits


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


2


4


6


8


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


b
eg


un


fro
m


a
n


ex
is


tin
g


es
ta


bl
is


hm
en


t


10


12


14


16


Male Female Male Female


Formal Informal




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 111


expectations, particularly regarding gender roles (Chitsike 2000; Fafchamps
2001; Farré and Vella 2007; Fogli and Veldkamp 2001; Gneezy, Leonard, and
List 2009; World Bank 2002, 2011). Th e three factors infl uencing the line
of business that are cited most oft en in the surveys of new entrepreneurs
are identifying a new market, seeing an inspiring case, and having prior


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


Figure 4.8 New Businesses Started by Women Average Less Capital and Fewer Initial
Employees—Regardless of Whether the Business Was Acquired or a Start-Up


0


2,500


5,000


U
.S


. d
ol


la
rs


7,500


Female Male


a. Initial capital


0


2


4


N
um


be
r


of
in


it
ia


l e
m


pl
oy


ee
s


6


8


Female Male


b. Initial employees


Started new business Took over existing firm




112 ENTERPRISING WOMEN


BOX 4.7


Do Entrepreneurs’ Reported Criteria for Success Refl ect
Effort and Performance?
While more traditional variables such as value added and labor productivity are the most
common criteria used for measuring success, entrepreneurs themselves may have dif-
ferent conceptions of success. It is important to fi nd out if possible differences in their
criteria for success refl ect differences across sectors (formal or informal) or in gender, as
different conceptions of success could infl uence their effort and thus their performance.


The two most common criteria for success cited by respondents to the survey of new
entrepreneurs are attaining some preset profi t and expanding the number of customers
(see fi gure B4.7.1). Among informal entrepreneurs, men and women rate these crite-
ria almost identically.  In the formal sector more male than female entrepreneurs cite
attaining a preset profi t, but male entrepreneurs cite expanding the customer base less
often than female entrepreneurs.


Expanding their range of products or services and remaining in business for at least
10 years are the next two most common criteria. In formal and informal sectors the
gender differences are fairly small. And for all entrepreneurs such criteria as providing
employment for family or expanding the number of employees are not important. Thus
the differences by level of formality or gender are relatively few.


Figure B4.7.1 New Entrepreneurs’ Criteria for Success Differ Only Slightly by Gender and
Registration Status


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0
5


10
15
20
25
30
35
40
45


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs


ci
ti


ng
c


ri
te


ri
on


Attain a preestablished level of profit Expand customer base


Expand number of employees


Still be in business in 10 years
Provide employment for family
Other


Expand range of services/products
provided




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 113


Figure 4.9 Prior Experience, New Market Opportunities, and Inspiring Cases Prompt
Entrepreneurs to Select Their Line of Business


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0 20 40 60
Percentage of entrepreneurs citing factor as


important in choosing line of business


80 100


Had prior experience


Wanted to continue/expand family business


Identified new market opportunity


Saw an inspiring case


Ease of entering sector


Need for low investment


Lack of potential competitors


Greater flexibility


Female Male Informal Formal


experience in a particular line (fi gure 4.9). Informal entrepreneurs cite these
three factors less oft en.


Entrepreneurs motivated by confi dence in their own skills and by optimism
about future profi tability are more likely to be infl uenced by some market
opportunity in choosing their product line. Th ose looking for fl exibility in
choosing their product line tend also to claim fl exibility as a major factor in
their decision to become an entrepreneur.


For two factors (fl exibility and easy entry due to low investment), no
gender or sector diff erences are discernible. But such diff erences are evident
in the importance attached to prior experience and the lack of potential com-
petitors: male and formal entrepreneurs are more likely to cite them than
female and informal entrepreneurs. Further, the gender diff erence holds even
aft er controlling for other individual and enterprise characteristics. For expe-
rience, this pattern likely refl ects the fact that the occupational history of
entrepreneurs is a signifi cant determinant of their sector choice. As shown
previously, formal entrepreneurs are likely to be drawn from the ranks of paid
employees of other formal fi rms. And the fi nding on the presence of poten-
tial competitors no doubt refl ects a formal entrepreneur’s superior advantage
in being less fi nancially constrained or burdened by other obstacles such as
registration. In fact, entrepreneurs who cite prior experience and presence of
competitors are likely to have more start-up capital and be initially registered
at start-up.




114 ENTERPRISING WOMEN


Options Not Pursued
Fewer than a quarter of entrepreneurs gave much consideration to pursuing a
diff erent business line. Of these, the overwhelming share were men (87 percent
of those in the formal sector and 71 percent of those in the informal sector).


Th e four most common reasons for not pursuing other business lines are
shown in fi gure 4.10. Male and formal entrepreneurs are more likely than their
female and informal counterpart to rate issues as important in the decision to
discard other lines. Th e exception is high upfront investment (slightly more
important to women than men). Th is fi nding is a concern because it would
be consistent with more limited access to fi nance, which constrains not only the
size of fi rms, but fi rms’ distribution across sectors and business lines.


Concerns about the high upfront investments needed to go into an
alternative business line could be an indicator of risk aversion—about sink-
ing in high fi xed costs without knowing whether the business is profi table.
It could also refl ect inadequate access to fi nance among many potential
entrepreneurs.


Part II has shown the extent of gender sorting across activities. A major
fi nding is that within similar enterprises, women and men have similar char-
acteristics. So gender gaps in education, work experience, and access to assets
are important in explaining the sorting. How to address these underlying gaps


Figure 4.10 Both Opportunities and Constraints Play a Role in New Entrepreneurs’ Decision
Not to Pursue Other Business Lines


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0 5 10


Percentage of entrepreneurs citing factor
as most important reason


15 20 25


Business line profitable


Competition in the market


High up-front investment


Lack of competent workers


Lack of tech/market knowledge


Alternative was riskier


Less flexible hours


Required better infrastructure


Female Male Informal Formal




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 115


is addressed in part IV. Before turning to that agenda, we look in part III at
whether the sorting matters for outcomes and opportunities.


Notes
1. Even though the data estimates suggest an inverted-U shape for such probability,


the peaks for men and women are at 79 years of age, outside our population of
interest.


2. An alternative measure would look at the legal economic rights. However, this
approach involves a series of dichotomous variables and so does not provide the
same degree of variation to exploit.


3. Percentages cited here and in the next paragraph are from national representa-
tive household surveys for 34 economies in Sub-Saharan Africa, most recent year
(2000–10).


4. But there is wide variation between countries. For Ethiopia, Rwanda, and São Tomé
and Príncipe, the share of married self-employed women is below 50 percent, while
for Benin, Burkina Faso, and Senegal, the share is 80 percent or above.


References
Aterido, A., and M. Hallward-Driemeier. 2011. “Whose Business Is It Anyway?” Small


Business Economics 37 (4): 443–64.
Aubert, P., E. Cavoli, and M. Rogers. 2006. “New Technologies, Organisation and Age:


Firm-Level Evidence.” Economic Journal 116 (509): 73–93.
Banerjee, A., and A. Newman. 1993. “Occupational Choice and the Process of Develop-


ment.” Journal of Political Economy 101: 274–98.
Behaghel, L., and N. Greenan. 2005. “Training and Age-Biased Technological Change:


Evidence from French Microenterprises.” Working Paper 2005–06, Centre de
Recherche en Économie et Statistique, Paris.


Blanchfl ower, D. G., and A. J. Oswald. 1998. “What Makes an Entrepreneur?” Journal of
Labor Economics 16 (10): 26–60.


Blau, D. 1985. “Self-Employment and Self-Selection in Developing Country Labor
Markets.” Southern Economic Journal 52 (2): 351–63.


Chitsike, C. 2000. “Culture as a Barrier to Rural Women’s Entrepreneurship: Experience
from Zimbabwe.” Gender and Development 8 (1): 71–77.


Colonia-Willner, R. 1998. “Practical Intelligence at Work: Relationship between Aging
and Cognitive Effi ciency among Managers in a Bank Environment.” Psychology and
Aging 13 (1): 45–57.


Dessing, M. 2002. “Labor Supply, the Family and Poverty: Th e S-Shaped Labor Supply
Curve.” Journal of Economic Behavior and Organization 49 (4): 433–58.


Djankov, S., E. Miguel, Y. Qian, G. Roland, and E. Zhuravskaya. 2005. “Who Are Russia’s
Entrepreneurs?” Journal of the European Economic Association 3 (2–3): 587–97.


Djankov, S., Y. Qian, G. Roland, and E. Zhuravskaya. 2006. “Who Are China’s
Entrepreneurs?” American Economic Review 96 (2): 348–52.




116 ENTERPRISING WOMEN


Fafchamps. M. 2001. “Networks, Communities, and Markets in Sub-Saharan Africa:
Implications for Firm Growth and Investment.” Journal of African Economies
10 (Suppl. 2): 109–42.


Farré, L., and F. Vella. 2007. “Th e Intergenerational Transmission of Gender Role Atti-
tudes and Its Implications for Female Labor Force Participation.” Discussion Paper
Series 2802, Institute for the Study of Labor, Bonn.


Fogli, A., and L. Veldkamp. 2001. “Nature or Nurture? Learning and the Geography of
Female Labor Force Participation.” Econometrica 79 (4): 1103–38.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Gneezy, U., K. L. Leonard, and J. A. List. 2009. “Gender Diff erences in Competition:
Evidence from a Matrilineal and a Patriarchal Society.” Econometrica 77 (5): 1637–64.


Goldin, C. 1990. Understanding the Gender Gap: An Economic History of American
Women. Oxford: Oxford University Press.


Grossbard-Shechtman, S., and S. Neuman. 1998. “Women’s Labor Supply and Marital
Choice.” Journal of Political Economy 96 (6): 1294–302.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Haltiwanger, J. C., J. I. Lane, and J. R. Spletzer. 1999. “Productivity Diff erences across
Employers: Th e Roles of Employer Size, Age and Human Capital.” American Economic
Review 89 (2): 94–98.


Heintz, J. 2012. “Why Do People Work in Informal Employment? Determinants of Selec-
tion into Self-Employment in Ghanaian Labor Markets.” Journal of Applied Economic
Research 6 (2): 181–209.


ILO (International Labour Organization). 2002. “Women and Men in the Informal
Economy: A Statistical Picture.” Gender and Employment Sector, ILO, Geneva.


Iyer, R., and A. Schoar. 2010. “Are Th ere Cultural Determinants of Entrepreneurship?”
In International Diff erences in Entrepreneurship, edited by J. Lerner, 209–40. Chicago:
University of Chicago Press.


Jones, P., and A. Barr. 1996. “Learning by Doing in Sub-Saharan Africa: Evidence from
Ghana.” Journal of International Development 8 (3): 445–66.


Kevane, M., and B. Wydick. 2001. “Microenterprise Lending to Female Entrepreneurs:
Sacrifi cing Economic Growth for Poverty Alleviation.” World Development 29
(7): 1225–36.


Klapper, L., and S. Parker. 2010. “Gender and the Business Environment for New Firm
Creation.” World Bank Research Observer 26 (2): 237–57.


Maloney, W. 2004. “Informality Revisited.” World Development 32 (7): 1159–78.
Mammen, K., and C. Paxon. 2000. “Women’s Work and Economic Development.”


Journal of Economic Perspectives 14: 141–64.
Minniti, M. 2009. “Gender Issues in Entrepreneurship.” Foundations and Trends in Enter-


preneurship 5 (7–8): 497–621.




SORTING INTO ENTREPRENEURIAL ACTIVITIES: INDIVIDUAL PATTERNS 117


Parker, S. C. 2004. Th e Economics of Self-Employment and Entrepreneurship. Cambridge:
Cambridge University Press.


Parker, S. C., and M. van Praag. 2006. “Schooling, Capital Constraints, and Entrepre-
neurial Performance.” Journal of Business and Economic Statistics 24 (4): 416–31.


Van der Sluis, J., M. van Praag, and W. Vijverberg. 2008 “Education and Entrepreneur-
ship Selection and Performance: A Review of the Literature.” Journal of Economic
Surveys 22 (5): 795–841.


World Bank. 2002. Engendering Development. Policy Research Report. Washington, DC:
World Bank.


. 2011. World Development Report 2012: Gender Equality and Development.
Washington, DC: World Bank.






Part III


How Women
Perform—and
the Constraints
They Face
Does the gender sorting across types of enterprises matter for
economic outcomes? Th is section looks at the extent of gaps in
productivity between enterprises run by women and men, and
how constraints in the business environment can vary by gender.
A  central question is the extent to which gender matters directly—
or indirectly, because of the diff erences in economic activities
where women and men are active. For example, do women have a
harder time accessing fi nance because they are women, or because
they are running smaller, informal fi rms that are perceived to be
less creditworthy?






121


Chapter 5


How Sorting Affects Gender Gaps in
Productivity and Profi ts


Part I showed that women entrepreneurs are more concentrated in self-
employment, in smaller fi rms, in the informal sector, and in more traditional
sectors. Th e questions for this chapter are these: Are women’s enterprises less
productive or profi table than men’s enterprises? If so, are productivity gaps due
to diff erences in sorting across types of entrepreneurial activities, or are they
present between women and men engaged in the same activity?


Th e literature on fi rm performance focuses on diff erences across fi rms
mainly by size and secondarily by sector (Aterido, Hallward-Driemeier, and
Pages 2011; Ayyagari, Beck, and Demirgüç-Kunt 2007; Beck, Demirgüç-Kunt,
and Maksimovic 2005; Falco and others 2009; Tybout 2000). Liedholm and
Mead (1999), McPherson (1995), and Mead (1994) provide some of the ear-
lier literature, with an explicit focus on micro and small fi rms. Large fi rms
are not included as comparators, however. Even so, size and age emerge as
important explanatory variables of growth and profi tability, though they are
less important for survival. On this last point, later work by Frazer (2005)
and Harding, Söderbom, and Teal (2006) confi rms the result that size aff ects
performance, but that larger fi rms are also more likely to survive. Indeed, this
work raises the question of what it means that so many small and produc-
tive fi rms exit: is it due to an inability to weather adverse shocks, or is it a
sign that successful entrepreneurs are off ered more lucrative and steady wage
employment opportunities elsewhere? Sleuwaegen and Goedhuys (2002) in
Côte d’Ivoire and Van Biesebroeck (2005) in nine countries fi nd important
contributions to productivity from large fi rms, arguing that the region dis-
plays evidence of a missing middle. Bigsten and Gebreeyesus (2007) also fi nd
that age matters as well as size, as does Söderbom (2012) and Söderbom and
Teal (2004). Th ese latter papers, however, do not include gender as a signifi -
cant part of their analysis.


Th is chapter fi nds that the choice of industry, the size of the enterprise, and
the decision about whether to operate in the formal sector markedly aff ect per-
formance patterns. It also fi nds a gap in average productivity between men’s




122 ENTERPRISING WOMEN


and women’s enterprises. But controlling for formal enterprise characteristics,
industry, and size of business—thereby comparing like with like—shrinks
productivity gaps and can remove them altogether.


Particularly among registered enterprises, gender in itself does not account
for productivity diff erences among similar types of enterprises. Instead, gender
gaps exist in that women account for such a small share of formal entrepreneurs.
In the informal sector, other enterprise and entrepreneur characteristics account
for most of the productivity gap. Similar patterns are found using earlier
rounds of the Enterprise Surveys, in Sub-Saharan Africa as well as in Eastern
Europe and Central Asia, with gender gaps persisting only among the smallest
enterprises (Bardasi, Blackden, and Guzman 2007; Bardasi and Sabarwal 2009;
Sabarwal and Terrell 2008). Indeed, this chapter fi nds that the type of enterprise
where gender gaps persist, even controlling for other characteristics, is informal
home-based enterprises. Diff erences in hours of operation seem to account for
much of the productivity gap, though the scarcity of data makes it hard to sub-
stantiate this claim.


Examining the extent to which country characteristics aff ect enter-
prise performance—notably income, governance, and indexes of gender
equality—this chapter fi nds that countries with higher incomes tend to have
fi rms with higher value added per worker, but also larger gender gaps in
average performance measures. In these environments women’s continued
higher concentration in traditional lower-value-added industries keeps
them from benefi ting from the opportunities at the top end. Controlling
for size and industry still has the eff ect of making gender insignifi cant as an
explanatory variable for performance measures; not taking these enterprise
characteristics into account shows that gender diff erences can actually rise
with income.


Still, a country’s income, governance, and indexes of gender equality tend
to have weaker explanatory power than enterprise characteristics: the type of
enterprise matters more in explaining patterns of performance (see Hallward-
Driemeier and Rasteletti [2010] for more details).


It is encouraging that there are few or no signifi cant diff erences between
female and male entrepreneurs in the productivity of their businesses
(aft er controlling for other key enterprise characteristics). It confi rms that
Sub-Saharan Africa has considerable hidden growth potential in its women,
and that tapping that potential—such as improving women’s choices of where
to be economically active—can boost the region’s economic growth (World
Bank 2011). Th is fi nding underscores the importance of analyzing where
obstacles to women and men have gender diff erences (undertaken in this
chapter), and why the patterns of entrepreneurship persist (undertaken
in part IV).




HOW SORTING AFFECTS GENDER GAPS IN PRODUCTIVITY AND PROFITS 123


Productivity and Gender Gaps


We use value added per worker as the base measure of performance among
registered fi rms. Simply comparing women and men points to a gender gap in
labor productivity of about six percentage points, but comparing them in enter-
prises of the same industry, size, and capital intensity shows no productivity gap
( fi gure 5.1). So the productivity gap stems from women operating in lower-value-
added sectors and smaller fi rms, rather than from gender itself. In other words,
controlling for enterprise characteristics, among registered fi rms at least, explains
the unconditional gender gap (Hallward-Driemeier and Rasteletti 2010).


With no control for any enterprise characteristics, value added per worker
averages 5.8 percent less in female enterprises (fi gure 5.1, top bar). Th e size of
the gap closes somewhat when the industry of operation is controlled (middle
bar). Adding fi rm size, measured by the number of employees, reduces the gap
to 3.9 percentage points, and the gap is no longer statistically signifi cant. Finally,
also controlling for the capital intensity of the enterprise makes the coeffi cient
on gender completely insignifi cant.1


Figure 5.1 Controlling for Enterprise Characteristics Removes the Gender Gap
in Productivity (registered firms)


Source: Hallward-Driemeier and Rasteletti 2010.
Note: Analysis is based on regressions using data from 37 Sub-Saharan countries, with country dummies
included to capture country-invariant effects. Thus the results are all based on within-country differences.
A dummy is included for whether there is female participation in ownership.


–6 –4 –2 0 2


Size of enterprise, sector, capital intensity


Control for size of enterprise


Control for sector


No controls


Percentage of gender gap in average firm labor productivity




124 ENTERPRISING WOMEN


One question is whether these results are also robust to diff erent measures of
defi ning “women’s enterprises.” For the four countries with additional informa-
tion on the main decision maker (Côte d’Ivoire, Kenya, Nigeria, and Senegal),
the unconditional gender gap is more than 1.5 times as large, at 10 percent.
But here again, once enterprise characteristics are controlled for, the gap
shrinks considerably. And once measures of the entrepreneur’s human capital
are included, the gap becomes insignifi cant (Aterido and Hallward-Driemeier
2011).


Similar patterns hold for new entrepreneurs and formality. (Here we have
less information on material inputs, so our metric for enterprise productivity
is revenue per worker.) Diff erences are accounted for by formality rather than
gender (fi gure 5.2).


Among the newly created enterprises, median revenue per worker in the
formal sector is more than three times that in the informal sector (fi gure 5.3). In
fact, female entrepreneurs’ median productivity in the formal sector is actually
higher than that of their male counterparts, but no signifi cant diff erence exists
in the informal sector (Gajigo and Hallward-Driemeier 2010).


Th e data can be further disaggregated by industry. An industry’s formality
and its median revenue per worker have a close positive relationship
(fi gure 5.4).


On the other hand, the correlation between an industry’s degree of formality
and its share of enterprises run by women is signifi cantly negative (fi gure 5.5).


Figure 5.2 New Entrepreneurs in the Formal Sector Have Significantly Higher Revenue per
Worker Than Their Informal Counterparts


Source: Gajigo and Hallward-Driemeier 2010.
Note: Kernel = Epanechnikov; bandwidth = 0.2725. Data are for newly established enterprises in Côte d’Ivoire,
Kenya, Nigeria, and Senegal, 2010.


0


0 5 10 15


D
en


si
ty


Log of revenue per worker (US$)


0.1


0.2


0.3


0.4


Male, formal sectorFemale, formal sector


Male, informal sector Female, informal sector




HOW SORTING AFFECTS GENDER GAPS IN PRODUCTIVITY AND PROFITS 125


Figure 5.3 New Entrepreneurs’ Median Revenue per Worker Is Higher for Women Than Men
in the Formal Sector


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0


100


200


300


400


500


600


Male Female Male Female


Formal Informal


Median productivity by sector and gender


M
ed


ia
n


re
ve


nu
e


pe
r


w
or


ke
r


(U
S$


)


Figure 5.4 Median Revenue per Worker Trends Higher in Formal Sector Industries


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


Revenue per worker Formality


0
10
20
30
40
50
60
70
80
90


0


100


200


300


400


500


600
Pe


rc
en


ta
ge


o
f f


or
m


al
fi


rm
s


in
s


ec
to


r


Re
ve


nu
e


pe
r


w
or


ke
r


(U
S$


)


Te
xti


les
an


d g
arm


en
ts


Re
tai


l sa
le


in
no


ns
pe


cia
lty


st
ore


s


Re
tai


l sa
le


of
tex


tile
s,


clo
thi


ng
, fo


otw
are


Wh
ole


sal
e


Re
tai


l sa
le


of
foo


d,
be


ve
rag


es,
to


ba
cco


Ot
he


r s
erv


ice
s


Ot
he


r re
tai


l


Co
ns


tru
cti


on


Ch
em


ica
ls,


pla
sti


cs,
an


d r
ub


be
r


Tra
ns


po
rt


Fo
od


Ma
ch


ine
ry


an
d e


qu
ipm


en
t a


nd
el


ect
ron


ics


Ba
sic


m
eta


ls a
nd


m
eta


l p
rod


uc
ts


Ot
he


r m
an


ufa
ctu


rin
g


Ho
tel


an
d r


est
au


ran
t




126 ENTERPRISING WOMEN


A simple comparison of women and men shows women’s enterprises as less
productive, but a large share of the measure of productivity is really due to
women’s concentration in informal industries.


Th e average fi rm size in Sub-Saharan Africa is smaller than in other regions,
though not always signifi cantly so. Aterido, Beck, and Iacovone (forthcoming)
test whether women’s enterprises are smaller than men’s on average and how
this pattern may vary in Sub-Saharan Africa using the database of Enteprise
Surveys. Controlling for fi rm size, sector, location, export status, legal status,
and ownership, fi rms with female participation in ownership tend to be 7.6–
10.3 percent smaller. But women’s enterprises are not disproportionately smaller
in Sub-Saharan Africa (the coeffi cient on “female” is negative and signifi cant,
showing the eff ect ranges from −7.6 to −10.3 percent. But the coeffi cient on
“female_Africa” is not signifi cant; see Aterido, Beck, and Iacovone 2011 for
more details).


Among household enterprises, more evidence of gender gaps in performance
emerges, though this must be seen in a context of additional data challenges.
Th e surveys do not consistently ask for the time spent working in the enterprise,
either as hours a week or weeks a year. Th e Enterprise Surveys limit themselves


Figure 5.5 Median Revenue per Worker Tends to Be Lower in Sectors with Greater Female
Ownership


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal, 2010.


0
5
10
15
20
25
30
35
40
45


0


100


200


300


400


500


600


Re
ve


nu
e


pe
r


w
or


ke
r


(U
S$


)


Pe
rc


en
ta


ge
o


f
fe


m
al


e-
ow


ne
d


en
te


rp
ri


se
s


Ba
sic


m
eta


ls a
nd


m
eta


l p
rod


uc
ts


Ch
em


ica
ls,


pla
sti


cs,
an


d r
ub


be
r


Co
ns


tru
cti


on


Ma
ch


ine
ry


an
d e


qu
ipm


en
t a


nd
el


ect
ron


ics


Ot
he


r m
an


ufa
ctu


rin
g


Ot
he


r s
erv


ice
s


Fo
od


Tra
ns


po
rt


Re
tai


l sa
le


of
foo


d,
be


ve
rag


es,
to


ba
cco


Ot
he


r re
tai


l


Wh
ole


sal
e


Re
tai


l sa
le


in
no


ns
pe


cia
lty


st
ore


s


Te
xti


les
an


d g
arm


en
ts


Re
tai


l sa
le


of
tex


tile
s,


clo
thi


ng
, fo


otw
are


Ho
tel


an
d r


est
au


ran
t


Median revenue Female




HOW SORTING AFFECTS GENDER GAPS IN PRODUCTIVITY AND PROFITS 127


to full-time enterprises, but many of the household enterprises are run only
part-time. Not being able to control for that fact is a concern, particularly
because the countries with measures of time spent show that women are more
likely to work part-time or seasonally. One option is that we restrict the sample
to urban settings, which are less likely to be aff ected by strong seasonal patterns.
Another is to distinguish comparisons of enterprises run out of the house from
those operated in a separate location. Th e assumption is that the former may be
more likely to be operating fewer hours.


Among household enterprises, the unconditional gender gap—at
50  percent—is considerably larger than in the Enterprise Survey data. Th e major-
ity of household enterprises are in the informal sector. Controlling for whether
the enterprise is registered reduces the gap by half, with productivity rising as
much for women as men among registered businesses.2 Th e eff ects of industry
and size also serve to reduce the gap. Looking at the subset of countries that
have information on the number of months of operation, we fi nd that control-
ling for the time spent working in the enterprise greatly narrows the gender gap.
Th is indicates the importance of taking into account the time spent in an enter-
prise, information not always available in the household surveys. It also cautions
against simple, unconditional comparisons of women’s and men’s enterprises.


Controlling for physical capital is also very important in looking at house-
hold enterprises, because once we do this, the gap in performance of female-
headed fi rms is no longer signifi cant.


Country Characteristics’ Effect on Potential Gender Gaps


Constraints to improving the performance of women’s enterprises exist at several
levels. In looking at the eff ect of country-level constraints on potential gender
gaps in performance, we review income per capita, quality of governance, and
indexes of gender equality constructed by international organizations.


Income per capita refl ects the country’s overall development status. It is oft en
highly correlated with the quality of the country’s infrastructure and institu-
tions, both of which should have general positive eff ects on business. Th e ques-
tion is whether they have a gender dimension in aff ecting people’s ability to
operate their business and improve its performance. Th e answer: they do. And,
perhaps surprisingly, not in women’s favor (box 5.1).


Beyond income, several other indicators of country characteristics could
aff ect fi rm performance. One is the quality of governance, measured through,
for example, control of corruption, political stability, or the rule of law (u sually
in combination). Better governance is generally associated with better private
outcomes. A mild gender eff ect is also apparent—women’s performance is
closer to men’s in better-governed countries.




128 ENTERPRISING WOMEN


BOX 5 .1


Gender Gaps in Labor Productivity and in Firm Size Can Rise
with Income
Countries with higher incomes tend to have fi rms with higher value added per
worker. The share of informal businesses tends to decline. Is the gender gap smaller
in high-income countries? No. The effects of industry selection there are even more
pronounced (Hallward-Driemeier and Shah 2009). Top performers earn high rates of
return and operate high-value-added businesses. In these environments women’s con-
tinued higher concentration in traditional lower-value-added industries keeps them
from benefi ting from these opportunities.


In average fi rm size, too, gender gaps can open at higher levels of development
in Sub-Saharan Africa (fi gure B5.1.1). The average size of female-owned fi rms rises
gently with income, but that of male-owned fi rms rises faster. Some of this differ-
ence is again explained by industry differences: in more-developed countries, the more
capital-intensive sectors operate at larger economies of scale. This fi nding makes clear
that the need to increase women’s participation in higher-end entrepreneurial activities
is relevant across the income spectrum.


Figure B5.1.1 The Sector-Selection Effects of Average Firm Size Appear Greatest in
More-Developed Countries


Source: Hallward-Driemeier and Shah 2009.
Note: The relationship is fitted with a polynomial rather than a straight line.


0


Ma
li


Gu
ine


a


Ga
mb


ia,
Th


e


Gu
ine


a-B
iss


au


Se
ne


ga
l


Mo
za


mb
iqu


e


Ma
uri


tan
ia
Gh


an
a


Bu
run


di


An
go


la


Co
ng


o,
De


m.
Re


p.


Ug
an


da


Ni
ge


ria


Rw
an


da


Za
mb


ia


Ta
nz


an
ia
Ke


ny
a


Sw
az


ila
nd


Bo
tsw


an
a


So
uth


Af
ric


a


Na
mi


bia


20


40


60


80


100


120


Female Male


Fitted relationship (female) Fitted relationship (male)


A
ve


ra
ge


n
um


be
r


of
e


m
pl


oy
ee


s




HOW SORTING AFFECTS GENDER GAPS IN PRODUCTIVITY AND PROFITS 129


Finally, we consider aggregate measures collected by various international
organizations with a focus on gender equality and women’s empowerment
(appendix B). Most of these measures suggest that women may face particularly
challenging environments in Sub-Saharan Africa (fi gure 3.7). Indeed, we fi nd
that countries with weaker institutions of gender inclusion or equality tend to
have slightly wider gender gaps in performance (fi gure 5.6).


Yet despite the evidence that income, governance, and gender inclusion can
aff ect gender performance gaps, they tend to have smaller explanatory power
than enterprise characteristics. What kind of enterprise an entrepreneur runs
matters more than where it is located—although location or country character-
istics are signifi cant in that they enable diff erent types of enterprises to thrive.


Notes
1. As capital intensity is available only for manufacturing fi rms, which are just under


half of the sample, repeating the initial specifi cation shows that the same uncondi-
tional gender gap exists within manufacturing; the lack of a signifi cant gender gap
once the enterprise characteristics are controlled for is thus not due to any selection
issue or special characteristics of the subset of fi rms with capital stock information
available.


2. Th us, the coeffi cient on “registered” is large and positive, and the gender-registration
interaction term is small and insignifi cant.


Development
(GDP per capita)


Controlling for sector selection is
important in high-income countries;


women’s lower participation in capital-
and technology-intensive sectors


becomes relatively more
costly in more sophisticated markets.


Social/Gender Inclusion


More inclusion is associated
with smaller performance gaps.


Governance
(control of corruption; government


effectiveness)


Good governance reduces gender
performance gaps; women benefit


disproportionately from it.


Human Capital
(educational attainment)


Declines in gender education gaps are
associated with declines in


performance gaps—particularly
when governance is strong.


Figure 5.6 Gender Gaps in Revenue per Worker Are Affected by Country Characteristics


Source: Hallward-Driemeier and Rasteletti 2010.




130 ENTERPRISING WOMEN


References
Aterido, R., T. Beck, and L. Iacovone. Forthcoming. “Gender and Finance in Sub-Saharan


Africa: Are Women Disadvantaged?” World Development.
Aterido, R., and M. Hallward-Driemeier. 2011. “Whose Business Is It Anyway?” Small


Business Economics 37 (4): 443–64.
Aterido, R., M. Hallward-Driemeier, and C. Pages. 2011. “Big Constraints to Small Firms’


Growth? Business Environment and Employment Growth across Firms.” Economic
Development and Cultural Change 59 (3): 609–47.


Ayyagari, M., T. Beck, and A. Demirgüç-Kunt. 2007. “Small and Medium Enterprises
across the Globe.” Small Business Economics 29: 415–34.


Bardasi, E., M. Blackden, and J. C. Guzman. 2007. “Gender, Entrepreneurship, and
Competitiveness.” In Africa Competitiveness Report 2007, edited by World Economic
Forum, African Development Bank, and World Bank, 69–86. Geneva: World
Economic Forum, African Development Bank, and World Bank.


Bardasi, E., and S. Sabarwal. 2009. “Gender, Access to Finance, and Entrepreneurial
Performance in Sub-Saharan Africa.” Working paper, World Bank, Washington, DC.


Beck, T., A. Demirgüç-Kunt, and V. Maksimovic. 2005. “Financial and Legal Constraints
to Growth: Does Firm Size Matter?” Journal of Finance 60 (1): 137–77.


Bigsten, A., and M. Gebreeyes us. 2007. “Th e Small, the Young, and the Productive:
Determinants of Manufacturing Firm Growth in Ethiopia.” Economic Development
and Cultural Change 55 (4): 813–40.


Falco, P., A. Kerr, N. Rankin, J. Sandefur, and F. Teal. 2009. “Th e Returns to Formality
and Informality in Urban Africa.” Working Paper Series 2010-03, Centre for the Study
of African Economies, Oxford, U.K.


Frazer, G. 2005. “Which Firms Die? A Look at Exit from Manufacturing in Ghana.”
Economic Development and Cultural Change 53 (3): 585–617.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and M. Shah. 2009. “Female Entrepreneurship in Sub-Saharan
Africa: Diff erences across Sub-Regions and Sizes of Firms.” Working paper, World
Bank, Washington, DC.


Harding, A., M. Söderbom, and F. Teal 2006. “Th e Determinants of Survival among
African Manufacturing Firms.” Economic Development and Cultural Change 54
(3): 533–56.


Liedholm, C., and D. Mead. 1999. Small Enterprises and Economic Development: Th e
Dynamics of Micro and Small Enterprises. London: Routledge.


McPherson, M. 1995. “Growth of Micro and Small Enterprises in Southern Africa.”
Journal of Development Economics 48: 253–77.


Mead, D., C. 1994. “Th e Contribution of Small Enterprises to Employment Growth in
Southern and Eastern Africa.” World Development 22 (December): 1881–94.




HOW SORTING AFFECTS GENDER GAPS IN PRODUCTIVITY AND PROFITS 131


Sabarwal, S., and K. Terrell. 2008. “Does Gender Matter for Firm Performance? Evidence
from Eastern Europe and Central Asia.” Policy Research Working Paper 4705,
World Bank, Washington, DC.


Sleuwaegen, L., and M. Goedhuys. 2002. “Growth of Firms in Developing Countries,
Evidence from Côte d’Ivoire.” Journal of Development Economics 68 (June): 117–35.


Söderbom, M. 2012. “Firm Size and Structural Change: A Case Study of Ethiopia.” Jour-
nal of African Economies 21: ii126–51.


Söderbom, M., and F. Teal. 2004. “Size and Effi ciency in African Manufacturing Firms:
Evidence from Firm-Level Panel Data.” Journal of Development Economics 73 (Febru-
ary): 369–94.


Tybout, J. R. 2000. “Manufacturing Firms in Developing Countries: How Well Do Th ey
Do, and Why?” Journal of Economic Literature 28 (March): 11–44.


Van Biesebroeck, J. 2005. “Firm Size Matters: Growth and Productivity Growth in
African Manufacturing.” Economic Development and Cultural Change 53 (3): 545–83.


World Bank. 2011. World Development Report 2012: Gender Equality and Development.
Washington, DC: World Bank.






133


Chapter 6


How Sorting Affects Constraints


Th e analysis in chapter 5 compared the performance of women’s and
men’s enterprises. Th is chapter turns to the constraints on entrepreneurs
in operating and expanding their business. Are they diff erent for men and
women?


The literature points to constraints in the business environment or
investment  climate in which a fi rm operates as signifi cantly aff ecting fi rm
profi tability and growth (Aterido and Hallward-Driemeier 2010; Aterido,
Hallward-Driemeier, and Pages 2011; Bardasi, Blackden, and Guzman 2007;
Batra, Kaufmann, and Stone 2003; Bigsten and others 2003; Dollar, Hallward-
Driemeier, and Mengistae 2005; McCormick, Kinyanjui, and Ongile 1997;
Ramachandran, Gelb, and Shah 2009; World Bank 2004). However, the severity
and relative importance of any given constraint can vary by type of enterprise
or by the gender of the entrepreneur. Improving the investment climate may
not necessarily succeed in leveling the playing fi eld. If there are systematic dif-
ferences by type of enterprise or by the gender of the entrepreneur in which
constraints are binding, then reforms that address those constraints will be
disproportionately benefi cial for those enterprises or entrepreneurs. In setting
priorities for reforms of the business environment, a disaggregated approach to
understanding constraints is clearly needed.


Th e chapter uses surveys of entrepreneurs to understand the types and
severity of such obstacles. Enterprise Surveys are the primary data source. Th e
gender modules and the surveys of new entrepreneurs allow fi ner-grained anal-
ysis, making it possible to capture diff erent defi nitions of “female” or “woman’s”
business. Th e Enterprise Surveys provide two types of data on constraints. Th e
fi rst are subjective rankings of the degree to which specifi c issues constrain
operating and expanding a business; they are responses to questions such as
“How constraining is access to fi nance to the growth of your fi rm?” Th e second
are quantitative measures of the time and costs associated with particular types
of transactions; they are responses to questions such as “Do you have a loan?
What are the terms of the loan?”


Issue areas will likely vary in whether there is a gender dimension to them,
and whether any gender dimension is direct or indirect. Access to fi nance is one




134 ENTERPRISING WOMEN


area that is oft en reported to pose greater challenges for women. Interactions
with offi cials and access to land are others. Other issues of infrastructure, such
as access to reliable electricity or to roads, are less likely to have a direct gender
impact, but may reveal some gender diff erences based on choice of sector or
size of the enterprise.


The survey evidence in this chapter shows patterns similar to the
performance outcomes discussed in chapter 5: once the characteristics of
the enterprise are controlled for, gender diff erences are not signifi cant.1 Th at
is, while there are some gender gaps, they are largely explained once enterprise
characteristics are taken into account; in similar industries and at similar fi rm
sizes, women and men report similar constraints. If women have a harder time
accessing land, for example, it is largely because small fi rms report this as a
greater constraint, and women are more likely to be in smaller fi rms. What
remains at issue is how much the original sorting into smaller and more infor-
mal fi rms itself refl ects gender diff erences in constraints.


Th ese fi ndings hold on average across Sub-Saharan Africa, but some
countries show more persistent gaps. Indeed, the quality of a country’s gov-
ernance and of its broad institutions of social inclusion is associated with
smaller gender gaps in performance. Still, the eff ect of country characteristics
is generally small compared with that of enterprise characteristics.


Four caveats bear repeating. First, the defi nition of female ownership can
underestimate some of the gender diff erences in constraints. If some of these
fi rms have a female owner but are otherwise run by men, counting them as
women’s enterprises masks diff erences between the genders. In this case, focus-
ing on sole proprietors gives a cleaner look at the role of gender and reveals
larger gender gaps in reported constraints in access to fi nance and as a result
of corruption.


Second, we do not have the data to fully analyze how constraints aff ect the
entry decision or the choice of formality, industry, or size itself. We can look
at the eff ects of gender within various fi rm sizes and conclude that size, rather
than gender, is the main determinant. But we cannot assess how much gender
diff erences in the constraints explain why women are more likely to run smaller
fi rms to begin with. Th e data needed to extend this analysis are lacking: gender-
disaggregated data remain scarce on potential entrepreneurs. Th ose who faced
conditions so constraining that they could not enter or remain in business are
not included.2


Th ird, reforms to address constraints may not always have the intended
consequences or be eff ective at increasing women’s empowerment, and in some
cases they could even be detrimental. Even if a constraint is identifi ed as having
a gender dimension, such as women having a harder time qualifying for credit,
increasing the credit that goes to women may not necessarily improve their
entrepreneurial outcomes or even their intrahousehold bargaining power.




HOW SORTING AFFECTS CONSTRAINTS 135


Th ere are positive examples, but some evidence is more mixed (Armendariz
and Roome 2008; Ashraf 2009; Banerjee and others 2009; Bruhn and Love
2011; Fafchamps and Quisumbing 2002; Kabeer 2001; Kantor 2005; Klapper
and Parker 2010).


Fourth, the reforms that businesses want most are not necessarily those
in the public interest, and so need to be interpreted with some caution.
Businesses will, for example, almost always want lower taxes and cheaper credit
(World Bank 2004).


Constraints Facing Entrepreneurs


Both subjective and quantitative information shed light on the extent to which
women and men face diff erent constraints.


Subjective Information
Th e detailed gender module in the fi ve countries and the survey of new entre-
preneurs in four countries (see box 1.3) asked respondents, regardless of the
overall severity of the constraint, whether women and men would face diff erent
degrees of constraint. Interestingly, both men and women identifi ed areas where
they thought women face greater challenges—and similar proportions agreed
on the same areas, though women reported interactions with the police and
court systems as greater (fi gure 6.1).


Th at these areas pose greater constraints for women makes sense in that
they are areas where characteristics of the individual entrepreneur could make
a diff erence. For areas like access to electricity or macroeconomic instability,
the surveys found no gender diff erences.


Th e responses do not, however, take into account gender patterns in the
types of enterprises women and men run, and how these could aff ect con-
straints. It turns out that controlling for enterprise characteristics is again
important in explaining much of the gender gap in constraints to improved
performance.


Figures  6.2  and 6.3 show the responses to the subjective questions in
the enterprise surveys, looking at four issues: access to fi nance, access to
land, corruption, and labor regulations. So that many more countries can
be covered, the data are based on the broader defi nition of female par-
ticipation in ownership, rather than the defi nition that takes into account
decision-making control. Figure 6.2 compares small and large formal fi rms,
and includes small informal enterprises to facilitate comparison between
informal and small formal fi rms. Th e exercise is repeated in fi gure 6.3 using
only sole proprietors, to ensure that the designated gender of the enterprise
captures decision- making power too.




136 ENTERPRISING WOMEN


For three of these issues the diff erences are more signifi cant by formality and
size than by gender. For access to fi nance, small formal fi rms perceive themselves
as having a harder time than large formal fi rms. Small informal enterprises do
not share this view, however, no doubt precisely because they oft en operate at
a very small scale where expectations of better bank loans are minimal. Small,
particularly informal, fi rms report access to land as a bigger constraint. Large
formal fi rms regard labor regulations as constraining, presumably refl ecting


Figure 6.1 Do Women Face Greater Constraints? Many Women—and Men—Think So


Source: Aterido and Hallward-Driemeier 2010.


0 10 20 30 40
Percent


50 60 70 80 90 100


Male


Female


Male


Female


Male


Female


Male


Female


Male


Female


Male


Female


Male


De
al


in
g


w
ith


th
e


po
lic


e


Female


O
bt


ai
ni


ng
lic


en
se


De
al


in
g


w
ith


ta
xe


s
an


d
ta


x
co


lle
ct


or
s


De
al


in
g


w
ith


la
bo


r
in


sp
ec


to
rs


O
bt


ai
ni


ng
cr


ed
it


De
al


in
g


w
ith


co
ur


ts


G
et


tin
g


a
go


ve
rn


m
en


t
co


nt
ra


ct


How would women fare compared to men?


Better or sameSlightly worseSignificantly worse




HOW SORTING AFFECTS CONSTRAINTS 137


Figure 6.2 Obstacles Vary More by Formality and Size of Firm Than by Gender
(subjective responses)


0


1


2


3


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)


4


Male Female Male Female Male Female


I: small F: small F: large


a. Access to finance


Male Female Male Female Male Female


I: small F: small F: large


b. Access to land


0


1


2


3


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)


—Continued




138 ENTERPRISING WOMEN


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.
Note: I = informal; F = formal. A small firm is defined as one with less than 20 employees; a large firm has 20 or
more employees. Respondents rated severity of obstacles on a scale of 0 to 4.


Figure 6.2 (continued)


Male Female Male Female Male Female


I: small F: small F: large


0


1


2


c. Corruption
A


ve
ra


ge
r


at
in


g
of


t
he


c
on


st
ra


in
t


(o
n


a
sc


al
e


of
0


–4
)


Male Female Male Female Male Female


I: small F: small F: large


0


1


2


d. Labor regulations


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)




HOW SORTING AFFECTS CONSTRAINTS 139


Figure 6.3 Obstacles Facing Sole Proprietors Show Somewhat Larger Differences by Gender
(subjective responses)


0


1


2


3


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)


4


Male Female Male Female Male Female


I: small F: small F: large


a. Access to finance


Male Female Male Female Male Female


I: small F: small F: large


b. Access to land


0


1


2


3


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)


—Continued




140 ENTERPRISING WOMEN


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.
Note: I = informal; F = formal. A small firm is defined as one with less than 20 employees; a large firm has 20 or
more employees. Respondents rated severity of obstacles on a scale of 0 to 4.


Figure 6.3 (continued)


Male Female Male Female Male Female


I: small F: small F: large


0


1


2


c. Corruption
A


ve
ra


ge
r


at
in


g
of


t
he


c
on


st
ra


in
t


(o
n


a
sc


al
e


of
0


–4
)


Male Female Male Female Male Female


I: small F: small F: large


0


1


2


d. Labor regulations


A
ve


ra
ge


r
at


in
g


of
t


he
c


on
st


ra
in


t
(o


n
a


sc
al


e
of


0
–4


)




HOW SORTING AFFECTS CONSTRAINTS 141


the greater red tape that comes with having more employees. Informal fi rms
also see them as a constraint, possibly refl ecting the fact that labor regula-
tions are one of the main reasons some fi rms stay informal (McKenzie and
Sakho 2010; McKenzie and Woodruff 2006). Large female formal fi rms report
corruption as a signifi cant constraint.


Objective Information
Respondents answered objective questions on four issues: frequency of pay-
ments needed to “get things done,” access to specifi c fi nancial services, the
amount of managers’ time spent with offi cials, and losses due to electricity
outages. Unfortunately, there is no corresponding indicator for access to land.
We use these more objective measures to see if we can confi rm that diff erences
vary less by gender and more by enterprise size and sector.


Th e survey results do confi rm the pattern: diff erences are generally more
signifi cant by size than gender (fi gure 6.4). For access to fi nance, small fi rms
complained more than large fi rms—consistent with fewer small fi rms having
a loan or even a bank account. Th e time managers spend with offi cials is also
dramatically diff erent by size, but only slightly by gender. Large fi rms’ managers
spend much more time dealing with offi cials, partly because their fi rms try to
comply with regulations (rather than trying to operate under the radar).


For corruption, the quantitative measure is of the share of fi rms that report
“fi rms like theirs” making payments to “get things done.” Th e subjective rankings
show less variation by size or gender; the objective data also show less variation
by size and only mild variation by gender. But informal microfi rms seem less
likely to pay (informality as a strategy of staying below the radar can succeed).
Losses due to electricity outages were greater for smaller fi rms than larger fi rms.
Part of the explanation is that larger fi rms have the scale and resources to pay for
generators. As expected, there is no diff erence in this measure by gender within
size categories of enterprises.


Similar patterns are also found when dividing the sample by industry and
gender rather than by size (fi gure 6.5). Th us enterprise characteristics (rather than
gender) help account for the obstacles to operating and expanding a business.


Infl uence of Constraints on Employment Category


Th e discussion of the microdata on constraints has focused on enterprise
performance, and has looked specifi cally at whether these obstacles could aff ect
women’s relative performance within an employment category. But there is a
second way these constraints could have a gender impact. Th ey could aff ect
the employment category men and women are more likely to enter. Th us
constraints, particularly gender gaps in constraints, could be what underlie




142 ENTERPRISING WOMEN


Figure 6.4 Obstacles to Doing Business Vary More by Size Than Gender
(quantitative responses)


0


10


20


30


40


50


Male Female
Small Large


Male Female


Pe
rc


en
ta


ge
o


f
en


tr
ep


re
ne


ur
s


re
po


rt
in


g
th


at


pa
ym


en
ts


n
ee


d
to


b
e


m
ad


e
"t


o
ge


t
th


in
gs


d
on


e"


a. Bribes


0


25


50


75


100


Male Female
Small Large


Male Female


Pe
rc


en
ta


ge
o


f fi
rm


s
w


it
h


ac
ce


ss
t


o
so


m
e


fin
an


ci
al


s
er


vi
ce


s


b. Access to finance




HOW SORTING AFFECTS CONSTRAINTS 143


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.
Note: A small firm is defined as one with less than 20 employees; a large firm has 20 or more employees.
“Access to finance” (figure 6.4b) is defined as having a bank account, overdraft, or loan.


Figure 6.4 (continued)


0


1


2


3


4


5


6


7


8


9


Male Female Male Female


Pe
rc


en
ta


ge
o


f
m


an
ag


em
en


t'
s


ti
m


e


c. Manager time with officials


Small Large


0


1


2


3


4


5


6


7


8


Male Female Male Female


d. Losses due to outages


Lo
ss


es
a


s
pe


rc
en


ta
ge


o
f s


al
es


(m
ea


n)


Small Large




144 ENTERPRISING WOMEN


Figure 6.5 Obstacles Vary More by Industry Than Gender (quantitative responses)


0


10


20


30


Pe
rc


en
ta


ge
o


f fi
rm


s


40


50


60


a. Bribes


M
al


e


Fe
m


al
e


M
al


e


Fe
m


al
e


M
al


e


M
al


e


Fe
m


al
e


Fe
m


al
e


Food Garment Manufacturing Service


Pe
rc


en
ta


ge
o


f fi
rm


s


M
al


e


Fe
m


al
e


M
al


e


Fe
m


al
e


M
al


e


M
al


e


Fe
m


al
e


Fe
m


al
e0


b. Access to finance


25


50


75


100


Food Garment Manufacturing Service




HOW SORTING AFFECTS CONSTRAINTS 145


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.


Figure 6.5 (continued)
Pe


rc
en


ta
ge


o
f m


an
ag


er
’s


t
im


e
(m


ea
n)


M
al


e


Fe
m


al
e


M
al


e


Fe
m


al
e


M
al


e


M
al


e


Fe
m


al
e


Fe
m


al
e0


1


2


3


4


5


6


7


8


9


c. Management time with officials


Food Garment Manufacturing Service


Lo
ss


es
a


s
pe


rc
en


ta
ge


o
f s


al
es


(m
ea


n)


M
al


e


Fe
m


al
e


M
al


e


Fe
m


al
e


M
al


e


M
al


e


Fe
m


al
e


Fe
m


al
e0


1


2


3


4


5


6


7


d. Losses due to outages


Food Garment Manufacturing Service




146 ENTERPRISING WOMEN


the diff erential entry into activities to begin with. Both directions of causality
are of interest. Again, data limitations restrict the extent to which this second
channel can be examined because there are few or no gender-disaggregated
data on constraints faced by those who do not become entrepreneurs. Th us one
cannot examine how the presence of constraints aff ected the entry decision.
(Chapter 8 addresses this potential channel when looking deeper into issues of
access to fi nance.)


Among established enterprises, the surveys of new entrepreneurs in Côte
d’Ivoire, Kenya, Nigeria, and Senegal are as close as we can get to understanding
the role of the constraints to entry. Th e data show four areas where gender could
have a role: access to fi nance, interactions with government offi cials, corruption,
and harassment.


Access to Finance
Th e surveys show that access to fi nance varies greatly by formality, but gender
matters as well. Men in the formal sector are far more likely to have a loan than
either men in the informal sector or women in the formal sector (fi gure 6.6).
Indeed, men in the informal sector make up a somewhat larger share (albeit
very low) of fi rms with a loan than women in the formal sector.


Similar patterns pertain for the start-up capital that entrepreneurs had when
launching their business: it is higher in the formal than informal sector, and in
both, higher for men than women (fi gure 6.7).


Figure 6.6 Male Formal Entrepreneurs Are Far More Likely to Have Loans Than Other Groups


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


2


4


6


8


10


12


14


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
cu


rr
en


tl
y


w
it


h
lo


an
s




HOW SORTING AFFECTS CONSTRAINTS 147


Some sources of start-up capital are also correlated with enterprise
productivity (Gajigo and Hallward-Driemeier 2010). Entrepreneurs whose
largest source of start-up capital is commercial banks or friends and relatives
have signifi cantly higher profi tability than those who tapped other sources.
Getting the bulk of one’s start-up capital from friends and relatives has no
gender gradient on productivity, unlike relying on commercial banks. Th is
pattern is consistent with female entrepreneurs being more constrained than
their male counterparts.


Th ese results are consistent with those of studies looking at gender gaps
in access to credit across diff erent sources of fi nance. Fafchamps (2000, 2001)
found that women did not face gaps in getting credit from banks once fi rm
size was taken into account. However, with more informal, relationship-
based lending, women were less likely to receive credit. Fafchamps’s work
on the importance of networks primarily focuses on issues of ethnicity, but
it has important implications for gender too—particularly if women have not
traditionally been part of these networks (see discussion in chapter 8).


Figure 6.7 Male Formal Entrepreneurs Had More Start-Up Capital Than Other Groups


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


0.5


1.0


1.5


2.0


2.5


3.0


3.5


4.0


4.5


0


2


4


6


8


10


12


14


16


Male Female Male Female


Formal Informal


St
ar


ti
ng


n
um


be
r


of
p


ai
d


w
or


ke
rs


(i
nc


lu
di


ng
o


w
ne


r)


M
ed


ia
n


st
ar


t-
up


c
ap


it
al


(U
S$


t
ho


us
an


ds
)


Start-up capital Start-up workforce




148 ENTERPRISING WOMEN


Interactions with Government Offi cials
For the time that management spends dealing with government offi cials, both
formality and gender again appear important (fi gure 6.8). Entrepreneurs in
the  formal sector spend much more time dealing with offi cials than those
in the informal sector—and in both sectors, men spend more time than women.
Th is last diff erence may refl ect the tendency of men’s businesses to be larger
and perhaps need more licenses, or the lesser ability of larger fi rms to ignore
regulatory requirements.


Corruption
One concern with interactions with offi cials is that women may be soft er
targets for bribes than men, or less able to negotiate lower informal payments
to “get things done.”


Information on the frequency of bribes paid shows that formal fi rms
are much more likely to make “gift s” than those in the informal sector
( fi gure  6.9). Th e gender diff erence is small, except that women in the


Male Female Male Female


Formal Informal


0


1


2


3


4


5


6


7


8


Pe
rc


en
ta


ge
o


f m
an


ag
er


’s
t


im
e


sp
en


t
w


it
h


of
fic


ia
ls


Figure 6.8 Formality and Gender Affect the Time Managers Spend with Officials


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.




HOW SORTING AFFECTS CONSTRAINTS 149


informal sector appear less likely to pay than men, and their payments are
lower than men’s.


What is also interesting is that formal entrepreneurs report having a better
sense of the amount of money that is needed “to get things done” (fi gure 6.10)
and greater confi dence that the payment will achieve its aim (fi gure 6.11).


Th e view that informality allows the entrepreneur to remain under the radar
and not subject to harassment from offi cials may be true in some cases. But in
many others the very fact that a business is not registered and may face larger
sanctions is what gives offi cials the ability to demand gift s.


Th e survey also inquired about payments made to other fi rms in the private
sector for “protection” (fi gure 6.12). Like bribes, they are more common in the
formal sector, but payments are larger in the informal sector. Th e gender bias
is attenuated, though women in the formal sector were somewhat less likely to
make such payments.


As with getting things done, the formal sector entrepreneurs again reported
having a better sense of what the payments were likely to be (fi gure 6.13)
and were slightly more confi dent that they would receive the benefi ts of such
payments (fi gure 6.14).


Figure 6.9 Formal Firms Are Much More Likely to Make “Gifts” Than Informal Firms


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


0.5


1.0


1.5


2.0


2.5


3.0


3.5


4.0


0


10


20


30


40


50


60


70


Male Female Male Female


Formal Unofficial


Pe
rc


en
ta


ge
o


f s
al


es
p


ai
d


in


un
of


fic
ia


l p
ay


m
en


ts


Pe
rc


en
ta


ge
o


f fi
rm


s
m


ak
in


g
un


of
fic


ia
l p


ay
m


en
t


Made unofficial payment


Percentage of sales paid
in unofficial payments




150


Figure 6.10 Formal Entrepreneurs Believe They Know How Big Their “Gifts” Should Be


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


10


20


30


40


50


60


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
w


ho
r


ep
or


te
d


kn
ow


in
g


si
ze


o
f e


xp
ec


te
d


pa
ym


en
t


ah
ea


d
of


t
im


e


Figure 6.11 Many Formal Entrepreneurs Believe That Their “Gifts” Will Achieve
Their Purpose


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f
en


tr
ep


re
ne


ur
s


w
ho


p
ai


d
a


“g
ift




Not confident payment will achieve purpose


Sometimes confident payment will achieve purpose


Always confident payment will achieve purpose




151


Figure 6.12 Formal Firms Are More Likely to Pay for Protection Than Informal Firms—but
Pay Less for It


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


0.5


1.0


1.5


2.0


2.5


3.0


3.5


0


20


40


60


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f
an


nu
al


s
al


es
p


ai
d


in


un
of


fic
ia


l p
ro


te
ct


io
n


pa
ym


en
ts




Pe
rc


en
ta


ge
m


ak
in


g
un


of
fic


ia
l


pa
ym


en
ts


f
or


p
ro


te
ct


io
n


Percentage of sales paid
in unofficial payments


Made unofficial payment


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


Figure 6.13 Formal Entrepreneurs Believe They Know How Big Their Payments for Protection
Should Be


0


5


10


15


20


25


30


35


40


45


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
w


ho
r


ep
or


te
d


kn
ow


in
g


co
rr


ec
t


pa
ym


en
t


ah
ea


d
of


t
im


e




152 ENTERPRISING WOMEN


Harassment
Some challenges for female entrepreneurs may vary only in degree from men’s,
but some are diff erent in kind. One of the concerns raised by women in a
series of focus groups held with entrepreneurs from 15 countries was that the
“gift s” sought were not always monetary. When asked whether they knew of
cases where sexual favors had been asked for, the majority replied “yes” (with
almost equal shares reporting they heard of such harassment “occasionally” and
“ frequently”) (fi gure 6.15). Formal sector entrepreneurs, male and female, were
more likely to report having heard of such activities. Th e transactions most
susceptible to harassment varied: borrowing money and dealing with suppliers
were deemed more susceptible, dealing with government offi cials (inspectors
or those granting licenses) marginally less so.


What is particularly troubling is that women also fear harassment from those
who should be protecting them. In discussions with several women’s groups
in preparing this work, we heard repeatedly about women’s inability to go to
a police station for fear of encountering further harassment. Th is fear makes it
very diffi cult for women to have their complaints investigated by the authorities,


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


Figure 6.14 Many Formal Entrepreneurs Believe That Their Payments for Protection Will
Achieve Their Purpose


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f
en


tr
ep


re
ne


ur
s


w
ho


m
ad


e
a


pr
ot


ec
ti


on
p


ay
m


en
t


Not confident payment will achieve purpose


Sometimes confident payment will achieve purpose


Always confident payment will achieve purpose




HOW SORTING AFFECTS CONSTRAINTS 153


let alone have much confi dence that the formal system would provide assistance
or enforce their rights if property was stolen or disputes arose in the course of
running their businesses.


Clearly this is not to say that sexual harassment is something all women
face—nor are women’s successes to be attributed to their providing sexual
favors. Th at many have heard of harassment may refl ect a few examples that
were widely discussed in the media or among the respondents. But concerns
about potential sexual harassment need to be addressed in their own right—and
harassment could have additional indirect costs too. It could keep women from
undertaking certain economic activities that would otherwise be viable.


Th us, overall, women may face some constraints as women—and these need to
be addressed. However, for most issues, the type of enterprise rather than the
gender of the entrepreneur determines which constraints matter relatively more.


Notes
1. A similar fi nding, that gender becomes insignifi cant once fi rm size is controlled


for, is found for access to fi nance in the analysis of access to banking credit in
Fafchamps (2000). However, it does not hold for access to trade fi nance, where
gender (and  ethnic) ties remain important predictors of who receives trade credit.


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for new entrepreneurs in Côte d’Ivoire, Kenya, Nigeria, and Senegal. Figure indicates percentages
of entrepreneurs who indicated they had “sometimes” or “frequently” heard of sexual favors being asked for.


Figure 6.15 When Women Borrow Money or Engage in Other Business Transactions,
They May Be Asked for Sexual Favors


0


10


20


30


40


50


60


70


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f
en


tr
ep


re
ne


ur
s


Had heard of lenders requesting favors
Had heard of suppliers requesting favors


Had heard of inspectors requesting favors
Had heard of licensors requesting favors




154 ENTERPRISING WOMEN


2. Similarly, the surveys do not capture those enterprises that exited. Panel surveys
can capture the conditions enterprises faced prior to exit, although they may fail
to capture shocks or deteriorating conditions that pushed the enterprise into going
out of business. Frazer (2005) and Harding, Söderbom, and Teal (2006) did fi nd
reported constraints were oft en higher for fi rms that subsequently exited.


References
Armendariz, B., and N. Roome. 2008. “Gender Empowerment in Microfi nance.”


Working paper, Department of Economics, Harvard University, Cambridge, MA.
Ashraf, N. 2009. “Spousal Control and Intra-household Decision Making:


An  Experimental Study in the Philippines.” American Economic Review 99
(4): 1245–77.


Aterido, R., and M. Hallward-Driemeier. 2010. “Th e Impact of the Investment Climate
on Employment Growth: Does Sub-Saharan Africa Mirror Other Low-Income
Regions?” Policy Research Working Paper 5218, World Bank, Washington, DC.


Aterido, R., M. Hallward-Driemeier, and C. Pages. 2011. “Big Constraints to Small Firms’
Growth? Business Environment and Employment Growth across Firms.” Economic
Development and Cultural Change 59 (3): 609–47.


Banerjee, A., E. Dufl o, R. Glennerster, and C. Kinnan. 2009. “Th e Miracle of Micro-
fi nance? Evidence from a Randomized Evaluation.” Working paper, Massachusetts
Institute of Technology, Cambridge, MA.


Bardasi, E., M. Blackden, and J. C. Guzman. 2007. “Gender, Entrepreneurship, and
Competitiveness.” In Africa Competitiveness Report 2007, edited by World Economic
Forum, African Development Bank, and World Bank, 69–86. Geneva: World
Economic Forum, African Development Bank, and World Bank.


Batra, G., D. Kaufmann, and A. Stone. 2003. Investment Climate around the World: Voices
of the Firms from the World Environment Survey. Washington, DC: World Bank.


Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. Gunning, A. Oduro,
R. Oostendorp, C. Pattillo, M. Söderbom, F. Teal, and A. Zeufack. 2003. “Credit
Constraints in Manufacturing Enterprises in Africa.” Journal of African Economies
12 (1): 104–25.


Bruhn, M., and I. Love. 2011. “Gender Diff erences in the Impact of Banking Services:
Evidence from Mexico.” Small Business Economics 37 (4): 493–512.


Dollar, D., M. Hallward-Driemeier, and T. Mengistae. 2005. “Investment Climate and
Firm Performance in Developing Economies.” Economic Development and Cultural
Change 54 (1): 1–31.


Fafchamps, M. 2000. “Ethnicity and Credit in African Manufacturing.” Journal of
Development Economics 61 (1): 205–35.


_____. 2001.“Networks, Communities, and Markets in Sub-Saharan Africa: Implications
for Firm Growth and Investment.” Journal of African Economies 10 (Suppl. 2): 109–42.


Fafchamps, M., and A. R. Quisumbing. 2002. “Control and Ownership of Assets within
Rural Ethiopian Households.” Journal of Development Studies 38 (2): 47–82.


Frazer, G. 2005. “Which Firms Die? A Look at Exit from Manufacturing in Ghana.”
Economic Development and Cultural Change 53 (3): 585–617.




HOW SORTING AFFECTS CONSTRAINTS 155


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Harding, A., M. Söderbom, and F. Teal 2006.“Th e Determinants of Survival among
African Manufacturing Firms.” Economic Development and Cultural Change
54 (3): 533–56.


Kabeer, N. 2001. “Confl icts over Credit: Re-Evaluating the Empowerment Potential of
Loans to Women in Rural Bangladesh.” World Development 29 (1): 63–84.


Kantor, P. 2005. “Determinants of Women’s Microenterprise Success in Ahmadabad,
India: Empowerment and Economics.” Feminist Economics 11 (3): 63–83.


Klapper, L., and S. Parker. 2010. “Gender and the Business Environment for New Firm
Creation.” World Bank Research Observer 26 (2): 237–57.


McCormick, D., M. N. Kinyanjui, and G. Ongile. 1997. “Growth and Barriers to Growth
among Nairobi’s Small and Medium-Sized Garment Producers.” World Development
25 (7): 1095–110.


McKenzie, D., and Y. S. Sakho. 2010. “Does It Pay Firms to Register for Taxes? Th e Impact
of Formality on Firm Profi tability.” Journal of Development Economics 91: 15–25.


McKenzie, D., and C. Woodruff . 2006. “Do Entry Costs Provide an Empirical Basis
for Poverty Traps? Evidence from Mexican Microenterprises.” Economic Development
and Cultural Change 55: 3–42.


Ramachandran, V., A. Gelb, and M. K. Shah. 2009. Africa’s Private Sector: What’s Wrong
with the Business Environment and What to Do About It. Washington, DC: Center for
Global Development.


World Bank. 2004. World Development Report 2005: A Better Investment Climate for
Everyone. Washington, DC: World Bank.






Part IV


Shifting Women to
More Productive Work
Where individuals work shapes their opportunities. Th us the agenda
moving forward is to address the factors that account for gender
sorting across types of entrepreneurial activities. Four issues are
highlighted: strengthening the economic right to own and control
assets, increasing access to fi nance, improving access to education
and business skills, and strengthening women’s voice in the reform
process. Part IV draws on examples of the impact of reforms and
explores variations across countries to show the importance of this
agenda in expanding economic opportunities for women in Africa.






159


Chapter 7


Increasing the Right to Own and
Control Assets


Can you reap the rewards of your investments of time and resources? Are you
restricted in your legal ability to make decisions that aff ect your economic
activities? Th ese are central questions for people in business everywhere, and
both relate to property rights and the ability to make economic decisions in
one’s own name.1 Th e strength of these rights determines the incentives to invest
and put time and energy into a business venture. It also determines the ability
to control collateral to obtain credit, and the types of risks that will be taken.


Th is chapter provides evidence confi rming earlier research (see box 7.1) that
a woman’s ability to engage in economic activity is aff ected by what property
and economic rights she enjoys and what legal capacity she possesses. Th e new
database of indicators relating to women’s formal property rights and legal
capacity, Women–LEED–Africa, shows the extent of discriminatory family,
marital property, and inheritance laws. Along with legal restrictions on women’s
mobility, employment outside the home, and administration of personal assets,
those laws present barriers to women’s economic opportunity.2


Th e chapter will describe the three main fi ndings of Women–LEED–Africa,
summarized briefl y here. First, all 47 Sub-Saharan African countries recog-
nize the principle of nondiscrimination in their constitutions or in treaties—
but allow many legal exceptions. Second, the treatment of women’s economic
rights is not closely related to a country’s level of income or development,
so active measures are needed to close gender gaps in these rights; closing
income gaps is not suffi cient. (Th ese measures can work, as the case of Ethiopia
shows; see box 3.1 and Hallward-Driemeier and Gajigo 2011). Th ird, many
discriminatory provisions that women face apply not to women as women, but
to women as married women. Marital status, and the capacities and limitations
associated with it, determine women’s eff ective property rights and economic
autonomy, in ways oft en markedly diff erent from men’s.


Th e customary and social norms from which many laws derive are deep
challenges to reform, because customary law is extremely important both as a




160 ENTERPRISING WOMEN


BOX 7 .1


Earlier Research on the Impact of Property Rights on
Economic Opportunities
An extensive literature shows the importance of property rights for growth, investment,
and government effectiveness.a Aggregate cross-country data show a positive asso-
ciation between growth and the quality of institutions or property rights, though the
exact causal mechanism can be hard to establish.b


Much recent literature focuses on microeconomic analyses, generally within a single
country that has changed legal rights or that grants different rights to different groups.
This box highlights examples of such changes to property rights or family law.


Strong Land Rights Can Promote Investment
Empirical work suggests that a greater share of resources controlled by women
promotes agricultural productivity (Besley and Ghatak 2009; Quisumbing 1996; Saito,
Mekonnen, and Spurling 1994; Udry and others 1995) and helps reduce poverty
(World Bank 2001). Insecure property rights to land have multiple ramifi cations for
agriculture and for how rural economic activity is organized. For one, the risk that land
will be expropriated deters investment. Insecure property rights also reduce borrowers’
ability to pledge land as collateral, and thus tighten credit constraints. Finally, ill-defi ned
property rights to land can inhibit land transactions—rentals or sales—thereby costing
owners the potential gains from trade (Aryeetey and Udry 2010).


Udry and Goldstein (2008) examine the effect of contested land rights on
investment and productivity in agriculture in Akwapim, Ghana. They show that individ-
uals who hold powerful positions in a local political hierarchy have more-secure tenure
rights, and therefore invest more in land fertility, leading to much higher output. The
intensity of investments on different plots cultivated by a given individual corresponds
to that individual’s security of tenure over those specifi c plots.


Besley (1995), also in Ghana, shows that individuals vary their investment across
plots depending on the security of their rights—and that property rights need to be
understood as embedded in a broader social context.


Many countries have formal titling programs. Some evaluations have shown an
associated increase in agricultural productivity and a (weak) increase in access to credit
(for example, Pande and Udry [2005]). The weak increase in access to credit has been
attributed to two factors. First, creditors often have only weak rights to foreclose on
land (Field and Torero 2008). Second, collateral is not the only constraint to accessing
fi nance: a profi table idea and the ability to work in a reasonably hospitable investment
climate are also needed (Besley and Ghatak 2009).


One of the challenges for women is that titling has too often been done under a
single name, that of the male head of household.


Strong Land Rights Can Increase Labor Supply
Field (2007) evaluates the impact of a titling program in the slums of Peru. She fi nds
little impact of a title on decisions to invest in the home or plot of land, but does fi nd




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 161


formal source of law and as informal practice. It touches the lives of the majority
of the population in much of Africa.


Moreover, the diversity of legal systems and sources of law complicates the
task of determining women’s legal status and eff ective rights, and adds to uncer-
tainty in the business environment. Family law, seldom addressed in programs to
improve the business environment, shapes the business environment for women.


Such diversity is mirrored by a corresponding diversity in case law and
interpretations, examined in greater detail in the companion report (Hallward-
Driemeier and Hasan 2012). Even where women’s rights are enshrined in
law, contradictions among formal sources of law undermine the equality of
these rights for women, and the gulf is oft en wide between paper and prac-
tice. Contradictory provisions within laws, and a high degree of variability in
the interpretations given to these laws, especially concerning marital property,
circumscribe women’s legal rights and act as a brake on their ability to seize
economic opportunities.


an impact on labor supply, particularly for women. The title freed members of the
household from having to remain on the plot to ensure a claim over it.


Changes in Inheritance Laws Alter the Incentive of Families to Invest in
Daughters
Deininger, Goyal, and Nagarajan (2010) analyze the effect in some southern states of
changes to the Hindu Succession Act, which gave equal rights to females in inheriting
property. The effect of the new law was to raise the likelihood of women inheriting
land (without fully eliminating the gender difference), increase the age at marriage
for girls, raise their educational attainment, and increase household investments in
daughters. Roy (2008) found that the law increased women’s autonomy.


Changes in Family Law Can Strengthen Women’s Economic Empowerment
As family law determines issues of legal capacity or who controls assets in the family,
changes in legislation can affect economic opportunities. Part of the effect may come
from shifts in intrahousehold bargaining power, as illustrated by Stevenson and Wolfers
(2006) and Gray (1997), who looked at the changes in divorce laws in the United
States. For an account of progress in Ethiopia, see box 3.1.


Source: Hallward-Driemeier and Hasan 2012.


a. Pande and Udry (2005) provide a review of the literature, focusing on microeconomic analyses. Besley


and Ghatak (2009) provide a synthesizing theoretical framework of the relationship of property rights


and economic outcomes (particularly investment), and also discuss the existing evidence on the impor-


tance of property rights.


b. See, for example, Acemoglu and Johnson (2005); Acemoglu, Johnson, and Robinson (2001); Glaeser


and others (2004); Johnson, McMillan, and Woodruff (2002); Rodrik, Subramanian, and Trebbi (2004).




162 ENTERPRISING WOMEN


Th e chapter ends with recommendations for improving the substance of
laws, strengthening the process of the formal and informal legal systems, and
strengthening the administration of laws and access to justice. Where possible,
the formal and informal sectors should be linked, so that decision makers can
be cognizant of their impact on peoples’ daily lives—with the goal of identify-
ing strategies to improve the economic rights of women within their sphere of
infl uence.


Regulations, Formal Law, and Practice


Regulations on business stipulate the procedures for registering property and
businesses, enforcing contracts, and safeguarding investor and creditor rights.
Th ey rarely have gender-diff erentiated provisions. Almost all, with the exception
of some labor laws (discussed below), are gender blind. (Th e few areas where
they treat men and women diff erently are usually specifi c situations, such as
pregnancy or night work.) Th e impact in practice, of course, may not be gender
neutral if women face greater time constraints, have more-limited mobility, or
face cultural restrictions on the transactions they can engage in—or if offi cials
see them as soft er targets for harassment. Gender-blind regulations also pre-
suppose that the parties can enter contracts, have freedom of movement and
access to economic exchange, and can own property or control assets in their
own name. Th is is not always the case for women, so gender-blind regulations
do not guarantee gender equality in economic rights.


Other areas of the law, rarely addressed in analyses of the business
environment, play a determining role in framing these rights—notably family
law for marriage, divorce, and inheritance, as well as laws for land rights and
labor markets. Th ese laws, more than business regulations, determine whether
women and men can make economic decisions in their own name, or whether
there are restrictions on their ability to enter contracts or to own, administer,
transfer, or inherit assets and property. It is in these areas that gender diff erences,
including outright discrimination, are most apparent.


Two other factors are important. First is the frequency with which laws within
a country are subject to overlapping legal systems, such as when constitutions
and statutes explicitly recognize marriage, inheritance, and property as domains
where formal customary or personal law applies. Second is the tendency to
grant these domains formal exemption from nondiscrimination provisions.3


Formal law defi nes formal economic rights, articulated in international law,
in constitutions, and in specifi c statutes. Th e formal rules refl ect what should
happen if the legal system functions well, and they thus are worth examining
for their incentives and protections. Th e strength of de jure rights provides a
measure of the potential to use the law to address discriminatory practices.




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 163


If formal laws do not provide safeguards against discrimination, that closes a
critical avenue for redress.


But the strength of formal economic rights is determined not only by
the content of formal laws but also by how eff ectively the formal legal sys-
tem safeguards these rights. Ambiguity in defi ning or enforcing any of these
rights, coupled with multiple sources of law and legal systems in many African
countries, limits the use of property, raises transaction costs, and increases
uncertainty and unpredictability in exercising economic rights.


Practical constraints—including distance, cost, and language—can further
shape people’s ability to exercise formal economic rights, with important
gender-diff erentiated eff ects. So, the de jure indicators in the next few sections
do not fully refl ect de facto, or actual, practices. Nor do many people engage
with the formal legal system, or have much knowledge of the protections it
aff ords. Particularly in areas with low incomes, low education, and strong
customary traditions, as well as in areas that are more rural, people rarely turn
to the formal system to secure economic rights. Th ey turn instead to local elders
or chiefs and follow customary practices.


Constitutional and statutory provisions do not treat women as a homoge-
neous group. Some treat men and women diff erently, based purely on gender.
Others recognize a gender diff erence on marriage, and women’s legal capac-
ity and the strength of their property rights most oft en weaken then. Any
assessment of the equality of de jure economic rights must therefore consider
both gender and marital status.


Th e law is not of course the only factor that infl uences a person’s decision
to become an entrepreneur or that aff ects an enterprise’s performance. Many
other factors—including individuals’ skills as well as their access to assets, tech-
nology, and infrastructure—also matter. Men and women can have diff erent
preferences for how they spend their time, and diff erent interests and abilities
in their economic activities. Changing the laws to ensure equality of economic
rights for women and men will likely be insuffi cient to bring about equality of
participation and performance for women and men. But unequal legal protec-
tion will make achieving such a goal all but impossible.


Focus of Women–LEED–Africa


Th e fi rst step in assessing women’s legal rights is to look at the rights on the
books according to offi cial sources of law in each country, and to determine
how these (de jure) rights diff er from men’s. Th e Women–LEED–Africa data-
base gives the dimensions for which diff erential treatment between women and
men is legally allowed in diff erent countries. Th e subject coverage is not exhaus-
tive; the focus is on areas that have fi rst-order eff ects on existing and potential




164 ENTERPRISING WOMEN


businesspeople: legal capacity, property rights (land and assets), and restrictions
in labor laws.


Th e database covers the fi ve sources of law:


• International treaties and conventions on women’s rights. Th ey provide legal
protections that are binding on their signatories. Th eir direct application
domestically can vary by monist or dualist state system (they are directly
applicable in the former, but need to be incorporated into domestic laws in
the latter).


• Constitutions. Th ey are the highest source of law in a country and lay out
the guiding principles for legal rights. Th e focus is on provisions for nondis-
crimination on the basis of sex and, as appropriate, for explicitly promoting
gender equality.


• Statutes. Family and civil codes, marital property laws, land laws, and labor
laws—rather than generic business regulations—determine who has legal
capacity, who can own property, and what the restrictions are on equal labor
opportunities.


• Customary law. Many African countries’ constitutions or statutes (or both)
recognize customary law as a separate—oft en equal—source. Some coun-
tries recognize only certain areas of customary law. Th e interest here is in its
applicability to legal capacity, property, and inheritance.


• Religious law. Many regional countries recognize religious law as a separate—
oft en equal—source. Some recognize it as the primary source of law, others
as the applicable source of law for members of a particular religion or for
certain issues (or both). Again, the interest is in its applicability to issues of
legal capacity, property, and inheritance.


Using seven indicators of where women’s economic and legal rights diff er from
men’s, Women–LEED–Africa looks at each of these fi ve sources of law in all 47
Sub-Saharan African countries. Th e database does not try to assess how exten-
sive the male-female diff erences are; it categorizes countries as “yes” or “no” on
each indicator. (Th e country indicators are listed in appendix C.)


Th e fi rst three indicators measure the recognition of diff erent sources of law
that could aff ect the protection of nondiscrimination on the basis of gender:


• International agreements and conventions. At issue is the status of sig-
nature/ratifi cation of the Convention on the Elimination of All Forms of
Discrimination against Women; the Protocol to the African Charter of
Human and Peoples’ Rights on the Rights of Women in Africa; and key
International Labour Organization (ILO) Conventions, notably Convention
100 on equal remuneration for men and women workers for work of equal
value, Convention 111 on equality of opportunity and treatment in respect




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 165


of employment and occupation, and Conventions 171 and 183 on the labor
rights of women with respect to night work and the labor rights of women
who are pregnant or breastfeeding.


• Nondiscrimination provisions. At issue are protections for nondiscrimination
on the basis of gender and for gender equality within constitutions. Specifi c
provisions addressed include recognition of nondiscrimination on the basis
of sex, provisions explicitly promoting gender equality, guarantees of prop-
erty ownership, guarantees of women’s property ownership, and equal rights
to work and to equal pay.


• Recognition of customary and/or religious law. At issue is whether countries
recognize customary and/or religious law, whether this recognition stems
from provisions within the constitution or statutes, and whether customary
and/or religious law is explicitly exempt from constitutional provisions for
gender nondiscrimination.


Th e four remaining indicators measure topical issues, showing where the eco-
nomic rights of men and women diff er:


• Legal capacity. Th is mainly involves “head-of-household” laws, which give
husbands power to choose the marital domicile, or which require the hus-
band’s permission for the wife to enter a trade or profession, to work outside
the home, to enter into contracts, or to open a bank account.


• Property rights related to marriage and inheritance. Th ese concern the pro-
visions of diff erent marital property regimes, including within marriage,
and on divorce or death of the spouse, including treatment of nonmonetary
contributions.


• Land laws. Th e focus is on key provisions relating to the protection of
women’s land rights in land laws, statutory recognition of customary law
on land ownership and inheritance, exemption of customary ownership
from statutory succession laws, and availability of co-ownership options in
marriage for women.


• Labor laws. Th e focus is on statutory provisions relating to equal pay for equal
work, restrictions of women’s work (sectors or hours worked), application to
pregnant women, and maternity leave (duration and funding).


Th ese indicators largely relate to statutes, but also record customary or religious
laws when they are recognized as the prevailing source of law.


Database compilation benefi ted from several concurrent initiatives, includ-
ing the Gender Law Library of the World Bank and its accompanying publica-
tion Women, Business, and the Law (World Bank 2010; see appendix C), and the
work by the International Finance Corporation’s Women in Business Program
(Simavi, Manuel, and Blackden 2010).




166 ENTERPRISING WOMEN


Main Findings from Women–LEED–Africa


Th ree key messages emerge from the database. First, all 47 Sub-Saharan
countries recognize the principle of nondiscrimination—in their constitutions
or in treaties (or both). Many countries, however, grant various legal exceptions
to nondiscrimination, including many in the constitution itself. A common
exception is the recognition of customary law, which oft en is not bound to
respect nondiscrimination as a principle. Moreover, the multiplicity of sources
of law adds uncertainty to defi ning women’s economic rights: despite recogniz-
ing nondiscrimination as a guiding principle of law, many countries’ statutes
discriminate.


Second, the treatment of women’s economic rights is not closely related to
a country’s level of income or development. One implication is that simply
raising national income is not likely to be suffi cient to improve women’s
legal and economic rights; to meet this goal more active reforms will likely
be needed. Some countries have expanded overall income even with gaps
in women’s economic rights—while others, with strong protections for
nondiscrimination, have not. Th e legal framework is not the only factor, but
the strength of legal protections aff ects women’s economic opportunities,
particularly their ability to run and expand larger enterprises and to move out
of self-employment. Th e share of women entrepreneurs who are employers
is signifi cantly higher where women’s economic rights are stronger—across
the income spectrum.


Th ird, many of the discriminatory provisions apply not to women as women,
but to women as married women. From a legal standpoint, marriage changes
the legal status and rights of women, sometimes radically, oft en conferring legal
capacities and responsibilities on husbands, and removing them from wives.
As discussed below, this type of change applies particularly to property regimes,
to rights in and aft er marriage, and to rules aff ecting women’s economic capacity
and decision making within marriage.


Nondiscrimination
Th e principle of nondiscrimination is recognized in all Sub-Saharan countries,
either in constitutions or in the international conventions to which countries
are signatories (fi gures 7.1 and 7.2).


Th e constitutional recognition of customary law is pervasive—it applies
in all common law countries and in almost half the civil law countries.
Where customary law is not recognized in constitutions, this recognition
is implicitly provided in statutes, particularly those for marriage or inheri-
tance. What varies across countries is the extent to which constraints are
placed on customary law in upholding the principle of nondiscrimination
(fi gure 7.3).




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 167


Figure 7.1 All Sub-Saharan Constitutions Enshrine the Principle of Nondiscrimination, and
Most Enshrine Gender Equality


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


0


20


40


60


80


100


Low-income
countries


Middle-income
countries


Middle-income
countries


Low-income
countries


Recognizes nondiscrimination Has specific provision for
gender equality


Pe
rc


en
ta


ge
o


f c
on


st
it


ut
io


ns
in



Su


b-
Sa


ha
ra


n
A


fr
ic


a


NoYes


Figure 7.2 Almost All Sub-Saharan Countries Are Signatories to at Least Some International
Conventions on Nondiscrimination


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.
Note: CEDAW = Convention on the Elimination of All Forms of Discrimination against Women; ILO =  International
Labour Organization.


0


25


50


75


100


CE
DA


W


Af
ric


a w
om


en
's


rig
hts


pr
oto


co
l


ILO
co


nv
en


tio
n


10
0 (


eq
ua


l p
ay


)


ILO
co


nv
en


tio
n 1


11


(no
nd


isc
rim


ina
tio


n


in
em


plo
ym


en
t)


ILO
co


nv
en


tio
n 1


71


(ni
gh


t w
ork


)


ILO
co


nv
en


tio
n 1


81


(m
ate


rni
ty


pro
tec


tio
ns


)


Pe
rc


en
ta


ge
o


f S
ub


-S
ah


ar
an



co


un
tr


ie
s


Did not ratifyRatified




168 ENTERPRISING WOMEN


Income
Restrictions on women’s legal capacity do not diff er much by country income,
but they are found largely in civil law countries, where various laws stipulating
the man as “head of household” apply. (Th e two common law countries that
restrict women’s legal capacity are Sudan and Swaziland.) While one indicator
measures the countries that have a “head-of-household” provision, its implica-
tions can mislead—for two reasons. First, some countries without such a provi-
sion still have statutes that provide for the same powers of husbands over their
wives. Second, some countries deem the man as head of household to be a social
distinction, and they have explicit provisions indicating that husbands do not
have power over the economic decisions of their wives. In short, a “head-of-
household” provision is not an infallible indicator of who makes the economic
decisions.


Husbands have power over their wives’ economic activities in three main
ways. Th e right of the husband to choose the matrimonial home is the most
common, followed by his ability to deny his wife permission to pursue a job
or profession. Th e need to get his signature to open a bank account is less


Figure 7.3 The Constraints Placed on Customary Law in Upholding Nondiscrimination
Vary across Countries


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


0


10


20


30


40


50


60


70


80


90


100


Low-income countries Middle-income countries


Pe
rc


en
ta


ge
o


f S
ub


-S
ah


ar
an


c
ou


nt
ri


es


Constitution does not recognize customary law


Constitution recognizes customary law—and
exempts it from nondiscrimination requirements


Constitution recognizes customary law—and
limits its ability to discriminate based on gender




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 169


common, at least in laws governing marriage (though many countries allow
banks to require this as part of their business practice) (fi gure 7.4).


Property Regime for Marriage
Th e type of property regime in marriage determines the ability of both
spouses to own property during marriage and aft er its dissolution through
death or divorce. Th ese property rights in turn determine spouses’ access
to and control of assets and other productive resources that can be used
as collateral for loans or for other business purposes. Statutory, customary,
and religious marriages are subject to various property regimes. Th e most
common are community of property (including universal community of
property), separate ownership of property, dowry, and customary law. Th e
default marital regime that applies is regulated by the relevant family statute
or code, which in turn depends on the type of marriage contract that the
parties enter.


Th e community of property regime off ers women a better chance of
maintain ing their property rights on dissolution of marriage than separate
ownership regimes, because it entitles them to a portion of the property, gener-
ally half, without having to make proof of contribution. Not having to prove
contribu tion is vital, because millions of women in Africa contribute to mari-
tal property through nonmonetized activities, such as performing household
chores and working in subsistence agriculture.


Figure 7.4 Head-of-Household Rules Provide Several Ways Husbands Can Control Their
Wife’s Assets


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


0


25


50


75


100


Low-
income
country


Pe
rc


en
ta


ge
o


f
Su


b-
Sa


ha
ra


n
co


un
tr


ie
s


Middle-
income
country


Low-
income
country


Middle-
income
country


Low-
income
country


Middle-
income
country


Low-
income
country


Middle-
income
country


Man is head of
household


Husband chooses
matrimonial home


Husband’s
permission


needed to open
bank account


Husband can
oppose wife's


exercise of
trade or profession


Statutes were not found Law affirmsNo such law




170 ENTERPRISING WOMEN


Even when community of property is the default regime, it may not always
apply, particularly in polygamous marriages, where the default is separate own-
ership. Separate property in a polygamous marriage protects a wife from hav-
ing her property divided among other wives, but it also limits a wife’s access to
assets acquired during marriage.


Th e nature of the marital property regime is important as it determines mar-
ried women’s control over assets that can be used as collateral in applying for a
loan or used in a business, as well as their incentive to accumulate additional
assets or expand a business. Th e share of assets a woman is entitled to when a
marriage ends can be critical in determining whether she can run a business
and if so what type of business.


Inheritance Regime
Inheritance remains one of the main ways for women to acquire and control
property (fi gure 7.5) and one of the main areas where women fi nd themselves
involved in property disputes. Th e legal framework for succession laws in Sub-
Saharan Africa falls under constitutions as well as family, customary, and reli-
gious laws. Judicial precedence also plays a large role. All these factors aff ect
whether women, married and unmarried, can own and control property and
thus have the ability to use such assets in their business. Figure 7.5 focuses on
inheritance of marital property on the death of the husband intestate.4 Under
a separate property regime, married women do not automatically inherit from
their husband’s estate. Some countries provide for some inheritance, but the
share is usually far less than half.


Land
Land is central to getting fi nance, especially in Africa’s collateral-based
banking systems, and is a key resource for enterprise development.
Land  issues bring to the fore many of the problems associated with mul-
tiple legal systems, specifi cally involving customary law and practices for
land ownership and access rights as well as deep-rooted gender biases
(Quisumbing and others 2001). Some land laws are gender neutral, some
explicitly favor men, and others recognize the rights of women to own land
(fi gure 7.6).


Gender diff erences in access to and control over land remain a key prob-
lem in Sub-Saharan Africa. Th e avenues available to women in access to land
include purchase, allocation in case of customary land tenure, inheritance,
and distribution in the event of divorce. Th e challenges arising in inheritance
and divorce have been examined extensively elsewhere.5 Many studies have
shown clearly that women’s rights over land are inferior to those of men.
For example, while the majority of males reported unfettered rights to give
land to family members, fewer than 5 percent of women could do so across




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 171


sites in Burundi, Uganda, and Zambia (Place 1995). Th ere are, however, a
few exceptions, such as in cocoa-growing areas of Ghana, where women are
granted rights to land and trees through gift s. Yet women are rarely allowed
to inherit land, even in matrilineal systems. As for acquisition of short-
duration rights to land through renting or sharecropping, women appear to
fare better.


Intestate succession laws in several countries, including Ghana and Zambia,
exclude customary or lineage land from property that a wife can inherit on the
death of her husband. Instead, the land follows customary rules of inheritance,
usually going to a male heir. Customary land comprises 72 percent of all land
in Malawi, 80 percent in Mozambique, 60 percent in Swaziland, and 81 percent
in Zambia (UNECA 2003), so this rule is a major impediment to women’s land
rights.


Figure 7.5 Inheritance Is One of the Main Ways Women Can Acquire and Control Property—
But Such Rights Vary


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.
Note: Data are for wife’s right to inherit matrimonial property if husband dies intestate under three property
regimes (community, separate, and customary).


0


Recogniton of wife’s
portion of joint


property


Entitlement of the wife
to a share of matrimonial


property


Statutory recognition of
customary law in property


inheritance
(eg., in succession acts)


5


10


15


20


25


Co
mm


un
ity


Se
pa


rat
e


Cu
sto


ma
ry


Co
mm


un
ity


Se
pa


rat
e


Cu
sto


ma
ry


Co
mm


un
ity


Se
pa


rat
e


Cu
sto


ma
ry


N
um


be
r


of
S


ub
-S


ah
ar


an
c


ou
nt


ri
es


Legislation was not found Excluded by property regime Included in property regime




172 ENTERPRISING WOMEN


Labor
Legal safeguards for women’s labor rights in Sub-Saharan Africa are in the
ILO conventions that countries sign and in the constitutions and labor laws of
countries. Because men’s and women’s economic activities outside agriculture
are mainly as self-employed entrepreneurs, as employers, or as wage earners,
their options are aff ected by laws, regulations, and practices governing labor
and employment. Th us while labor laws directly aff ect employees, they can also
aff ect entrepreneurs by raising or lowering the availability and attractiveness
of wage employment. Constitutions in 30 countries in the region go beyond a
general clause on nondiscrimination to provide equal rights to work or equal
pay (or both). Eff ectively implementing the principle of nondiscrimination is
critical in enforcing labor rights for women to ensure equal pay for equal work.


Figure 7.6 Not All Land Laws Recognize Women’s Right to Own Land


Source: M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


0


25


50


75


100
Pe


rc
en


ta
ge


o
f S


ub
-S


ah
ar


an


co
un


tr
ie


s


Lo
w


-in
co


m
e


co
un


tr
ie


s


M
id


dl
e-


in
co


m
e


co
un


tr
ie


s


Lo
w


-in
co


m
e


co
un


tr
ie


s


M
id


dl
e-


in
co


m
e


co
un


tr
ie


s


Lo
w


-in
co


m
e


co
un


tr
ie


s


M
id


dl
e-


in
co


m
e


co
un


tr
ie


s


Lo
w


-in
co


m
e


co
un


tr
ie


s


M
id


dl
e-


in
co


m
e


co
un


tr
ie


s


Protection
of


land
rights for
women


Statutory
recognition of


customary
law applying


to land
ownerhship


and/or
distribution


Entitlement of
women to


co-ownership
of property
based on
marriage


Customary
land is
exempt


from
succession


laws


Land legislation was not found
Not included in land rights


Included in land rights




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 173


Restrictions on women’s labor hours, or on the nature of the work they may
undertake, still apply in many countries. Women’s ability to participate fully in
the labor force, unlike men’s, is therefore constrained, limiting access to some
opportunities.


Some restrictions apply to all women, some only to pregnant women,
ostensibly aimed at protecting them. Fift een countries restrict the nature
of the work any woman may engage in, and 20 more apply such restric-
tions only to pregnant women (fi gure 7.7). Twenty-three countries restrict
the hours that any woman may work, and a further 12 restrict only preg-
nant women. Th ese restrictions, combined with other limitations resulting
from head-of-household provisions, are a severe obstacle to women becom-
ing wage earners. Th ey may be contributing to the tendency of women who
are not agricultural workers to be self-employed in informal and small
enterprises.


Figure 7.7 Restrictions on Women’s Hours and Type of Work Vary


Source: Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and E. Lobti, Women’s Legal and Economic
Empowerment Database.


0


25


50


75


100


Low-income
countries


Middle-income
countries


Low-income
countries


Middle-income
countries


Restrictions on nature
of work


Restrictions on hours


No restrictions


Not found in labor laws


Laws apply only to pregnant women


Laws apply to all women


Pe
rc


en
ta


ge
o


f S
ub


-S
ah


ar
an


c
ou


nt
ri


es




174 ENTERPRISING WOMEN


Gaps between Principle and Practice


According to the Women–LEED–Africa database, governments have made much
progress in enshrining rights for women in law, even if, in some critical areas, such
rights still remain precarious or poorly defi ned. Th e gap between what is in law in
principle and what can be realized in practice is, however, very wide.


Formal legal pluralism limits women’s economic rights in three main ways.
First, the very existence of customary law exemplifi es the multiple systems
and sources of law, and raises questions about which systems prevail in which
circumstances. Second, legal systems have confl icting, sometimes contradictory,
provisions for where women’s property rights are addressed—inconsistently—
across diff erent areas of law and through diff erent legal instruments. Th ird,
customary law has discriminatory provisions that are allowed under statutory
law.


But other factors keep the principle-practice gap wide as well. Barriers
in administrative law include physical access to the justice system (distance
to courts and legal services, and costs in time and money); gender-based
diff erences in representation in the justice system; complex legal proceedings
(including language and procedures); cultural obstacles in the way communities
address disputes; hierarchies of legal systems, where formal/statutory and infor-
mal/customary legal systems coexist, raising questions of jurisdiction (which
system prevails?); and “forum shopping” by those with the power and resources
to obtain the most favorable results.


Customary law also presents women with multiple constraints in access-
ing justice. Even though it may be physically and culturally more accessible,
women’s experience within customary institutions can diff er signifi cantly
from men’s. Most of the customary courts are adjudicated by men and tend to
favor men in their decisions. Women are traditionally excluded from adjudi-
cating matters of customary law and so cannot infl uence the law’s evolution.
Women may not be able to voice their grievances directly, and it is up to the
male head of the family to bring a grievance to the attention of elders.


Before presenting recommendations for the way forward, we show how
easily case law can reverse earlier gains (box 7.2).


The Way Forward


Case law can be a progressive instrument for change when statutes are inter-
preted equitably or legal ambiguities are creatively fi lled in to advance women’s
rights.


To reduce the potential for discrimination, eff orts should be directed toward
draft ing clear legislation, in harmony with constitutional principles of gender




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 175


equality and nondiscrimination. In family law and inheritance, women’s rights
to marital and inheritance property should be unequivocally equal to men’s.


Based on the more in-depth analysis in the companion report, Empowering
Women: Expanding Economic Opportunities in Africa (Hallward-Driemeier and
Hasan 2012), we propose recommendations in three areas to address gaps in
legal and economic rights for women—as they exist on the books as well as in
the form of practical constraints to accessing justice (box 7.3).


Despite the obvious benefi ts of reform, success is more likely if governments
proceed with caution, and with respect for existing systems. For reforms to be
eff ective, buy-in from all stakeholders is essential; this is the only way to ensure
that the change is enacted—and enforced.


To unify and strengthen women’s rights, all sources of law should be
subject to the principle of nondiscrimination. If protections are important
enough to be included as a guiding constitutional principle, they should
apply equally to all people. Th ey should cover all sources of law, including
customary and religious law. And they should specifi cally cover, rather than


BOX 7 .2


A Step Back: A Kenyan Court’s Ruling on Dividing Marital
Property
In the Kenyan case of Echaria v. Echaria, the spouses had been married for 23 years.
The wife was university educated and had worked outside the home for some time, but
she had spent much of her married life looking after their four children and supporting
her husband, who had risen in the diplomatic service to become an ambassador.
The  family had lived abroad and, on her return to Kenya, Mrs. Echaria worked as a
senior education offi cer. In the divorce proceedings, Mrs. Echaria claimed a 50 percent
share of the matrimonial property.


The Court of Appeal decided the case and overturned an earlier decision of the
High Court recognizing nonmonetary contributions. It held that the division of prop-
erty in marriage would be determined under the general laws of contract in Kenya and
that a woman would have to show her monetary contribution.


The Court of Appeal awarded her only a quarter share of the property. It
concluded that the only contribution toward the acquisition of the property that
Mrs. Echaria could have made was by payment of monthly installments for a loan.
The court further stated that the mere status of marriage does not entitle a spouse to
a benefi cial interest in the property registered in the name of the other. Nor did the
performance of domestic duties qualify as a contribution to the acquisition of marital
property.


Source: Hallward-Driemeier and Hasan 2012.




176 ENTERPRISING WOMEN


BOX 7 .3


Recommendations for Closing Gaps in Legal and Economic
Rights
The following recommendations for closing gaps in legal and economic rights summa-
rize those made in the companion report.


Improve the substance of laws by


• Reforming family law, including measures to strengthen the legal recognition of
nonmonetary contributions to marriage in division of property after divorce or death,
and removal of head-of-household and related provisions in family codes and other
statutes that diminish women’s legal capacity and economic autonomy


• Reforming land laws, notably to facilitate and encourage joint land titling
• Reforming labor and employment laws, primarily to address restrictions on all


women or on married women that limit the type of work women may engage in or
the hours they may work


• Strengthening in customary law the application of nondiscrimination principles,
especially for marital property and land, and building on the strengths and accessi-
bility of customary dispute-resolution mechanisms, while offsetting areas of gender
bias in how customary law is applied


Strengthen the process of formal and informal systems by


• Addressing the political economy, especially in relation to amending family codes
or laws


• Taking the sociocultural context into account when drafting new laws that are
specifi cally appropriate to the country situation


• Undertaking a thorough analysis of the legal framework of the country as an integral
part of the reform process


Strengthen the administration of laws and access to justice by


• Taking steps to encourage the registration of marriages, including customary
marriages


• Encouraging the use of prenuptial agreements and wills, to provide a foundation for
articulating and enforcing women’s rights in marriage and inheritance—and building
capacity in the use of these instruments


• Expanding access to laws and legal decisions in the judiciary
• Improving accountability in the judicial system
• Undertaking gender-sensitivity training for key members in the judicial system,


notably judges and magistrates


• Encouraging greater participation of women in judicial decision-making bodies




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 177


exempt, family law and other laws aff ecting property rights in and outside
marriage.


Notes
1. Other rights matter, too, such as civil and political rights. But the focus here is on


issues that most directly aff ect the ability to engage in business, and, specifi cally, on
gender diff erences in these areas.


2. Th e database is M. Hallward-Driemeier, T. Hasan, M. Blackden, J. Kamangu, and
E. Lobti, Women’s Legal and Economic Empowerment Database, http://worldbank
.org/gender/womenleedafrica. Th e companion report, Empowering Women: Legal
Rights and Economic Opportunities in Africa (Hallward-Driemeier and Hasan 2012),
presents the Women–LEED–Africa database and off ers a legal analysis of gaps in
property rights, including analysis of court decisions, the importance of customary
law and practices, and the impact of overlapping legal systems on women’s economic
rights. It also explores the practical gaps in accessing formal justice and outlines
a legal reform agenda for policy makers. Th is chapter summarizes some of that
report’s fi ndings.


3. As shown in chapter 3, women are more likely to stream into self-employment in
countries with weaker legal rights—and more likely to be employers in countries
with stronger legal rights.


4. Collecting information on inheritance rights of daughters compared to sons was
beyond the scope of this book.


5. See Quisumbing and others (2001), Lastarria-Cornhiel (1997), Place (1995), and
Deininger (2003).


References
Acemoglu, D., and S. Johnson. 2005. “Unbundling Institutions.” Journal of Political


Economy 113 (5): 949–95.
Acemoglu, D., S. Johnson, and J. Robinson. 2001. “Th e Colonial Origins of Comparative


Development: An Empirical Investigation.” American Economic Review 91
(5): 1369–401.


• Implementing steps to reduce costs and simplify procedures
• Giving thought to institutional reforms to improve access, such as establishing


small claims courts to tackle smaller business disputes, and using alternative dispute
resolution mechanisms in family law and property disputes, because such mecha-
nisms may be more familiar to communities already accustomed to traditional justice
forums


Source: Hallward-Driemeier and Hasan 2012.




178 ENTERPRISING WOMEN


Aryeetey, E., and C. Udry. 2010. “Creating Property Rights: Land Banks in Ghana.”
American Economic Review Papers and Proceedings 100 (2): 130–34.


Besley, T. 1995. “Property Rights and Investment Incentives: Th eory and Evidence from
Ghana.” Journal of Political Economy 103 (5): 903–37.


Besley, T., and M. Ghatak. 2009. “Property Rights and Economic Development.”
CEPR Discussion Paper 7234, Centre for Economic Policy Research, London.


Deininger, K. 2003. Land Policies for Growth and Poverty Reduction. Policy Research
Report, World Bank, Washington, DC.


Deininger, K., A. Goyal, and H. Nagarajan. 2010. “Inheritance Law Reform and Women’s
Access to Capital: Evidence from India’s Hindu Succession Act.” Policy Research
Working Paper 5338, World Bank, Washington, DC.


Field, E. 2007. “Entitled to Work: Urban Property Rights and the Labor Supply in Peru.”
Quarterly Journal of Economics 122: 1561–602.


Field, E., and M. Torero. 2008. “Do Property Titles Increase Credit Access among the
Urban Poor? Evidence from a Nationwide Titling Program.” Working paper, Harvard
University, Cambridge, MA.


Glaeser, E. L., R. La Porta, F. Lopez-de-Silanes, and A. Shleifer. 2004. “Do Institutions
Cause Growth?” Journal of Economic Growth 9 (3): 271–303.


Gray, J. 1997. “Th e Fall in Men’s Return to Marriage: Declining Productivity Eff ects or
Changing Selection.” Journal of Human Resources 32 (3): 481–504.


Hallward-Driemeier, M., and O. Gajigo. 2011. “Strengthening Economic Rights and
Women’s Occupational Choice: Th e Impact of Reforming Ethiopia’s Family Law.”
Paper presented at Centre for the Study of African Economics annual conference, St.
Catherine’s College, Oxford, March 20–22.


Hallward-Driemeier, M., and T. Hasan. 2012. Empowering Women: Legal Rights and
Economic Opportunities in Africa. Washington, DC: World Bank and Agence Française
de Développement.


Johnson, S., J. McMillan, and C. Woodruff . 2002. “Property Rights and Finance.” Ameri-
can Economic Review 92 (5): 1335–56.


Lastarria-Cornhiel, S. 1997. “Impact of Privatization on Gender and Property Rights in
Africa.” World Development 25 (8): 1317–33.


Pande, R., and C. Udry. 2005. “Institutions and Development: A View from Below.”
Economic Growth Center Discussion Paper 928, Yale University, New Haven, CT.


Place, F. 1995. Th e Role of Land and Tree Tenure on the Adoption of Agroforestry
Technologies in Zambia, Burundi, Uganda, and Malawi: A Summary and Synthesis.
Madison, WI: Land Tenure Center, University of Wisconsin–Madison.


Quisumbing, A. E. 1996. “Male-Female Differences in Agricultural Productiv-
ity: Methodological Issues and Empirical Evidence.” World Development 24 (10):
1579–95.


Quisumbing, A. E., Payongayong, J. B. Aidoo, and K. Otsuka. 2001. “Women’s Land
Rights in the Transition to Individualized Ownership: Implications for Tree‐Resource
Management in Western Ghana.” Economic Development and Cultural Change 50
(1): 157–82.




INCREASING THE RIGHT TO OWN AND CONTROL ASSETS 179


Rodrik, D., A. Subramanian, and F. Trebbi. 2004. “Institutions Rule: Th e Primacy of
Institutions over Geography and Integration in Economic Development.” Journal of
Economic Growth 9 (2): 1381–438.


Roy, S. 2008. “Female Empowerment through Inheritance Rights: Evidence from India.”
STICERD working paper, London School of Economics, London.


Saito, K. A., H. Mekonnen, and D. Spurling. 1994. “Raising Productivity of Women
Farmers in Sub-Saharan Africa.” Discussion Paper 230, World Bank, Washington, DC.


Simavi, S., C. Manuel, and M. Blackden. 2010. Gender Dimensions of Investment Climate
Reform: A Guide for Policy Makers and Practitioners. Washington, DC: World Bank.


Stevenson, B., and J. Wolfers. 2006. “Bargaining in the Shadow of the Law: Divorce Laws
and Family Distress.” Quarterly Journal of Economics 121 (1): 267–88.


Udry, C., and M. Goldstein. 2008. “Th e Profi ts of Power: Land Rights and Agricultural
Investment in Ghana.” Journal of Political Economy 116 (6): 981–1022.


Udry, C., J. Hoddinott, H. Alderman, and L. Haddad. 1995. “Gender Diff erentials in
Farm Productivity: Implications for Household Effi ciency and Agricultural Policy.”
Food Policy 20 (5): 407–23.


UNECA (United Nations Economic Commission for Africa). 2003. Land Tenure Systems
and Sustainable Development in Southern Africa. ECA/SA/EGM.Land/2003/2. Lusaka,
Zambia: UNECA.


World Bank. 2001. “Engendering Development: Th rough Gender Equality in Rights,
Resources and Voice.” Policy Research Report, World Bank, Washington, DC.


. 2010. Women, Business, and the Law 2010. Washington, DC: World Bank.






181


Chapter 8


Expanding Women’s Access to Finance


Starting a business requires assets. Once a business is started, internal resources
are not always adequate, particularly for expansion. And if business and house-
hold fi nances are not fully independent, it can be a challenge to keep resources
from being diverted from the business. Financial services provide solutions to
these challenges by securing access to productive resources, smoothing cash
fl ow, and providing savings instruments (box 8.1). Th ey can be provided by the
informal sector too, but the focus here is largely on formal fi nancial services
provided by microcredit institutions and banks.


Limited access to fi nance is cited as a top constraint facing entrepreneurs,
and indeed, few fi rms, particularly in lower-income and weak rule of law coun-
tries, report having formal loans from banks (Banerjee and Dufl o 2008; Beck,
Demirgüç-Kunt, and Maksimovic 2008). In Sub-Saharan Africa fewer than one in
fi ve households has access to formal fi nancial services. It is a systemic issue for
businesses (male or female), which are 40 percent less likely to have any formal
fi nancial access than their peers in other regions.1 But larger companies do have
an advantage in accessing fi nancial institutions.


More men than women have access to formal fi nancial services. However, it
is not necessarily due to discrimination within the fi nancial sector. Education
and experience are associated with using credit more productively, and thus
both are highly correlated with the ability to secure access to fi nance. An analy-
sis of individuals strongly suggests that gender diff erences in income, educa-
tion, and employment status explain women’s lower access to formal fi nancing.
Education, which is lower for women on average, rather than gender per se, is
a better predictor of whether someone is likely to get credit. Th is fi nding makes
clear that strengthening women’s human capital and managerial skills (the sub-
ject of chapter 9) is an integral part of the agenda to expand access to fi nance.


At the same time, the Enterprise Surveys show that established enterprises
run by women in the formal sector do not seem more fi nancially constrained
than those run by men.2 Access to fi nancial resources depends more on the
size and registration status of the fi rm than on the gender of the manager. But
what is striking is that women own and run such a small proportion of these




182 ENTERPRISING WOMEN


large formal fi rms. Th is raises two points. Th e few women who run large formal
fi rms have strong educational backgrounds and prior work experience and are
thus able to qualify for credit (Aterido, Beck, and Iacovone, forthcoming). But
precisely because there are disproportionately fewer women in this tier, gender
dynamics may be at work in accessing fi nance at entry.


Does access to fi nance act as a barrier to entry that is particularly diffi cult for
women to surmount? Certainly among new entrepreneurs, women’s businesses
have less access than men, and this diff erence is strongly associated with the
nature of their business. Data suggest that prior to entry, women have more-
limited access, consistent with their starting smaller and less capital-intensive
fi rms, which are then less likely to access external fi nance once they are run-
ning. Th e earlier analysis showing that fewer women are employers where gaps
in legal and economic rights persist is consistent with women facing barriers
at entry. However, more data are needed to conclusively examine the barriers
to entry.3


Th e concern over limited access to fi nance stems from the belief that if credit
were available, entrepreneurs would be able to exploit additional opportuni-
ties that are otherwise cut off from them.4 Certainly the data show a positive
association of access to credit and profi tability, not just in the data used here
but in most of the literature (for example, Bardasi and Sabarwal 2009; Karlan
and Morduch 2010; World Bank 2007).5 But if creditors are doing their job in
allocating capital, it should go to those with higher potential, so selection is
clearly contributing to the relationship. A better way to measure causation is to
look at studies that randomize access to credit. Th ese studies indeed show very
high rates of return to credit (de Mel, McKenzie, and Woodruff 2008; McKenzie
and Woodruff 2008). However, in some cases women have not benefi ted as
much as men (de Mel, McKenzie, and Woodruff 2009). Gender sorting into less
capital-intensive sectors could be part of the explanation; less control within the
household over how profi ts are used is another. Box 8.1 reviews the literature on
women’s access to fi nance; the rest of this chapter examines the extent to which
women have diff erential access to diff erent sources of fi nance.


Sub-Saharan Africa in a Global Context


Many entrepreneurs, worldwide, fail to secure the fi nance they want, but the
problem is worse in Sub-Saharan Africa than in other regions. Data from 112
countries, including 37 from Sub-Saharan Africa, show a smaller proportion of
formal businesses in the region have access to formal external fi nance, whether
for investment or working capital, than elsewhere in the world (fi gure 8.1).
Th e share of fi rms with some type of formal access to fi nance (bank account,
credit line, or loan) is also lower (fi gure 8.2). Th is result is consistent with other




EXPANDING WOMEN’S ACCESS TO FINANCE 183


BOX 8.1


A Review of the Literature on Women’s Access to Finance
As documented by an extensive and still growing literature, access to credit is important
for fi rm growth, especially that of small fi rms (Beck, Demirgüç-Kunt, and Maksimovic
2005), and for new business creation (Klapper, Laeven, and Rajan 2006). Randomized
fi eld experiments confi rm that access to capital can be critical (de Mel, McKenzie, and
Woodruff 2008) for both women and men. Dupas and Robinson (2009) found that
in Kenya opening a bank account increased the investments of female traders but
not male.


As chapter 2 discussed, the inability to access external fi nance is reported as a top
constraint by entrepreneurs in the region. Both men and women report that women are
likely to face greater obstacles in accessing external credit. There is increasing research
on the gender gap in access to credit (see Klapper and Parker 2010 for a survey). Cross-
country studies have shown that women are less likely to get fi nancing from a formal
fi nancial institution, are charged higher interest rates than men ( Muravyev, Schäfer,
and Talavera 2007), and generally raise less formal and informal venture capital than
men (Brush and others 2004).


The literature has also explored the reasons behind such a gender gap. Buvinic and
Berger (1990) fi nd that female entrepreneurs struggle more with loan applications,
while Lusardi and Tufano (2009) fi nd lower overall fi nancial literacy among women.
Fafchamps and others (2010) studied microenterprises in urban Ghana and found
that capital alone is not suffi cient to enhance growth of subsistence businesses run
by women; human capital measures and behavioral characteristics can matter too.
According to Karlan and Valdivia (2011), women trained in fi nancial literacy can apply
their new knowledge and pass it on in their communities.


Legal restrictions or property requirements for formal fi nancing could lead women
to have recourse to informal, though more expensive fi nancing. Such restrictions might
include requirements for married women to obtain their husband’s signature to open a
bank account, a provision in the laws of eight Sub-Saharan countries (see chapter 7).
Richardson, Howarth, and Finnegan (2004) fi nd for Sub-Saharan Africa that women
entrepreneurs are more likely than men to rely on internal or informal fi nancing. Evidence
from Sub-Saharan Africa shows that in many instances, only male heads of households
can receive formal credit (Johnson 2004; Narain 2009). Women can also be affected by
a husband’s adverse credit history and (as in South Africa) be required to repay the debt
or be denied credit (Blanchard, Zhao, and Yinger 2005; Naidoo and Hilton 2006).


Behavioral differences between men and women could suggest that gender gaps in
credit are due to cultural preferences rather than statistical discrimination (Beck, Behr,
and Madestam 2011). Fafchamps and others (2010) fi nd that microenterprises’ returns
to positive shocks in urban Ghana yield positive outcomes only for in-kind grants.
Cash grants, by contrast, do not increase profi ts and tend to be spent in the house,


—Continued




184 ENTERPRISING WOMEN


fi ndings based on earlier rounds of fi rm surveys in the region (Bigsten and
Söderbom 2006).


Female-owned enterprises in Sub-Saharan Africa seem to have slightly more
access to fi nance than those owned by men only, though access also depends on
formality and other enterprise characteristics. (For example, formality is a sig-
nifi cant predictor of the fi nancial sources—internal, microfi nance institutions,
moneylenders, commercial banks, or friends and relatives.) Th is fi nding may
mask the fact that fi rms with at least one woman among owners are typically
larger, more likely to innovate, and as a consequence more likely to have more
access to external fi nance. For sole proprietors, the gender gap disappears
( figures  8.1 and 8.2), though for financing investments, female-owned
businesses have slightly more access.


Data from the gender module of the Enterprise Surveys show, however, that
female-run fi rms (rather than female-owned fi rms) have somewhat less access
to fi nance. Th is discrepancy once again shows the problem of defi ning a fi rm
with any female owner as a female business.


especially when given to women. This differential effect seems to be due to behav-
ioral—not external—causes. However, other studies fi nd few statistical differences in
liquidity, risk aversion, and entrepreneurial ability in explaining gaps in returns and
investment rates (Falco 2012).


The differences in sectors chosen or activities undertaken by women and men could
partly explain the gender gap in fi nance. Indeed, the gender gaps found by de Mel,
McKenzie, and Woodruff (2008) close signifi cantly when taking sector into account—
but not entirely (and this still raises the question of whether differential access to
fi nance underlies differences in choice of activity).


Not all studies fi nd a gender gap. In a study of eight Latin American countries, Bruhn
(2009) does not fi nd evidence of access to fi nance explaining the gender difference in
size of existing enterprises. Looking at Kenya, Akoten, Sawada, and Otsuka (2006)
fi nd that while there are some gender differences in credit sources, the only statistically
signifi cant gender difference in average loan size occurs when the loan is from friends
and relatives (female loans on average are higher). De Mel, McKenzie, and Woodruff
(2008) fi nd that female entrepreneurs experienced lower returns to capital; they also
fi nd differences in the kinds of investment by gender.


The question explored here is whether women do indeed have greater trouble
getting fi nance—and if so, the extent to which this diffi culty is due to gender biases or
to the concentration of women in enterprises that are less attractive to lenders. While
not conclusive because of data limitations, the discussion here also explores whether
differential access to fi nance underlies differences in the initial choice of enterprise by
women and men.


BOX 8.1 con t i nued




EXPANDING WOMEN’S ACCESS TO FINANCE 185


Figure 8.1 Sub-Saharan Africa Lags in Access to Formal Finance, Including Bank Accounts,
Credit Lines, and Loans


0


20


40


60


80


100


Male Female Male Female


Other regions Sub-Saharan Africa


Pe
rc


en
ta


ge
o


f fi
rm


s
w


it
h


ac
ce


ss
t


o
fo


rm
al



fin


an
ci


al
s


er
vi


ce
s


a. All formal firms


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.


0


20


40


60


80


100


Male Female Male Female


Other regions Sub-Saharan Africa


Pe
rc


en
ta


ge
o


f fi
rm


s
w


it
h


ac
ce


ss
t


o
fo


rm
al



fin


an
ci


al
s


er
vi


ce
s


b. Formal sole proprietorships




186 ENTERPRISING WOMEN


Figure 8.2 Sub-Saharan Africa Lags in Access to Formal External Finance


0


5


10


15


20


25


Male Female Male Female


Other regions Sub-Saharan Africa


Pe
rc


en
ta


ge
o


f fi
na


nc
es


fr
om


fo
rm


al


ex
te


rn
al


s
ou


rc
es


(m
ea


n)


a. All formal firms


Source: Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.


0


5


10


15


20


25


Male Female Male Female


Other regions Sub-Saharan Africa


Pe
rc


en
ta


ge
o


f fi
na


nc
es


fr
om


fo
rm


al


ex
te


rn
al


s
ou


rc
es


(m
ea


n)


b. Formal sole proprietorships


Investments Working capital




EXPANDING WOMEN’S ACCESS TO FINANCE 187


Th e patterns shown in fi gures 8.1 and 8.2 are robust to controlling for other
characteristics in a multivariate regression analysis. Th e result that Sub-Saharan
businesses are less able to access formal fi nancial services is extremely robust.
Regional businesses receive 9–14 percentage points less in external fi nancing
from formal institutions for both their investments and working capital, and
are 40 percent less likely to access any formal fi nancial services at all, including
a bank account. Th e results also show that larger companies have a signifi cant
advantage in getting fi nancial institutions to fi nance both their investments
and working capital: an increase in fi rm size of 10 percent is associated with a
12–18 percentage point increase in the share of investment or working capital
fi nanced by fi nancial institutions (Aterido, Beck, and Iacovone, forthcoming).


Whereas size is strongly correlated with access to formal fi nancial services,
gender is not. One exception is that larger enterprises of female sole proprietors
tend to have greater access to fi nance in Sub-Saharan Africa compared to other
regions. Analyzing only Sub-Saharan Africa in separate subsamples for formal
and informal enterprises confi rms the absence of statistically signifi cant diff er-
ence by gender in access to fi nance. Female enterprises in the region have the
same access to fi nance as male-owned fi rms. Th ese results apply to formal and
informal companies, and are robust in the subsample of companies with a sole
proprietor (Aterido, Beck, and Iacovone, forthcoming).


Part of this explanation comes from the expansion of alternative forms of
fi nance that in many cases explicitly target women (see box 8.2). Four exam-
ples of International Finance Corporation (IFC) initiatives provide additional
practical insights into how women entrepreneurs’ access to fi nance could be
expanded (box 8.3).


Individuals’ Access to Finance


To what extent does access to fi nance itself drive the selection of the type of fi rm
that an entrepreneur runs? Unfortunately, the data are too scarce to address
this question directly. Panel data on individuals and their access to assets and
fi nance would be needed, along with information on individuals’ employment
history and entrepreneurial activities. If the analysis controlled for individual
characteristics, these data could capture the factors shaping entry decisions.


Lacking such data, we look in this section and the next at two sets of evidence.
Th is section looks at data at the individual level on who has access to fi nan-
cial services. Individual rather than household data are important for gender
analysis. Th e data cover individuals with various employment histories—so,
one caveat is that not all individuals are entrepreneurs. Correlations between
access to fi nance and loans do not determine causation, of course, but they do
allow one to see if those who are entrepreneurs are more (or less) likely to have




188 ENTERPRISING WOMEN


BOX 8.2


Alternative Finance for Women in Sub-Saharan Africa
Many microfi nance institutions (MFIs) have targeted women, helping to shrink gender
gaps in access to credit. In some cases, the focus of MFIs on women has actually led
to more women than men having access to fi nance (Armendariz and Roome 2008;
Pitt, Khandker, and Cartwright 2003). The Women’s World Banking (2009) report on
microfi nance in Africa fi nds that in Kenya, Nigeria, and South Africa, MFIs’ clientele is
more than 50 percent women. Some MFIs offer services almost exclusively to female
clientele (GAWFA in The Gambia, KWFT in Kenya, Microloan Foundation MWI in
Malawi, MECREF in Niger, LAPO in Nigeria, and SEF in South Africaa). According to the
Consultative Group to Assist the Poor (CGAP 2010), some West African countries’ MFIs
have extended their activities such that deposit-taking microfi nance institutions have
more depositors than commercial banks.


Beyond microcredit, many individuals and enterprises across the developing world
use informal fi nancial services, ranging from moneylenders to Rotating Savings and
Credit Associations. This type of fi nancing is very expensive but requires less collateral
and has fewer legal requirements. In countries where women face gender-specifi c legal
constraints, women may have recourse more frequently to this type of informal fi nanc-
ing. Given the limitations of microcredit and informal lending, both in volume and in
outreach, it is still important to understand gender differences in the use of formal
banking services (Honohan 2004).


a. GAWFA = Gambia Women’s Finance Association; KWFT = Kenya Women Finance Trust (KWFT);


MECREF = Mutuelle d’Epargne et de Credit des Femmes; LAPO = Lift Above Poverty Microfi nance Bank


Ltd.; SEF = Small Enterprise Foundation.


BOX 8.3


Expanding Access to Finance for Female Entrepreneurs—
Insights from the Supply Side
Financial institutions are recognizing that, with women as half of all entrepreneurs,
there is a large and underserved market opportunity in developing a larger female
clientele. Since 2006 the IFC has partnered with 14 fi nancial institutions to increase
access to fi nance for women entrepreneurs. It has also helped enact reforms to support
women’s participation in the private sector in more than a dozen countries.


Case 1. Expanding a Bank’s Financial Outreach to Female Clients in Nigeria
IFC research in Nigeria showed that women had different attitudes than men toward
fi nance, that women poorly understood what banks required of their clients, and that




EXPANDING WOMEN’S ACCESS TO FINANCE 189


—Continued


banks did not understand how best to serve their women clientele. One of the key
structural issues was the paucity of historical credit information from independent
sources like credit bureaus.


The IFC provided a US$15 million credit line along with a US$400,000 Advisory
Services Program to Access Bank Nigeria, which in turn contributed US$500,000
toward developing and running the program. One objective was to improve Access
Bank’s fi nancial service delivery to the women’s market in Nigeria, including staff train-
ing, strategic planning, market positioning, and segmentation. A second was to assist
Access Bank in improving the quality of its female client base by providing women
entrepreneurs with fi nancial literacy and business skills. Several new women-friendly
products and services were developed, such as fl exible collateral, including the pledg-
ing of equipment and cash fl ow–based lending.


Between 2006 and 2009 more than US$35 million in loans was disbursed to
women entrepreneurs, while maintaining a nonperforming loan ratio of less than
1 percent (1,300 new deposit accounts and 1,700 checking accounts were opened;
650 women were trained). Its success led Access Bank to replicate the program in
The Gambia and Rwanda. Other banks in Nigeria have followed suit, and a new pri-
vate equity fund and an asset management fund targeting women have entered the
Nigerian market.


Case 2. Building Credit Histories and Expanding Loan Guarantees for
Female Entrepreneurs in Uganda
The Women In Business program of the Development Finance Company of Uganda
(DFCU) shows how access to fi nance and skill development can drive the growth of
female-owned enterprises. The DFCU has built a portfolio of business loans, leases,
mortgages, and other products targeting women entrepreneurs. The effort began in
2007 after IFC research showed that Ugandan women owned nearly 40 percent of
registered businesses but received less than 10 percent of commercial credit.


A lack of information on these businesses was a key barrier. Working with the
IFC, DFCU emphasized equipment leases over traditional loans to help women build
a credit history. DFCU introduced group borrowing as well as land loans to enable
women to acquire collateral. Financial training and business support completed the
picture.


Since 2007, more than 368 women have been trained in entrepreneurship and
business and management best practices. As of December 2009, DFCU had disbursed
close to US$16.1 million in term loans, working capital loans, mortgages, leases, and
land loans to 300 female entrepreneurs in the small and medium enterprise (SME)
sector. The default rate for the women’s SME portfolio (1.5 percent) is lower than
that for male borrowers (2.5 percent). IFC supports similar projects in Benin, Burundi,
Côte d’Ivoire, the Democratic Republic of Congo, Kenya, Malawi, Mozambique, Niger,
Nigeria, and Tanzania.




190 ENTERPRISING WOMEN


access to fi nance. Another caveat is that the fi nancial services included can be
for personal use. Still, the benefi t of this approach is that these types of loans are
oft en those available to prospective entrepreneurs.


Th is section focuses more on savings and payments (formal and informal)
than credit. It uses data on nine Sub-Saharan countries from household surveys,
called FinScope or FinAccess surveys, which gather information on individuals
rather than households.6 While this approach might reduce representativeness
(and hence overall accuracy) because the individual has indirect access to
fi nancial services through other household members, it has the advantage of


Case 3. Providing Finance Where Laws Limit Women’s Access to Traditional
Sources of Collateral: Sero Lease and Finance Ltd. in Tanzania
Tanzania’s customary law largely excludes women from owning land, and with a
predominantly collateral-based banking system, women were effectively excluded from
loans, including business loans. Sero Lease and Finance Ltd. (Selfi na) is a women’s leasing and
fi nance company that went into microleasing in 1997 to enable women to acquire equip-
ment for immediate use with a down payment and fi nancial lease. It targeted 3,000 SMEs
and had a zero default rate and 99 percent payback rate, with an average loan size of $500.


A further objective was to help women use their good credit history in microfi -
nance to gain access to commercial banking. The IFC helped broker a $1 million loan
from the Exim Bank facility to Selfi na. As of October 2007, 150 Selfi na clients had
already opened “Tumaini” savings accounts at Exim Bank. IFC training for the women
enhanced their knowledge of the application process and also included courses on
business planning and management.


Case 4. Global Banking Alliance for Women: Recognizing Best Practices
in the Delivery of Financial Services to Women
Originally founded by four banks from developed countries, the Global Banking
Alliance for Women (GBA) has grown into a truly global organization. The GBA mission
is to accelerate the growth of women in business and aid in women’s wealth creation,
while generating superior business outcomes for member fi nancial institutions. Mem-
bers share best practices and research and collaborate with fi nancial institutions to
provide women with vital access to capital, markets, education, and training. The GBA
chapter in Uganda, for example, allows GBA member banks like DFCU to provide their
customers with a streamlined exchange of information, research, and resources, giving
women a chance to spur their business growth.


Source: IFC, Sustainable Finance Department, “Banking on Women Pays Off: Creating Opportunities for
Women Entrepreneurs,” http://www.intracen.org/uploadedFiles/intracenorg/Content/About_ITC/Where_
are_we_working/Multi-country_programmes/Women_and_trade/Banking%20on%20Women%20
pays%20off.pdf.


BOX 8.3 con t i nued




EXPANDING WOMEN’S ACCESS TO FINANCE 191


Figure 8.3 A High Degree of Financial Exclusion Exists across Eastern and Southern Africa


0


Bo
stw


an
a


Ke
ny


a


Ma
law


i


Na
mi


bia


Rw
an


da


So
uth


Af
ric


a


Ta
nz


an
ia


Ug
an


da


Za
mb


ia


10


20


30


40


50


60


70


80


a. Banking


Pe
rc


en
ta


ge
o


f i
nd


iv
id


ua
ls



m


ak
in


g
us


e
of


b
an


ki
ng


—Continued


being able to focus on gender. All surveys used in this section were undertaken
between 2004 and 2009; the analysis is done in the non agriculture sector.


Th e analyses focus on three segments: formal banking services; informal
fi nancial services, including unregulated SACCOs, ASCAs, and ROSCAs;7
and exclusion from any service. Revealing large cross-country variation in use
(fi gure 8.3), the surveys also indicate the high degree of fi nancial exclusion
across eastern and southern Africa.


All nine surveys showed that compared to men, women were less likely to
use formal fi nancial services, were generally more likely to use informal ser-
vices, and were generally as likely or more likely to be excluded from access to
any fi nancial service.


Th ese results are consistent with the hypothesis of a gender gap in the use of
formal banking services, but because they do not control for other individual
characteristics, we used a multivariate regression analysis to explore whether
these unconditional diff erences still hold with controls (table 8.1).


For access to formal fi nancial services, unconditional gender gaps lose
signifi cance once education and experience are controlled for. Women on
average are no more (or less) likely to use them. (South Africa is a notable
exception—women are 12.2 percentage points less likely to use them.)


Th e use of formal fi nancial services is correlated with an array of other
individual factors, which seem to explain why women are less likely to have
access to such services, and why once those characteristics are controlled for
the gender diff erence disappears. In work conducted for this project, Aterido,




192 ENTERPRISING WOMEN


Beck, and Iacovone (forthcoming) show that the biggest eff ect seems to come
from income diff erences between men and women, which explain up to half of
the gender diff erence. Th is explanation is particularly signifi cant in Rwanda.
Another big eff ect stems from women’s lower level of education. Adding the
economic eff ect of lower education across primary, secondary, and tertiary


Source: Aterido, Beck, and Iacovone, forthcoming.
Note: Data are for the nonagricultural sector and are drawn from the FinScope surveys, http://www.finscope.co.za.


0


Bo
stw


an
a


Ke
ny


a


Ma
law


i


Na
mi


bia


Rw
an


da


So
uth


Af
ric


a


Ta
nz


an
ia


Ug
an


da


Za
mb


ia


10


20


30


40


50


60


70


80


c. Excluded


Pe
rc


en
ta


ge
o


f i
nd


iv
id


ua
ls


e
xc


lu
de


d


fr
om


a
ny


fi
na


nc
ia


l s
er


vi
ce


Male Female


Figure 8.3 (continued)


0


Bo
stw


an
a


Ke
ny


a


Ma
law


i


Na
mi


bia


Rw
an


da


So
uth


Af
ric


a


Ta
nz


an
ia


Ug
an


da


Za
mb


ia


10


20


30


40


50


60


b. Informal


Pe
rc


en
ta


ge
o


f i
nd


iv
id


ua
ls



m


ak
in


g
us


e
of


in
fo


rm
al


s
er


vi
ce


s




EX
PA


N
D


IN
G


W
O


M
EN


’S A
C


C
ESS TO


FIN
A


N
C


E


193


Table 8.1 Once Education and Experience Are Controlled for, Women Are No More Likely Than Men to Use Formal Financial Services


Sample All Botswana Kenya Malawi Namibia Rwanda South Africa Tanzania Uganda Zambia


Female 0.017 0.027 −0.018 0.024 −0.019 −0.008 −0.118 −0.002 −0.029 0.005


[0.019] [0.041] [0.030] [0.018] [0.040] [0.018] [0.050]** [0.008] [0.025] [0.006]


Individual characteristics Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Regional effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Observations 33,872 974 6,589 4,712 1,065 1,894 3,345 5,864 1,674 3,990


Pseudo R2 0.43 0.37 0.46 0.36 0.47 0.32 0.27 0.40 0.41 0.53


Use of informal fi nancial services


Female 0.058 0.105 0.147 −0.013 −0.000 −0.086 0.011 0.063 0.041 −0.000


[0.010]*** [0.034]*** [0.029]*** [0.018] [0.000] [0.032]*** [0.011] [0.019]*** [0.029] [0.002]


Individual characteristics Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Regional effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Observations 33,173 974 6,589 4,712 228 1,869 3,345 5,864 1,674 3,990


Pseudo R2 0.33 0.29 0.10 0.07 0.33 0.05 0.19 0.05 0.08 0.25


Excluded from using fi nancial services


Female −0.068 −0.127 −0.076 0.017 0.019 0.090 0.055 −0.076 −0.067 −0.004


[0.020]*** [0.040]*** [0.021]*** [0.025] [0.040] [0.035]*** [0.032]* [0.023]*** [0.037]* [0.011]


Individual characteristics Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Regional effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes


Observations 33,872 974 6,589 4,712 1,065 1,894 3,345 5,864 1,674 3,990


Pseudo R2 0.43 0.35 0.31 0.11 0.48 0.10 0.31 0.18 0.19 0.44


Source: Aterido, Beck, and Iacovone, forthcoming.
Note: Dprobit regressions. Robust standard errors in brackets. Individual characteristics include education, income level, employment status, whether individual uses a mobile phone,
whether individual is household head, marital status, numerical literacy, measure of risk aversion, and region.
Significance level: * = 10 percent, ** = 5 percent, *** = 1 percent.




194 ENTERPRISING WOMEN


education in the pooled regression gives a total eff ect of four  percentage
points.


Another large eff ect comes from women’s lower likelihood of heading the
household; this accounts for three percentage points of diff erence in the pooled
regression. Employment also counts: women are less likely to be formally
employed than men, a diff erence with an economic eff ect of 5.5 percentage points
in the pooled regression. Finally, the ownership of mobile phones, a signifi cant
factor in explaining the univariate gender gap in use of formal fi nancial services,
adds another two percentage points (Aterido, Beck, and Iacovone, forthcoming).


Th e individual characteristics that explain the use of formal services also
largely explain the use of informal services, but they do not explain them
entirely. Gender gaps remain once other individual characteristics are included.
Th e eff ect is also economically large in some countries, with women on average
3.3 percentage points more likely than men to use informal fi nancial services, a
fi gure driven by Botswana, Kenya, Tanzania, and Uganda.


Looking at exclusion from all fi nancial services (formal and informal)
unconditionally, women are excluded more than men. However, when one
controls for individual characteristics, the gap fl ips, as the characteristics help
explain the gap in women’s access to formal but not to informal services. Th e
relatively large reliance of women on informal fi nance means that overall,
they are not more excluded than men at the same level of education and work
experience.


Th ese results are consistent with other work that looks at access to fi nance
and diff erentiates between formal and informal sources. Fafchamps (2000)
looks at access to bank loans among entrepreneurs in Kenya and Zimbabwe and
fi nds that the gender gap disappears once fi rm size is controlled for. However,
he fi nds that the eff ect on gender (and ethnicity) remains signifi cant for trade
credit and other forms that rely on more relationship-based lending.


Th ese fi ndings suggest that women’s lower use of formal banking services
is not due to discrimination in the banking system or lower inherent demand
by women—it is due to disadvantages in other areas, namely women’s lower
levels of education and income. Th ey also suggest that some of the fi ndings
might be driven by the survey methodology of interviewing individuals rather
than households: women may have indirect access to formal fi nancial services
through their formally employed husbands, the household heads.


Access to Finance: A Barrier to Entry?


Th e second set of evidence looks at data from the surveys of new entrepre-
neurs in Côte d’Ivoire, Kenya, Nigeria, and Senegal, in the formal and informal
sectors. Looking at the amount and sources of start-up capital sheds light on




EXPANDING WOMEN’S ACCESS TO FINANCE 195


gender gaps in access to fi nance and how they vary across activities and types
of enterprises. Th e data suggest that women are indeed more constrained in
their access to fi nance.


Finance is crucial for prospective entrepreneurs and, according to them, the
biggest obstacle when they set up a business. Th is is especially true for female
entrepreneurs in the informal sector, of whom almost 60 percent report fi nance
as the largest stumbling block. Although male entrepreneurs in the formal
sector are the least likely (among men and women in the formal and informal
sectors) to report lack of access to fi nance as the biggest obstacle, 40 percent of
them report that it is.


New entrepreneurs depend primarily on their own resources or those of
their friends and relatives when starting an enterprise (fi gure 8.4). Th ose with
limited savings or wealth face serious diffi culties in starting a business; and even
when they do set up one, their capacity to invest to optimal levels is constrained.


Figure 8.4 New Entrepreneurs Depend Primarily on Their Own, or on Friends’ and Relatives’,
Resources


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
u


si
ng



ca


pi
ta


l s
ou


rc
e


at
s


ta
rt


-u
p


Commercial banks


Purchase of supplies on credit


Friends/relatives
Microfinance institutions


Other


Moneylenders
Internal funds




196 ENTERPRISING WOMEN


Individual or household wealth is therefore likely to be an important predictor
not only of investment but also of profi tability, because poorer entrepreneurs
are less able to meet their optimal fi nancing needs.


As fi gure 8.4 shows, in sources of external fi nance accessed at start-up, strong
sector and gender components reveal themselves. Both male and female entre-
preneurs in the formal sector use banks more oft en than those in the informal
sector, but in the formal sector men use them signifi cantly more than women.
However, when entrepreneurs cite the single largest source of fi nancing at start-
up, the sectoral diff erences dominate the gender ones (fi gure 8.5).


Diff erence in access to microfi nance institutions is present only along sector
lines: male and female entrepreneurs in the formal sector have signifi cantly
more access to them than their informal counterparts. Formality, rather than
gender, also explains diff erences in patterns of fi nancing sources. Male and
female formal entrepreneurs are remarkably similar in depending on the vari-
ous sources of fi nance. And while for the informal sector we detect a gender


Figure 8.5 Sector Matters More Than Gender in Start-Ups’ Access to Formal Finance—
Although Some Gender Gaps Appear in the Informal Sector


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
r


ep
or


ti
ng


s
ou


rc
e


as
la


rg
es


t
at


s
ta


rt
-u


p


Moneylenders
Internal funds


Commercial banks


Purchase of supplies on credit


Friends/relatives
Microfinance institutions


Other




EXPANDING WOMEN’S ACCESS TO FINANCE 197


diff erence in the importance of moneylenders and friends and relatives, little or
no such diff erence appears in the importance of other sources of fi nance.


As we indicated in chapter 4, patterns in the way new businesses are created
also have gender dimensions. First, men are more likely to create a business
from an existing one than from scratch, while women show no diff erence.
Second, women start with less than half the initial capital of men (fi gure 4.8a).


Many new entrepreneurs lack access to fi nance. When the surveys asked
them why they did not apply for a loan, at least 55 percent of respondents who
had been in business for at least 12 months said they would like credit but could
not access it; they were intimidated by the complexity of the application process,
thought the interest was too high, did not have a guarantee, or did not think that
they would be approved. Th e 55 percent fi gure is likely an underestimate; as dis-
cussed below, a much higher proportion would have made diff erent investment
decisions if they had had twice as much money at start-up.


Conditional results for the determinants of various sources of start-up
capital yield a signifi cant positive female eff ect for dependence on internal funds
(that is, the entrepreneur’s own funds) and funds from friends or relatives. Th e
gender diff erence is negligible within the formal sector, but not within the infor-
mal sector. Female entrepreneurs in the informal sector are signifi cantly less
likely to depend on internal funds relative to males, while formal sector female
entrepreneurs have no signifi cantly diff erent eff ect. Female entrepreneurs are
signifi cantly more likely to depend heavily on friends or family, but the likeli-
hood is lower for female entrepreneurs in the formal sector once we control for
industry and other variables. In other words, the unconditional high female
dependence on this source of fi nance is driven mainly by those in the informal
sector.


Overall, the dependence on various sources of fi nance to start up a new
business is driven more by fi rm characteristics, particularly formality, than by
gender—but women in the informal sector do rely more on informal sources
of fi nance, which would be consistent with fi nance as a signifi cant barrier to
operating in the formal sector.


Financing New Businesses: Access to Loans after Start-Up


Access to fi nance is limited aft er start-up: only about 9 percent of new entre-
preneurs had a loan at the time of the survey, a rate similar to estimates from
other studies. Th at proportion contains strong gender and sector diff erences
(fi gure 8.6). In the formal and informal sectors, at least twice as many male as
female entrepreneurs had loans. Given their legal status, it is unsurprising that
formal entrepreneurs had more loans. But a gender diff erence within sectors
points to women facing greater constraints in accessing loans.




198 ENTERPRISING WOMEN


Despite being informal, some entrepreneurs secured loans from commer-
cial banks through various means (fi gure 8.7). Because of the small number of
entrepreneurs with loans, the analysis had to be limited to sectors and not gen-
der. Formal sector entrepreneurs depend more on land and buildings as guar-
antees. Informal entrepreneurs are signifi cantly more likely to use the owner’s
assets and to fi nd someone to cosign the loan.


Among those with loans, most formal sector entrepreneurs secured their
loans from commercial banks (fi gure  8.8). Informal entrepreneurs’ single-
biggest source was microcredit institutions, most likely due to specifi c targeting
by them. Nearly one-third of informal entrepreneurs managed to get loans from
banks, and one-fi ft h borrowed from moneylenders. Only a very small minority
in both sectors borrowed from suppliers or customers.


Entrepreneurial Choice Limited by Access to Finance


One concern about the impact of limited access to fi nance is that it constrains
which opportunities can be pursued. Th is section looks at how choices might
have been diff erent if more capital was available: what would entrepreneurs have


Figure 8.6 Strong Gender and Formality Differences Come through for the Few New
Entrepreneurs with Loans


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for new entrepreneurs in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


2


4


6


8


10


12


14


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
w


it
h


a
lo


an




EXPANDING WOMEN’S ACCESS TO FINANCE 199


done with twice as much money at start-up? And if the choices would have been
diff erent, what are the reasons given as to why a loan was not taken out?


Changing location and hiring more workers are the two most common
responses to the “what if?” question (fi gure 8.9). Th e desire to increase capi-
tal investment is particularly strong among male formal entrepreneurs. Even
though male entrepreneurs tend to have much more start-up capital than female
entrepreneurs, it is still possible that men may be more capital constrained,
given that gender sorting across industries and formal-informal activities is
not uniform. For example, male entrepreneurs are overrepresented relative to
women in manufacturing.


More men than women reported that they would have used additional
money to hire more workers. As with capital, this diff erence may well stem
from unequal concentrations across industries with greater scale economies
and formal-informal activities.


With twice the money at start-up, more informal than formal entrepreneurs
would have chosen a diff erent line of business (admittedly the sample is small).


Figure 8.7 Sources of Loan Guarantees Vary by Sector Formality


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal. Sample size is too
small to disaggregate by gender.


0


10


20


30


40


50


60


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


g
ua


ra
nt


ee
in


g
lo


an
w


it
h


so
ur


ce


Inventory & accounts receivablePersonal assets of owner


Cosigner


Machinery & equipment Land & buildings




200 ENTERPRISING WOMEN


Limited access to fi nance may therefore alter the distribution of fi rms across
industries and formal-informal activities, because high investment needs close
off certain business lines.


The gender pattern that shows more male entrepreneurs wanting
to invest  in machinery is robust when controlling for more variables.
Th is  fi nding is positively correlated with start-up capital, suggesting that
even  those  with higher start-up capital in this sample are likely to be
operating below their investment needs. Th e initial gender diff erence in the
preference for hiring workers is not, however, robust to controls for other
variables.


Are entrepreneurs actually constrained? Th e number of entrepreneurs
who applied for a loan in the previous 12 months—only 17 percent—initially
suggests not. But the reasons for not applying are important (fi gure 8.10).


Th e frequency with which specifi c reasons for nonapplication were
reported does not signifi cantly diff er from that found in other studies.
Th e  biggest reason (45  percent, combining men and women, formal and
informal) was a claim of no need (the same proportion among women in
both sectors, but 10  percentage points higher among male formal than
male informal entrepreneurs). But this response may need to be interpreted


Figure 8.8 Of Firms with External Start-Up Financing, Commercial Banks Are the Main
Source of Capital for Formal Firms


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal and show the
source of the loan for the 9 percent of entrepreneurs who currently have loans.


0


25


50


75


100


Formal Informal


Microcredit institution


Bank Moneylender


Supplier or customer credit


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


g
ua


ra
nt


ee
in


g
lo


an
w


it
h


so
ur


ce




EXPANDING WOMEN’S ACCESS TO FINANCE 201


with caution. Some individuals who assert they have no need may believe
that, perhaps because of existing debt, assuming further debt is not a good
course of action.


About 18  percent of all those not applying point to the complexity of
loan applications. Although the proportion is slightly higher in the informal
sector, the gender diff erence points in diff erent directions in the two sectors,
with women in the formal sector and men in the informal  sector more likely
to raise this concern. Th e fact that perceived transaction cost is  preventing
a signifi cant  proportion from even applying suggests that there is room
for public or other nongovernment initiatives to increase access to fi nance
through sensitization programs that reduce this cost.


One of the two areas with a signifi cant sector diff erence is a perceived
high interest rate: around 24 percent of formal, but only around 15 percent
of informal, entrepreneurs report this reason. Th is area also has a signifi cant
gender diff erence in the formal sector, with men more likely to report this as


Figure 8.9 With Twice the Money at Start-Up, Nearly All Entrepreneurs Would Have Done
Things Differently


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal and show what
entrepreneurs report they would have done differently if their money at start-up had been twice what it
actually was.


0


10


20


30


40


50


60


70


80


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f
en


tr
ep


re
ne


ur
s


w
ho


w
ou


ld
h


av
e


m
ad


e
th


e
ch


an
ge


Open additional establishment


Hire more workers


No change


Invest in more machinery


Locate in a different place


Change the line of business




202 ENTERPRISING WOMEN


their top concern. Women report more concerns about the application pro-
cedures themselves, or believe that an application would be futile because it
would not be approved. In short, almost half of the respondents express a need
for credit, but the large majority of them do not have it. A higher percentage
of respondents indicate they would have made diff erent investment decisions
in establishing their business had they had twice as much capital. Th e goal
should not be to extend credit to everyone who wants it; the point of a well-
functioning fi nancial system is precisely to allocate resources to their most
productive uses. But when entrepreneurs are discouraged by application pro-
cedures, transaction costs of applying, and perceptions that they will not be
given due consideration, it raises questions about how well the fi nancial system
is functioning, particularly for the smaller and less traditional borrower and for
those without an established track record, that is, for entrants. Further work
on understanding the fi nancial barriers to entry should be a priority going
forward.


Figure 8.10 Credit Constraints Appear to Be Common Among Sub-Saharan Entrepreneurs


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for enterprises that have been in operation for at least 12 months, based on surveys in Côte
d’Ivoire, Kenya, Nigeria, and Senegal.


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


re
pr


en
eu


rs
r


ep
or


ti
ng


a
s


re
as


on
w


hy
n


o
lo


an
a


pp
lic


at
io


n
w


as
m


ad
e


Interest rate too high


No need for loan Application too complex


Didn't think application would be approved


Had no guarantee


Other reason




EXPANDING WOMEN’S ACCESS TO FINANCE 203


Notes
1. Data on access to formal fi nance are from Finscope surveys for nine countries in


Sub-Saharan Africa, http://www.fi nscope.co.za.
2. Enterprise Surveys, World Bank, http://www.enterprisesurveys.org.
3. Bruhn and Love (2011) examine how expanding access to fi nance in Mexico was


associated with more men becoming entrepreneurs, but women were more likely to
increase their involvement with wage work. Some of the discrepancy could be that
couples worked in family enterprises, with the husband reported as the entrepreneur
and the wife a wage employee of the enterprise.


4. Economic opportunities are the focus here, but the literature also looks at the eff ect
of access to credit and of income earnings on women’s empowerment within the
home, and specifi cally on whether women’s bargaining positions are strengthened.
Much of the literature fi nds an eff ect, but Armendariz and Roome (2008) caution
that there can also be unintended consequences (see also Ashraf 2009; Ashraf,
Karlan, and Yin 2009; Banerjee and others 2009).


5. It should also be noted that simply not having access to credit is not equivalent to
being credit constrained. As discussed below, many fi rms report not wanting credit,
as there is insuffi cient demand for their product. One measure of credit constraints is
to examine if fi rms’ investment decisions are correlated with cash fl ow. Th e evidence
from Africa shows this pattern is greater for smaller fi rms, but the eff ect is not very
large (Bigsten and others 2003; Bigsten and Söderbom 2006). Th ese studies did not
look at the issue of gender.


6. Th e discussion draws on Aterido, Beck, and Iacovone (forthcoming), who ana-
lyzed FinScope data from nationally representative samples of individuals on their
perceptions and experiences accessing fi nancial services in nine Sub-Saharan coun-
tries. For more information, see also http://www.fi nscope.co.za.


7. SACCO = Savings and Credit Cooperative Organization; ASCA = Accumulat-
ing Savings and Credit Association; ROSCA = Rotational Savings and Credit
Association.


References
Akoten, J. E., Y. Sawada, and K. Otsuka. 2006. “Th e Determinants of Credit Access


and Its Impacts on Micro and Small Enterprises: Th e Case of Garment Producers in
Kenya.” Economic Development and Cultural Change 54 (4): 927–44.


Armendariz, B., and N. Roome. 2008. “Gender Empowerment in Microfi nance.” Working
paper, Department of Economics, Harvard University, Cambridge, MA.


Ashraf, N. 2009. “Spousal Control and Intra-household Decision Making:
An  Experimental Study in the Philippines.” American Economic Review 99
(4): 1245–77.


Ashraf, N., D. Karlan, and W. Yin. 2009. “Female Empowerment: Impact of
a Commitment  Savings Product in the Philippines. World Development 38
(3): 333–34.


Aterido, R., T. Beck, and L. Iacovone. Forthcoming. “Gender and Finance in Sub-Saharan
Africa: Are Women Disadvantaged?” World Development.




204 ENTERPRISING WOMEN


Banerjee, A., and E. Dufl o. 2008. “Do Firms Want to Borrow More? Testing Credit
Constraints Using a Directed Lending Program.” MIT Working Paper 02–25,
Massachusetts Institute of Technology, Cambridge, MA.


Banerjee, A., E. Dufl o, R. Glennerster, and C. Kinnan. 2009. “Th e Miracle of Micro-
fi nance? Evidence from a Randomized Evaluation.” Working paper, Massachusetts
Institute of Technology, Cambridge, MA.


Bardasi, E., and S. Sabarwal. 2009. “Gender, Access to Finance, and Entrepreneurial
Performance in Sub-Saharan Africa.” Working paper, World Bank, Washington,
DC.


Beck, T., P. Behr, and A. Madestam. 2011. “Sex and Credit: Is Th ere a Gender Bias in
Microfi nance?” European Banking Center Discussion Paper 2011-027, Tilburg
University, the Netherlands.


Beck, T., A. Demirgüç-Kunt, and V. Maksimovic. 2005. “Financial and Legal Constraints
to Firm Growth: Does Firm Size Matter?” Journal of Finance 60: 137–77.


. 2008. “Financing Patterns around the World: Are Small Firms Diff erent?”
Journal of Financial Economics 89: 467–87.


Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. Gunning, A. Oduro,
R. Oostendorp, C. Pattillo, M. Söderbom, F. Teal, and A. Zeufack. 2003. “Credit
Constraints in Manufacturing Enterprises in Africa.” Journal of African Economies
12 (1): 104–25.


Big sten, A., and M. Söderbom. 2006. “What Have We Learned from a Decade of
Manufacturing Enterprise Surveys in Africa?” World Bank Research Observer 21
(2): 241–65.


Blanchard, L., B. Zhao, and J. Yinger. 2005. “Do Credit Market Barriers Exist for Minority
and Women Entrepreneurs?” Working Paper 74, Syracuse University Maxwell School
Center for Policy Research, Syracuse, NY.


Bruhn, M. 2009. “Female-Owned Firms in Latin America: Characteristics, Perfor-
mance, and Obstacles to Growth.” Policy Research Working Paper 5122, World Bank,
Washington, DC.


Bruhn, M., and I. Love. 2011. “Gender Diff erences in the Impact of Banking Services:
Evidence from Mexico.” Small Business Economics 37 (4): 493–512.


Brush, C., N. Carter, E. Gatewood, P. Greene, and M. Hart. 2004. “Gatekeepers of
Venture Growth: A Diana Project Report on the Role and Participation of Women in
the Venture Capital Industry.” Kansas City, MO: Kauff man Foundation.


Buvinic, M., and M. Berger. 1990. “Sex Diff erences in Access to a Small Enterprise
Development Fund in Peru.” World Development 18: 695–705.


CGAP (Consultative Group to Assist the Poor). 2010. Financial Access 2010: Th e State
of Financial Inclusion through Crisis. Washington, DC: CGAP.


de Mel, S., D. McKenzie, and C. Woodruff . 2008. “Returns to Capital in Microenter-
prises: Evidence from a Field Experiment.” Quarterly Journal of Economics 123 (4):
1329–72.


. 2009. “Are Women More Credit Constrained? Experimental Evidence on
Gender and Microenterprise Returns.” American Economic Journal: Applied Economics
1 (3): 1–32.




EXPANDING WOMEN’S ACCESS TO FINANCE 205


Dupas, P., and J. Robinson. 2009. “Savings Constraints and Microenterprise Develop-
ment: Evidence from a Field Experiment in Kenya.” NBER Working Paper 14693,
National Bureau of Economic Research, Cambridge, MA.


Fafchamps, M. 2000. “Ethnicity and Credit in African Manufacturing.” Journal of
Development Economics 61(1): 205–35.


Fafchamps, M., D. McKenzie, S. Quinn, and C. Woodruff . 2010. “When Is Capital
Enough to Get Female Microenterprises Growing? Evidence from a Randomized
Experiment in Ghana.” NBER Working Paper 17207, National Bureau of Economic
Research, Cambridge, MA.


Falco, P. 2012. “Does Risk Matter for Occupational Choices? Experimental Evidence
from an African Labour Market.” Working paper, Oxford University, Oxford, U.K.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and O. Gajigo. 2010. “Where Women Work: Empowerment
and Occupational Choice.” Working paper, World Bank, Washington, DC.


Honohan, P. 2004. “Financial Sector Policy and the Poor.” Working Paper 43, World Bank,
Washington, DC.


Johnson, S. 2004. “Gender Norms in Financial Markets: Evidence from Kenya.”
World Development 32: 1355–74.


Karlan, D., and J. Morduch. 2010. “Access to Finance.” In Handbook of Development
Economics, vol. 5, edited by D. Rodrik and M. Rosenzweig, 4703–84. Amsterdam:
North-Holland.


Karlan, D., and M. Valdivia. 2011. “Teaching Entrepreneurship: Impact of Business
Training on Microfi nance Clients and Institutions.” Review of Economics and Statistics
93 (2): 510–27.


Klapper, L., L. Laeven, and R. Rajan, 2006. “Entry Regulation as a Barrier to Entrepre-
neurship.” Journal of Financial Economics 82 (3): 591–629.


Klapper, L., and S. Parker. 2010. “Gender and the Business Environment for New Firm
Creation.” World Bank Research Observer, doi: 10.1093/wbro/lkp032.


Lusardi, A., and P. Tufano. 2009. “Debt Literacy, Financial Experiences, and Overin-
debtedness.” NBER Working Paper 14808, National Bureau of Economic Research,
Cambridge, MA.


McKenzie, D., and C. Woodruff . 2008. “Experimental Evidence on Returns to Capital
and Access to Finance in Mexico.” World Bank Economic Review 22 (3): 457–82.


Muravyev, A., D. Schäfer, and O. Talavera. 2007. “Entrepreneurs’ Gender and Financial
Constraints: Evidence from International Data.” Discussion Papers of DIW Berlin 706,
German Institute for Economic Research, Berlin.


Naidoo, S., and A. Hilton. 2006. Access to Finance for Women Entrepreneurs in South
Africa. Washington, DC: International Finance Corporation.


Narain, S. 2009. “Access to Finance for Women SME Entrepreneurs in Bangladesh.”
Working paper, World Bank, Washington, DC.


Pitt, M., S. Khandker, and J. Cartwright. 2003. “Does Micro-Credit Empower Women?
Evidence from Bangladesh.” Policy Research Working Paper 2998, World Bank,
Washington, DC.




206 ENTERPRISING WOMEN


Richardson, P., R. Howarth, and G. Finnegan. 2004. “Th e Challenges of Growing Small
Businesses: Insights from Women Entrepreneurs in Africa.” SEED Working Paper 47,
International Labour Organization, Geneva.


Women’s World Banking. 2009. “Microfi nance in Africa: Th e Challenges, Realities and
Success Stories.” MicroBanking Bulletin 17: 5–11.


World Bank. 2007. Finance for All? Policies and Pitfalls in Expanding Access. Washington, DC:
World Bank.




207


Chapter 9


Enriching Managerial and
Financial Skills


In their provocatively titled article “What Capital Is Missing in Developing
Countries?,” Bruhn, Karlan, and Schoar (2010b) answer “human capital,”
particularly managerial skills.


Th e importance of human capital has long been recognized. Th e dimension
that has received the lion’s share of attention is schooling or formal education.
However, when it comes to entrepreneurship, there are other dimensions that
can matter, too—as well as specifi c types of knowledge that may be important,
such as management skills, fi nancial literacy, and an aptitude for assessing risks
and making deals.


When looking at specifi c types of skills that are included in business training
programs, two questions stand out: Are such skills important in improving
performance? Are they skills that can be taught or acquired? Beyond that, it
is worthwhile to understand any nuances in the results: For example, are there
groups for which the skills are more important? Does one need a certain level
of education to benefi t from the training? Which types of outcomes are aff ected
by business or management training—does training encourage new entrepre-
neurs to start a business or improve the performance of those already running
a business?


Th is chapter cannot provide answers to all these questions. However, it looks
at results from the gender module and survey of new entrepreneurs to quali-
tatively assess the prevalence of a broader set of human capital measures and
their association with performance outcomes. It fi nds that women have lower
levels of a broad range of measures of human capital on average (consistent with
gender gaps in education, discussed in chapters 3 and 4). But education and
managerial skills seem to have important eff ects for both women and men—and
the marginal returns to women of the underlying skills are no diff erent from
those for men.


It is not just that women benefi t as much as men from managerial
and fi nancial skills. Both groups also benefi t from experience, through
having had former employment in the formal sector, exposure to running




208 ENTERPRISING WOMEN


a business, or a parent who was an entrepreneur. Th at there is a gender gap
in this last eff ect shows that some teaching needs to be targeted to ensure
that women are included.  It also implies that as more women become
successful  entrepreneurs, a more virtuous cycle may be created for their
daughters, too.


Th e chapter shows that four management techniques had a signifi cant
eff ect on productivity among fi rms sampled in Ghana, Mali, Mozambique,
Senegal, and Zambia. Gender differences were not apparent for two
techniques (establishing formal objectives and monitoring employee
performance),  but  they  were seen in the other two (process innovation
and participatory decision making). Male entrepreneurs scored signifi -
cantly higher than female entrepreneurs in process innovation, but the
reverse was  true  in  participatory decision making (Gajigo and Hallward-
Driemeier 2010).


Th e motivation for being an entrepreneur, as discussed in chapter  4,
does not have striking gender patterns. As many women as men iden-
tify opportunity-related reasons for being an entrepreneur. What does
stand out, however, is how little correlation motivation has with actual
performance. Self-reporting aft er the event is a poor measure of potentially
higher-growth businesses; being an employer rather than self-employed
and being in the formal sector are better predictors of performance.
Skills, not motivation, seem to be the most important dimension of human
capital.


Evidence from randomized impact evaluations regarding programs that
aim to teach specifi c business and fi nancial skills indicates that the skills to
increase business knowledge can be taught, but fails to show unambiguously
that these skills improve business outcomes. Th e method of teaching itself
matters, as does participants’ initial level of business knowledge (see for exam-
ple Bruhn, Karlan, and Schoar 2010a; Karlan and Valdivia 2011; Mansuri and
Giné 2011).


Th e literature examining the effi cacy of providing business training, credit,
or a combination of the two fi nds the combination is more oft en signifi cant than
either one alone. Simply having more knowledge of how to use credit wisely is
not very eff ective at improving business outcomes where there are few fi nancial
resources available. And credit without fi nancial management skills is a risky
bet for both the borrower and the lender. Clearly there is a symbiosis between
strengthening the human capital of women entrepreneurs and expanding their
access to fi nancial services. Better human capital can improve business per-
formance directly, and can improve it indirectly by making the entrepreneur
more creditworthy, thus expanding the opportunities available. But there is still
a question of whether women can benefi t from this symbiosis as much as men
can (Coleman 2007).




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 209


Managerial Skills


Economic growth models have long recognized the importance of human
capital, taking the contribution of labor into account as a key input (Solow
1956, for example). Th e endogenous growth literature incorporated the
quality of that labor, including managerial quality as a factor of production
(Aghion and Howitt 1992; Baumol 1968; Lucas 1978; Romer 1990). Th e
empirical work on capturing the quality of human capital lagged in moving
beyond measures of formal education, but it has recently made progress in
two directions.


First, it has produced better measures of human capital, particularly
of managerial skills, which are then related to fi rm performance (see, for
example, Bloom and Van Reenen 2007, 2010). Second, drawing on some
of the insights of the fi rst approach, the empirical work has gone beyond
correlations to test the importance of specifi c skills through randomized
interventions (see,  for example, Bloom and others 2010; Drexler, Fischer,
and Schoar 2010).


Education as a Key Driver of Performance
Th e positive eff ect of education on enterprise productivity is one of the most
robust fi ndings in the literature (Bates 1990; Burki and Terrell 1998; Cohen and
House 1996; McPherson 1995). Th is is unsurprising, given education’s enhance-
ment of the quality of services by the entrepreneur, and given that worker pro-
ductivity also benefi ts from it. Education can also signal other qualities among
entrepreneurs, such as discipline, motivation, versatility in dealing with new
challenges, and other attributes that could lower transaction costs for numerous
entrepreneurship-relevant activities.


In Sub-Saharan Africa, analyses of surveys of both new and incumbent
entrepreneurs fi nd education to be a signifi cant determinant of revenue per
worker (Aterido and Hallward-Driemeier 2010). Entrepreneurs with at least
secondary education and some vocational training have signifi cantly higher
revenue per worker than those with no education. Primary education has no
more eff ect than no schooling (see fi gure 9.1).


Controlling for other characteristics of the enterprise, women entre-
preneurs do not have fewer years of education than men. Nor are the
diff erences in productivity that are associated with higher education statisti-
cally diff erent for women and men in the same sector and with enterprises
of the  same size. Women  may  have less education overall, but those who
receive it get as much benefi t from it as their male colleagues by running more
productive fi rms.


Th ese fi ndings are consistent with other fi ndings in the literature on
the eff ect of education on enterprise productivity in developing countries




210 ENTERPRISING WOMEN


(Bigsten and Söderbom 2006; Mead 1991). In a study of small enterprises in
southern Africa, McPherson (1995) found that education is one of the most
signifi cant determinants of growth in several countries. Bigsten and others
(2000) found signifi cant and increasing returns to human capital, both for
education and experience, in large samples of enterprises in fi ve countries in
the region.


As seen in earlier chapters, more-educated entrepreneurs tend to run larger,
older, and exporting enterprises. Education is also associated with having
registered at start-up and being affi liated with other enterprises. On the motiva-
tion for being an entrepreneur, education is associated with opportunity rather
than necessity. As discussed below, education is also associated with greater use
of some management techniques.


Measuring Managerial Skills
Bloom and Van Reenen (2010) set out to quantify a set of particular manage-
rial capabilities, based on interviews with senior managers. Th ey found their
indexes varied substantially across fi rms in ways associated with outcomes,


Figure 9.1 The Effect of Education on Productivity Is the Same for Women as for Men


Source: Hallward-Driemeier and Rasteletti 2010.
Note: The figure is based on regression of the log of revenue per worker and controls for firm age, formality,
industry, and country effects using the database of national household and labor force surveys for 101 low- and
middle-income economies, most recent years (2000–10). The reference school category is those with primary or
no schooling. The differences across men and women within the same educational category are not statistically
different.


0


10


20


30


40


50


60


70


80


90


100


Secondary
school


Vocational
training


Some
university


DegreeP
ro


du
ct


iv
it


y
ga


in
o


ve
r


th
os


e
w


it
h


pr
im


ar
y


or


le
ss


e
du


ca
ti


on
(p


er
ce


nt
)


FemaleMale




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 211


and that the average of the indicators varied across countries—management
quality, particularly, was lower in developing countries.


Building on that work and using a smaller set of indicators, Aterido and
Hallward-Driemeier (2011) found that management techniques have a
signifi cant productivity eff ect on fi rms in Ghana, Mali, Mozambique, Senegal,
and Zambia. Th at study considered the following four management techniques:


• Establishing formal objectives: consistently making and following through
on formal goals


• Monitoring employee performance: systematically keeping track of employee
performance and ensuring the aligning of incentives with fi rm performance


• Engaging in process innovation: consistently trying to improve enterprise
product


• Engaging in participatory decision making:1 including staff in the
decision-making process


Th e eff ects of each of these components on productivity were assessed sepa-
rately and jointly through a composite index.


Aterido and Hallward-Driemeier (2011) found no gender diff erences in
establishing formal objectives and monitoring employee performance, but
saw signifi cant diff erences in process innovation and participatory decision
making. Male entrepreneurs score signifi cantly higher than female entrepre-
neurs in process innovation, though the situation reverses for participatory
decision making. Th e eff ect of management practice on productivity is robust
to numerous individual and enterprise characteristics, with no signifi cantly
diff erent gradient by gender. Th us all the management techniques were found
to be signifi cantly correlated with productivity—and women entrepreneurs
benefi ted from them as much as their male colleagues.


Th e study also found that the use of better management techniques is signifi -
cantly correlated with higher productivity. Women are slightly less likely to use
them, but as with education more broadly, those who did use them benefi ted
as much as men. Th ese results are robust to including the entrepreneur’s age,
education, and prior work experience. Th us management skills provide addi-
tional benefi ts beyond more general education and work experience, with
returns similar for women and men.


Th e surveys of new entrepreneurs also gathered information on manage-
ment techniques, specifi cally whether business objectives are recorded in
writing, and whether formal records are kept (fi gures 9.2 and 9.3). Gajigo and
Hallward-Driemeier (2010) found that diff erences due to gender are small rela-
tive to those due to sector. Th ey depend largely on education, particularly for
the use of formal written records.




212 ENTERPRISING WOMEN


Financial Skills


To properly evaluate risk and opportunities among competing options, entre-
preneurs need to understand certain key fi nancial concepts. Financial literacy
is obviously indispensable for activities directly relevant to business operations,
such as keeping track of expenses and revenues, appreciating the advantages
and disadvantages of loan contracts, and deciding whether to make an invest-
ment or hire another employee. And it is important even in areas not directly
related to entrepreneurship.2 Given that entrepreneurs need to plan in many
ways, including saving before starting an enterprise, fi nancial literacy is crucial
for them.


Financial literacy can encompass many variables, but it should
certainly include some conception of interest rates and infl ation. Without
such  an  understanding, the ability to evaluate values over time would
be limited.


Figure 9.2 Whether Business Objectives Are Recorded in Writing Varies Primarily by Sector
and Only Secondarily by Gender


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


25


50


75


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


w
it


h
w


ri
tt


en


bu
si


ne
ss


o
bj


ec
ti


ve
s




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 213


Th e surveys of new entrepreneurs asked two questions to assess fi nancial
literacy:3


Let’s assume that you deposited K Sh 1,000 in a bank account for fi ve years
at 10 percent interest. Th e interest rate will be earned at the end of each
year and will be added to the principal. How much money will you have in
your account in fi ve years if you do not withdraw either the principal or the
interest [more than K Sh 1,500, exactly K Sh 1,500, or less than K Sh 1,500]?


Let’s imagine that the interest rate on your savings account in a bank was
1 percent per year and prices were rising at 2 percent per year. Aft er one
year, would you be able to buy [more than today, exactly the same, or less than
today] with the money in this bank account?


About 35 percent answered the fi rst question correctly, 23 percent answered
the second correctly, and only 7 percent answered both correctly. Gender was
not signifi cant, once education was controlled for. Education was the biggest
predictor of whether the respondent answered correctly, more than enterprise
formality or size.


Th ese fi ndings make clear that signifi cant work is still needed to expand
even rudimentary knowledge of fi nancial concepts to those who could benefi t
from them in running a business. Th ey also caution against simply expanding


Figure 9.3 Formal Records Are More Likely to Be Kept among Formal Enterprises, with
Little Gender Gap


Source: Gajigo and Hallward-Driemeier 2010.
Note: Data are for newly established enterprises in Côte d’Ivoire, Kenya, Nigeria, and Senegal.


0


10


20


30


40


50


60


70


80


90


100


Male Female Male Female


Formal Informal


Pe
rc


en
ta


ge
o


f e
nt


er
pr


is
es


k
ee


pi
ng



fo


rm
al


b
us


in
es


s
re


co
rd


s




214 ENTERPRISING WOMEN


access to fi nancial products without giving people more information to assess
the true costs and benefi ts of these products, including the risks associated with
assuming credit.


Does an entrepreneur’s greater understanding of fi nancial concepts make a
diff erence to a fi rm’s performance? Yes. Financially literate entrepreneurs have
10–15  percent higher labor productivity on average (Gajigo and Hallward-
Driemeier 2010), though once the analysis controls for education, this diff er-
ence becomes insignifi cant. So fi nancial literacy is important for enterprise
productivity largely to the extent that it is correlated with other variables that
enhance productivity.


Entrepreneurial Skills: Experience and Motivation


Th e surveys of new entrepreneurs show that years served as a formal-fi rm
employee and as an apprentice are signifi cantly associated with current enterprise
productivity (controlling for size, industry, and registration status). Th e impact of
prior experience is not signifi cantly diff erent for female and male entrepreneurs.
Years served as a nonenterprise employee (for example, as a teacher or nurse) is,
however, signifi cantly associated with lower productivity among female but not
male entrepreneurs (Gajigo and Hallward-Driemeier 2010).


Can a Family Background in Entrepreneurship Provide
Useful Experience?
A related question is whether entrepreneurs have gained some experience (in
a wider sense) from having grown up in a family where a parent was an entre-
preneur. Studies from other countries point to this as an important predictor of
who becomes an entrepreneur, particularly among those with other employment
options available (Djankov and others 2005, 2006). While those studies found a
particular role for having a mother who was an entrepreneur, the surveys from
Sub-Saharan African countries include too few mothers in the sample, so the
analysis focuses on the impact of a father who was an entrepreneur. Indeed,
a positive association with current productivity is evident—but only for sons,
not daughters. Th e sons report having received mentoring and introductions to
networks of business contacts from their entrepreneur fathers; fewer daughters
report having received them (Aterido and Hallward-Driemeier 2011).


Policy levers to address this gender diff erence seem limited. Still, measures
that could expand female entrepreneurship today might well provide the role
models and business networks for even more women to be entrepreneurs in
the future.


Another potential impact of family background involves the eff ect of acquir-
ing a business that has been in one’s family. Th e literature has focused on this




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 215


issue in the context of families with extensive holdings, where “dynastic”
ownership and management can be ineffi cient if later generations do not have
the same business skills as earlier (Bennedsen and others 2007; Bertrand and
Schoar 2006; Bertrand and others 2008; Caselli and Gennaioli 2005). We made
two comparisons. First, for those who became an entrepreneur by acquiring an
existing business, we looked at whether it matters if the acquired business was
a family business connected to the entrepreneur or a business with no prior
ownership links to the entrepreneur or his or her family. Indeed, we fi nd the
former are more productive. Second, we compared the productivity of newly
acquired family businesses with enterprises that were started from scratch. Here
we fi nd the new businesses are more productive than acquired family busi-
nesses. Th e same pattern is found among the larger population of enterprises
(Gajigo and Hallward-Driemeier 2010).


Th e mode of acquisition has greater implications for men’s productivity;
women show no diff erence based on how the business was acquired or whether
it was a new venture. Th e new start-ups owned by men appear to be the most
productive category. It is true that fewer women acquire existing family busi-
nesses, but to the extent such businesses bring with them an established network
of suppliers and customers, this advantage does not seem to be passed on to the
women in the family. Th is fi nding provides a similar message to that of an entre-
preneur father benefi ting sons rather than daughters.


One alternative family connection that appears to benefi t women is having
a husband who is also an entrepreneur. Th is may be because many businesses
are jointly run by husbands and wives, and such family businesses may operate
more effi ciently than one run by either spouse alone.


Productivity and Motivation Diff erences in Opportunity and
Necessity Entrepreneurs
One would expect opportunity entrepreneurs to be more productive than
necessity entrepreneurs because their motivation for starting a business was
exploiting a market opportunity. Surprisingly, this is not the case. Among the
entrepreneurs in the surveys of new entrepreneurs in Côte d’Ivoire, Kenya,
Nigeria, and Senegal, those who cited motivations—such as spotting high
profi t potential, recognizing some form of market opportunity, witnessing an
inspiring case, possessing business skills, or claiming special knowledge of their
product line—are no more productive when one controls for other individual
and enterprise variables. Th is fi nding is similar to the fi nding in Aterido and
Hallward-Driemeier (2011) that those who claimed to pursue market oppor-
tunities did not have signifi cantly higher productivity than others. Th ose who
say they chose entrepreneurship out of a desire to have greater time fl exibility
show signifi cantly lower profi tability, and this eff ect is stronger among female
entrepreneurs.




216 ENTERPRISING WOMEN


If characteristics of the entrepreneur are not controlled for, the analysis
reveals a 16 percent labor productivity defi cit for necessity entrepreneurs rela-
tive to opportunity entrepreneurs (Gajigo and Hallward-Driemeier 2010). (Th e
defi cit has no gender dimension.) When variables such as education, sector,
and country fi xed eff ects are controlled for, the productivity gap is no longer
signifi cant.


An alternative approach to looking at productivity is to divide entrepreneurs
by their aspirations—to explore whether those who set more ambitious targets
might also exert greater eff ort and achieve better results. Th e results show that
only those entrepreneurs who claim “being in business for the next 10 years” as
a criterion for success show signifi cantly higher labor productivity. And there is
no signifi cant gender diff erence in the importance of this criterion, controlling
for other enterprise characteristics; women and men both report being commit-
ted to having their enterprise be a longer-run venture.


Th is fi nding, which suggests that self-reported assessments of the motivation
or goal for the business are a poor indicator of the true potential of a business,
may simply refl ect weaknesses in the survey approach. For example, respon-
dents may not wish to give answers indicating that they did not choose a certain
pathway for themselves. Equally, those who would otherwise be unemployed
are likely to be motivated to make the most of the opportunity that they have.


Th e desire to separate necessity from opportunity entrepreneurs is under-
standable, since it would help programs targeting high-potential businesses to
become more effi cient. But basing the categories on self-reported answers is not
very informative. Th e distinction between the self-employed and employers,
though not perfect, may be a better proxy for analyzing the two groups.


What Kind of Entrepreneurial Training Is Effective—
And for Whom?


A growing line of research investigates the importance of business and fi nan-
cial skills through randomized interventions. It seeks to better identify the
causal links, separating out possible selection eff ects (more successful entre-
preneurs might be more likely to enroll in training in the fi rst place). Studies
analyze a variety of training methods and substantive content of the programs.
Heterogeneous eff ects across individuals, particularly by initial level of fi nancial
literacy, are examined, highlighting the fact that the eff ectiveness of programs
can vary across the range of entrepreneurs.


Th e level of missing managerial capital can be evident, even among larger
fi rms. Some studies show large, if somewhat “noisy,” impacts of more-tailored
knowledge initiatives, including those providing consulting services. Bruhn,
Karlan, and Schoar (2010a) did a randomized experiment where entrepreneurs




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 217


running small fi rms were given access to consulting services. Th e eff ects on
sales and productivity were signifi cant. A study in India (Bloom and others
2010), looking at somewhat larger textile fi rms, also found a large jump in pro-
ductivity for those receiving consulting services. Given the large returns that far
outweighed the market costs of these services, there is something of a puzzle
concerning why fi rms are not seeking them. It may well be that they under-
estimate the benefi ts of the services, that they do not have access to fi nance
suffi cient to pay for them, or that creditors are unwilling to lend for an invest-
ment that cannot be collateralized.


Th e training does not need to be complex, however, depending on the
target audience. Indeed, simple “rules of thumb” can have greater impact on
outcomes—for less educated entrepreneurs. Drexler, Fischer, and Schoar (2010)
fi nd in the Dominican Republic that a “rules of thumb” approach to training in
business skills had a larger impact for less educated entrepreneurs than more
traditional training in accounting. Th e result underscores the importance of
tailoring training to the group served—and of clarifying even very basic busi-
ness management ideas, such as keeping separate the accounts and fi nances of
the business and of the household. It also indicates that more traditional educa-
tion in the mechanics of record keeping is not particularly eff ective in this group
of entrepreneurs.


Bruhn and Zia (2011) evaluate a program in Bosnia and Herzegovina
that provides training to existing bank clients. An entrepreneur’s initial level
of fi nancial literacy is a strong predictor of initial business performance.
Th e  training did raise scores on the tests of fi nancial literacy, particularly for
those whose initial scores were low. It also led to greater take-up of fi nancial
services. Th e study shows, however, weak impact in spurring those who did
not already have a business to start one, nor did it predict subsequent survival.
While these improved fi nancial literacy skills are unlikely to be driving entry
and exit decisions, there was an eff ect on increasing sales and profi ts— strikingly,
particularly for those who began with higher levels of fi nancial literacy.


Karlan and Valdivia (2011) examine classroom training for preexisting
microenterprise clients of a microfi nance program in Peru. All participants in
the particular study were female. As participants in the microfi nance program,
they had access to small loans. Th e focus of the training was on basic business
skills and record keeping. Although business knowledge was found to increase
as a result of receiving the training, the results for business outcomes (revenue,
profi ts, or employment) did not change signifi cantly. Still, there is suggestive
evidence that revenues fell by less during “bad months” aft er the training than
they had before it.


However, neither human nor fi nancial capital is a magic bullet, particularly
if there are deeper constraints at work. A study in Pakistan fi nds that business
training leads to better business knowledge, and subsequently better business




218 ENTERPRISING WOMEN


practices and improvements in some household outcomes (Mansuri and Giné
2011). Th e benefi ts of the program appear to be restricted to male participants,
however. Th at could be due to the lower education and initial level of business
knowledge of the women. Or given the extent of the gender-segregated labor
market, more women could likely be necessity entrepreneurs rather than oppor-
tunity entrepreneurs, facing greater constraints in operating their business.


Exploiting Synergies between Human and Financial Capital


While Bruhn, Karlan, and Schoar (2010b) maintain that human capital is
the critical missing source of capital in developing countries, more oft en the
answer is not either fi nancial or human capital alone; the two types oft en com-
plement, rather than substitute for, one another. Indeed, while recognizing that
neither is a magic bullet, combining business training and access to credit is
more oft en signifi cant than either on its own. It is when credit is extended
that knowledge about how to use it—and how not to—can be most valuable.
Having knowledge, but not the resources to translate it into practice, will erode
its eff ectiveness.


On a deeper level, the synergies between types of capital hold when creditors
are deciding to whom they will provide credit. Candidates with better skill sets
are more likely to get credit; having the richer human capital makes them a bet-
ter risk for creditors. Th is fact also implies that the agenda for expanding skills
is a fundamental part of expanding opportunities, including expanding access
to fi nance, as discussed in the previous chapter.


Human capital expands opportunities. Ensuring women can develop their
skills is critical in aff ecting their choice of enterprise and the extent of gender
sorting across activities. But simply providing training is not enough. Neither
is just providing fi nance. Entrepreneurs must know what to do with these
resources, have a good business idea, and have access to markets. Th e services
provided need to fi t their needs—and their abilities. Not everyone will be a suc-
cessful entrepreneur, but many fewer will be successful without access to capital,
human or fi nancial.


Notes
1. Bloom and others (2010) built into each indicator measures of the frequency of


its use and how participatory the practice was. Aterido and Hallward- Driemeier’s
(2011) measures do give higher scores for more frequent use of the practice.
However, in that work, the participatory nature of the practices is separated out and
the importance of participatory management is tested for directly.


2. For example, it is hard for entrepreneurs to assess whether the savings from income
is enough for longer-run plans (investment or retirement) unless they understand




ENRICHING MANAGERIAL AND FINANCIAL SKILLS 219


interest rates and infl ation. Lusardi and Mitchell (2007) have shown that certain
types of economic and fi nancial literacy have a large eff ect on saving and investment,
in turn aff ecting retirement outcomes.


3. Amounts and currency were adapted to countries to refl ect the currency used and
to show a “normal” amount in a round fi gure that would facilitate the calculations.
Th e questions are not intended to test computational skills as much as the concepts
of compounding interest and real purchasing power.


References
Aghion, P., and P. Howitt. 1992. “A Model of Growth through Creative Destruction.”


Econometrica 60 (2): 323–51.
Aterido, R., and M. Hallward-Driemeier. 2010. “Th e Impact of the Investment Climate


on Employment Growth: Does Sub-Saharan Africa Mirror Other Low-Income
Regions?” Policy Research Working Paper 5218, World Bank, Washington, DC.


. 2011. “Whose Business Is It Anyway?” Small Business Economics 37 (4): 443–64.
Bates, T. 1990. “Entrepreneur Human Capital Inputs and Small Business Longevity.”


Review of Economics and Statistics 72 (4): 551–59.
Baumol, W. 1968. “Entrepreneurship in Economic Th eory.” American Economic Review


58 (2): 64–71.
Bennedsen, M., F. Perez-Gonzalez, K. Nielsen, and D. Wolfenzon. 2007. “Inside


the Family Firm: Th e Role of Families in Succession Decisions and Performance.”
Quarterly Journal of Economics 122 (2): 647–91.


Bertrand, M., S. H. Johnson, K. Samphantharak, and A. Schoar. 2008. “Mixing Family
with Business: A Study of Th ai Business Groups and the Families behind Th em.”
Journal of Financial Economics 88: 466–98.


Bertrand, M., and A. Schoar. 2006. “Th e Role of Family in Family Firms.” Journal of
Economic Perspectives 20: 73–96.


Bigsten, A., P. Collier, S. Dercon, M. Fafchamps, B. Gauthier, J. Gunning, A. Oduro,
R. Oostendorp, C. Pattillo, M. Söderbom, F. Teal, A. Zeufack, and S. Appleton. 2000.
“Rate of Return on Human and Non-Human Capital in Africa’s Manufacturing
Sector.” Economic Development and Cultural Change 48 (4): 801–27.


Bi gsten, A., and M. Söderbom. 2006. “What Have We Learned from a Decade of
Manufacturing Enterprise Surveys in Africa?” World Bank Research Observer 21 (2):
241–65.


Bloom, N., B. Eifert, A. Mahajan, D. McKenzie, and J. Roberts. 2010. “Does Manage-
ment Matter? Evidence from India.” NBER Working Paper 16658, National Bureau of
Economic Research, Cambridge, MA.


Bloom, N., and J. Van Reenen. 2007. “Measuring and Explaining Management Practices
Across Firms and Countries.” Quarterly Journal of Economics 122 (4): 1351–408.


. 2010. “Why Do Management Practices Diff er Across Firms and Countries?”
Journal of Economic Perspectives 24 (1): 203–24.


Bruhn, M., D. Karlan, and A. Schoar. 2010a. “Th e Impact of Off ering Consulting Services
to Small and Medium Enterprises: Evidence from a Randomized Trial in Mexico.”
Working paper, World Bank, Washington, DC.




220 ENTERPRISING WOMEN


. 2010b. “What Capital Is Missing in Developing Countries?” American Economic
Review 100 (2): 629–33.


Bruhn, M., and B. Zia. 2011. “Stimulating Managerial Capital in Emerging Markets: Th e
Impact of Business and Financial Literacy for Young Entrepreneurs.” Working paper,
World Bank, Washington, DC.


Burki, A. A., and D. Terrell. 1998. “Measuring Production Effi ciency of Small Firms in
Pakistan.” World Development 26 (1): 155–69.


Caselli, F., and N. Gennaioli. 2005. “Dynastic Management.” Journal of the European
Economic Association 3 (2–3): 679–89.


Cohen, B., and W. J. House. 1996. “Labor Market Choices, Earning, and Informal
Networks in Khartoum, Sudan.” Economic Development and Cultural Change 44 (3):
589–618.


Coleman, S. 2007. “Th e Role of Human and Financial Capital in the Profi tability and
Growth of Women-Owned Small Firms.” Journal of Small Business Management 45
(3): 303–19.


Djankov, S., E. Miguel, Y. Qian, G. Roland, and E. Zhuravskaya. 2005. “Who Are Russia’s
Entrepreneurs?” Journal of the European Economic Association 3 (2–3): 587–97.


Djankov, S., Y. Qian, G. Roland, and E. Zhuravskaya. 2006. “Who Are China’s Entrepre-
neurs?” American Economic Review 96 (2): 348–52.


Drexler, A., G. Fischer, and A. Schoar. 2010. “Keeping It Simple: Financial Literacy and
Rules of Th umb.” CEPR Discussion Paper 7994, Centre for Economic Policy Research,
London.


Gajigo, O., and M. Hallward-Driemeier. 2010. “Entrepreneurship among New Entrepre-
neurs.” Working paper, World Bank, Washington, DC.


Hallward-Driemeier, M., and A. Rasteletti. 2010. “Women’s and Men’s Entrepreneurship
in Africa.” Working paper, World Bank, Washington, DC.


Karlan, D., and M. Valdivia. 2011. “Teaching Entrepreneurship: Impact of Business
Training on Microfi nance Clients and Institutions.” Review of Economics and Statistics
93 (2): 510–27.


Lucas, R. E. Jr. 1978. “On the Size Distribution of Business Firms.” Bell Journal of
Economics 9 (2): 508–23.


Lusardi, A., and O. S. Mitchell. 2007. “Baby Boomer Retirement Security: Th e Roles of
Planning, Financial Literacy and Housing Wealth.” Journal of Monetary Economics 54
(1): 205–24.


Mansuri, G., and X. Giné. 2011. “Money or Ideas? A Field Experiment on Constraints to
Entrepreneurship in Rural Pakistan.” Working paper, World Bank, Washington, DC.


McPherson, M. 1995. “Growth of Micro and Small Enterprises in Southern Africa.”
Journal of Development Economics 48: 253–77.


Mead, D. C. 1991. “Review Article: Small Enterprises and Development.” Economic
Development and Cultural Change 39 (January): 409–20.


Romer, P. 1990. “Endogenous Technical Change.” Journal of Political Economy 98: 71–102.
Solow, R. M. 1956. “A Contribution to the Th eory of Economic Growth.” Quarterly


Journal of Economics 70 (1): 65–94.




221


Chapter 10


Strengthening Women’s Voices
in Business-Environment Reforms


As other chapters in this study show, women are important economic actors
in Africa’s private sector, and their experiences of legal, regulatory, and
administrative barriers to business tend to be diff erent from those of their male
counterparts. Women’s experiences also diff er from men’s in that women are
largely excluded from policy making in the private sector—and even from many
of the mechanisms and instruments for promoting public-private dialogue
(PPD), which has been developed to facilitate interactions between representa-
tives of the business community and government decision makers. More still
needs to be done to promote gender inclusion and to make space for identifying
and tackling business-environment issues of interest to women.


Such exclusion and underrepresentation are costly, not just to individual
women and their businesses, but to the economy. As this and other studies
show, Sub-Saharan Africa has considerable hidden growth potential in its
women. Tapping that potential—by removing barriers at entry and empower-
ing women economically through access to and control of resources—can make
a huge diff erence to Africa’s growth and poverty reduction. Bringing women’s
voices into PPD and other dialogue mechanisms is at the core of establishing
and sustaining a business environment that is favorable to women and that
creates opportunities for all.


Women’s business associations provide a platform to advocate women’s
business interests. But many of them are not involved in mainstream dialogue
and advocacy, and many lack the capacity and experience to pursue such work
eff ectively.


What is encouraging, however, is that more attention is gradually being
paid to understanding and addressing the gender dimensions of the business
environment—and to developing practical guidance to tackle gender issues in
business-environment reform (Simavi, Manuel, and Blackden 2010).1 Some ini-
tiatives are amplifying the voices of women entrepreneurs in policy making,
such as the Africa Businesswomen’s Network and its affi liated country-based
networks of women’s business associations.




222 ENTERPRISING WOMEN


Th is chapter focuses on the experience of women in making their voices
heard in business and looks at how they can participate in, and inform, policy
making for business and entrepreneurship. It reviews some PPD mechanisms
for private and public actors to defi ne and implement business-environment
reforms. It also looks at the representation of men and women in business
associations and other forums promoting dialogue and partnership around
policy making for business and entrepreneurship.


Why Focus on Women’s Voices?


Investment-climate reform that enables women, as well as men, to become
more productive businesspeople and to stimulate economic development must
address challenges faced by both men and women. It is more likely to do so if
women are full participants in policy discussions and reform eff orts. Th e eff ec-
tiveness of women’s voices also depends partly on the extent to which solid,
gender-informed, and sex-disaggregated analyses are available to inform policy
debates.


Two sets of issues are important for strengthening women’s voices in making
business policy. Th e fi rst is women’s participation in the policy arena—that is,
having women at the table where decisions are made. Th e second is women’s
role in setting the agenda discussed at the table, and in framing the policy
debate. Th ese two issues are discussed below in the context of business associa-
tions and other mechanisms designed to bring the private and public sectors
together in reforming the business environment.


Business associations have traditionally been a means to expand business
networks, but they can also lobby for particular policies. Of course, other advo-
cacy mechanisms, including those promoting women’s legal rights and human
rights more generally, can strengthen women’s property rights and, by extension,
their capacity to engage in economic and entrepreneurial activity. Underlying
any eff orts to integrate gender considerations into business-environment reform
is the need for solid empirical analysis so that a fuller understanding of gender
roles and gender-based constraints can inform policy choices.


Th is chapter reviews a specifi c PPD model developed by the International
Finance Corporation (IFC) to increase the private sector’s participation in
policy making. In doing so, it illustrates more generally the challenges of, and
potential for success in, giving women a greater role in advocacy and policy
reforms in areas of importance to business.


Underlying the two sets of issues—bringing more women to the table and
having issues important to women on the agenda—is a debate over whether it
is better for women to work through parallel structures focused on women, or
to seek stronger integration into mainstream mechanisms of policy dialogue




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 223


and business associations. Should women encourage more women’s business
associations? Or should they promote greater female participation in existing
business associations?


Similarly, should the agenda focus on issues specifi c to women in business
(a gender perspective)? Or should women expand the ways they participate
in, and contribute to, advocacy on issues that are not gender specifi c but are of
importance to business more generally? Th e review of experience shows where
each can be eff ective. A dual-track approach—separate women’s mechanisms
and better integration into the mainstream—is oft en required.


Grounding Policy Advocacy in Gender-Informed Analysis


Advocacy for policy reforms needs to be grounded in solid, country-specifi c
analysis of the opportunities and constraints in the business environment and,
specifi cally, of the ways these opportunities and constraints diff er for men and
women.


Th e lack of sex-disaggregated data on business activity and entrepreneur-
ship and a corresponding absence of gender-informed analysis have until now
made it hard to identify the nature and extent of gender-based barriers in the
business environment—and to develop ways to address them. Th is situation is
changing. Indeed, one of the objectives of this book is to fi ll a gap in this area.
But much more gender-informed and sex-disaggregated data and analysis are
needed.


A gender-informed analysis of investment-climate obstacles provides the
essential underpinning needed to identify, and advocate for, specifi c legal and
regulatory reforms. Recent years have seen several gender-focused analyses of
those obstacles in several African countries, including Ghana, Kenya, Rwanda,
Tanzania, and Uganda (Ellis, Blackden, and others 2007; Ellis, Cutura, and
others 2007; Ellis, Manuel, and Blackden 2006; IFC 2007a, 2007b). Similar
studies have been carried out in various Pacifi c island countries (for example,
Bowman and others 2009; Hedditch and Manuel 2010).


Drawing on broad analysis of the legal environment and links between
gender inequality and economic growth, these assessments focused on regula-
tory and administrative barriers to business registration, operation, and closing;
business licensing and taxation; access to land and fi nance; access to justice; and
issues in particular sectors. Th e studies identifi ed gender-based diff erences in
the application of business regulations and proposed specifi c regulatory reforms
to address them.


In conjunction with these detailed studies of the legal and regulatory envi-
ronment aff ecting women in business, the International Finance Corporation
also undertook its “Voices of Women Entrepreneurs” series, with works on




224 ENTERPRISING WOMEN


Ghana (IFC 2007a), Kenya (IFC 2006b), Rwanda (IFC 2008), and Tanzania
(IFC 2007b).2 By providing examples of women in business who have expe-
rienced the obstacles identifi ed in the technical analyses, the “Voices” studies
had an explicit purpose of supporting advocacy eff orts around specifi c reforms.


Th ese reports show how women perceive the business environment and the
obstacles they face. Th ey reveal both the importance of networking and the
problems women face in seeking to network—problems that make it harder
for women to develop new opportunities, build a customer base, and expand
markets. Consistent across all countries are problems associated with balancing
work and family obligations, the need to deal with complex (and oft en time-
consuming) regulations, the higher probability that women will be subject to
harassment and discrimination by public servants and offi cials overseeing com-
pliance with business regulations, and access to fi nance. Still, in diff erent ways
and to diff ering degrees, women in some countries have broken down barri-
ers and stereotypes and are working in nontraditional sectors—for example,
computer manufacturing in Rwanda, petroleum distribution and transport in
Kenya, and the emerging information and communication technology sector
in Ghana.


Th e gender assessments provide a foundation for defi ning reforms respon-
sive to women’s concerns. For people to be eff ective advocates on gender issues,
capacity building may be needed to extend their skills to investment-climate
issues. Conversely, organizations representing business interests to government
may require capacity building to improve their understanding of gender issues
in business. In Uganda, a gender coalition was set up to lobby for the assess-
ment’s recommendations, and it achieved some success in carrying out legal and
regulatory reform (box 10.1). It needed skills in commercial law to take full part
in the policy debate.


Having the knowledge and analysis is an important step toward getting
issues on the policy agenda. Women still need a seat at the table, however.


Women and Business Associations


Strengthening women’s participation in business associations is important
for greater inclusion of women and gender issues in business-related deci-
sions. Strengthening the capacity of women’s business associations to advocate
and lobby for business-environment reforms—not yet a sharp focus—is also
important.


Advantages of Business Associations
Th e advantages of business associations are clear. Th ey facilitate the networking
that helps members share market information, identify business opportunities,




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 225


BOX 10.1


Uganda Gender Coalition: Using Gender Analysis to Lobby
for Change
Uganda’s Ministry of Finance, Planning, and Economic Development asked the IFC to
assess the country’s investment climate through a gender lens. The resulting analysis
and recommendations were published as part of Uganda’s Gender and Growth Assess-
ment (GGA) (Ellis, Manuel, and Blackden 2006). A GGA team from the IFC followed up
with a two-day workshop on advocacy and public-private dialogue. During the work-
shop a gender coalition was formed to take the recommendations forward through
lobbying and advocacy.


The coalition comprises seven core civil society organizations: the Uganda Investment
Authority, Private Sector Foundation Uganda, Council for Economic Empowerment for
Women in Africa–Uganda Chapter, Uganda Association of Women Lawyers, Uganda
Women Entrepreneurs Limited, Uganda Women’s Network, and African Women’s
Economic Policy Network. Members have focused on thematic areas identifi ed by
the GGA, drawing on their area of technical expertise. Legal and regulatory reform is
complex and time-consuming, with impacts occurring over several years, but some posi-
tive results have already emerged:


• GGA recommendations were incorporated in Uganda’s Private Sector Development
Strategy 2005–2009, the National Gender Strategy 2005–2014, and the National
Development Plan 2010–2020.


• Following lobbying from the coalition, GGA recommendations were incorporated
in four labor law bills: the Employment Bill, the Occupational Safety and Health Bill,
the Labour Dispute Bill, and the Labour Unions Bill. The bills were passed in March
2006, and the president gave his assent. Uganda is now recognized in the World
Bank’s (2007) Doing Business report as the seventh-best country in the world for
“employing workers.”a


Incorporating these recommendations, the 2006 Employment Act outlines general
principles relating to forced labor, discrimination in employment, and sexual harass-
ment in the workplace. It protects the rights of women, though compliance is still very
low, and the main enforcement machinery—the Ministry of Gender, Labour, and Social
Development—has insuffi cient funding for its mandate.


Enforcement is therefore weak, particularly relating to prohibition of discrimina-
tion based on sex, prohibition of sexual harassment in the workplace, and the right to
return to the same job after maternity leave.


Source: Personal communication with Dr. Maggie Kigozi, executive director, Uganda Investment


Authority.


a. Uganda’s earlier ranking is not comparable due to a change in how this indicator is calculated.




226 ENTERPRISING WOMEN


and generate cross-referrals—and supports individual entrepreneurs who might
otherwise feel isolated. Business associations also amplify the voices of their
members in the public sphere.


Africa has many business-focused organizations, but reliable informa-
tion on women’s participation in them is patchy—for several reasons. First,
obtaining membership data is diffi cult, in part because many associations
do not wish to share their client lists out of concerns about confi dential-
ity, or because of fears that researchers might “take” their clients. Second,
information disaggregated by sex is largely absent from these data, except for
data from women-focused business associations. Th ird, some associations
have individuals as members and others have businesses, and the sex of the
business owner can be diffi cult to establish (as with family businesses, for
example, or businesses with multiple owners, particularly if ownership and
decision-making authority are separate), or it can be irrelevant (as with many
corporate entities).


One analysis of state-business relations inventories almost 450 business
organizations in 20 countries (te Velde 2006). An extensive database of Africa’s
development-focused institutions has listings for all 47 Sub-Saharan countries,
including many government, international, and faith-based organizations.3 But
one cannot determine how much these organizations are focused on business.
Th e data set for Cameroon, for instance, lists more than 350 organizations, of
which around 50 may be focused on business or the private sector; and, of
these, around 12 are estimated to be women focused. Th e “Voices of Women
Entrepreneurs” study for Ghana lists 44 women’s business associations and
institutions (IFC 2007a).


Some countries present their own challenges to increasing women’s
membership. Cultural and social imperatives can discourage women from
mixing freely with men, especially men from outside their families. In such
circumstances, a specialized women’s business association makes sense: such
networks not only provide women business owners with the support they
require, but also help spread new business ideas, facilitate making business con-
tacts, and provide avenues for larger-scale marketing and distribution.


Unclear Benefi ts of Membership
One problem in increasing women’s participation may be that women
are ambivalent about business associations that are specifi cally aimed at
women, or believe them to be too small to be worth joining, a self-fulfi lling
view that can undermine the associations’ eff orts. An International Labour
Organization study reported that women entrepreneurs had mixed views
about using business networks and associations as support for business devel-
opment (Richardson, Howarth, and Finnegan 2004). According to the study,
some women entrepreneurs used these organizations extensively as part




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 227


of their business development strategies, but many were either unaware of
them or felt unable to get into them. Membership seemed low, so the associa-
tions struggled for credibility and sustainability. Low membership may also
refl ect unclear mandates and functions, so businesswomen see little to gain
by joining.


Women’s low representation in business associations is mirrored in their
low representation in business management and corporate decision making,
as well policy making. Even in the United States in 2009, women were
13.5  percent of Fortune 500 executive offi cers and 15.2 percent of board mem-
bers (Catalyst 2009). And in Europe in 2007, women were only 11 percent
of the members of executive committees of listed companies (McKinsey and
Co. 2007).


Broadening the Horizons of Women’s Business Associations
What do these associations do? Th ey tend to provide direct support to women’s
businesses, through networking, developing market opportunities, improving
business skills, and getting fi nance—all important. But to tackle the challenges
facing women in business, broader policy and legal reforms are needed (as other
chapters have shown). Too oft en women are excluded from formal or infor-
mal networks. Gender-based stereotypes and a lack of role models oft en block
women’s professional advancement and limit their voices in business communi-
ties and policy making.


Women’s organizations in Africa are taking part in larger international
associations, sharing examples of change. Th e World Association of Women
Entrepreneurs, founded in 1945, has representatives from women’s business
associations in 10 Sub-Saharan countries.4


A recently established regionwide network, the Africa Businesswomen’s
Network, brings together women’s business associations from several African
countries; it provides an umbrella to support various national hubs to develop
women’s business associations, strengthen their capacity to serve members, and
lobby for policy changes in the business environment (box 10.2). It explicitly
aims to combine business networking with advocacy training.


A case study from Malawi to support a women’s business association provides
practice pointers, emphasizing bottom-up approaches (box 10.3).


Media events and the Internet expand the opportunities to build capacity
(see box 10.4).


Th e capacity of business associations—particularly women’s—to engage in
policy dialogue and advocacy also needs to be developed. First, it is crucial
to broaden the focus of advocacy to include parliamentarians and others pro-
moting gender-responsive reforms of family and other laws that aff ect women’s
economic opportunity. Second, more women need to participate directly in
mechanisms infl uencing policy.




228 ENTERPRISING WOMEN


BOX 10.2


The Africa Businesswomen’s Network: Amplifying
Women’s Voices
The Africa Businesswomen’s Network is a partnership between local business women’s
organizations throughout Africa, Vital Voices Global Partnership, and ExxonMobil
Foundation. Its goals are


• To build and then support a network of businesswomen’s organizations in Africa in
order to expand the number of women succeeding as entrepreneurs and leaders in
the corporate world


• To raise the profi le and credibility of women in business
• To foster global networking opportunities among businesswomen
• To advocate for policies that expand economic opportunities for women
The programs and events of the network provide a forum for peer learning, information
exchanges, business development, and access to education, resources, and tools—all
expanding economic opportunities and building networks for businesswomen in the
region. Members of the network—network hubs—are businesswomen’s organiza-
tions committed to contributing to economic growth and reform, to supporting the
needs of women-led businesses and professional women, and to having a signifi cant
social impact. Businesswomen take part in the network through membership in the
network hubs being developed in Cameroon, Ghana, Kenya, Nigeria, South Africa,
and Uganda.


Network Hub Goals
Network hubs seek to


• Establish a strong network of businesswomen and advance the exchange of best
practices and success strategies in business


• Raise the profi le and credibility of women in the private sector
• Monitor and highlight the contributions of women to economic growth in the region
• Educate and build the capacity of women for entrepreneurship in small and medium


enterprises and beyond


• Promote gender equity in corporate workplace policies and government legislation
• Connect women entrepreneurs to sources of capital and promote women as


investors and sources of venture capital


Network Hub Activities
Network activities include


• Outreach programs that empower and inform women to take advantage of
entrepreneurial and corporate advancement opportunities




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 229


• Special events (training workshops, skills clinics, seminars, conferences, networking
events) to provide women with practical learning and information that can be
applied immediately in their businesses and, in some cases, in their personal lives


• Advocacy for workplace policies and government legislation that promote gender
equity and advance the rights and interests of businesswomen.


• Wide distribution of information to businesswomen through newsletters, websites,
webinars, and other means to provide access to public and private resources for
business


• Outreach to the media to get broad coverage of businesswomen’s success stories
and to raise the profi le, visibility, and credibility of women leaders in business


• Outreach and education of government offi cials to improve their awareness of
the value of women in business to overall economic development, including the
dissemination of high-quality research on women in business


• Outreach to girls and young women, including mentoring and training as well as
internship programs for schools, youth groups, or other organizations, to develop
the next generation of businesswomen


Source: Vital Voices Global Partnership, http://vitalvoices.org/what-we-do/regions/africa/africa-


businesswomens-network.


BOX 10.3


National Association of Business Women in Malawi:
Creating a Grassroots Advocacy Program
Thanks to successful advocacy initiated with the help of the Center for International
Private Enterprise (CIPE), the National Association of Business Women (NABW) in
Malawi has been the driving force behind the growing empowerment of the coun-
try’s women entrepreneurs. In line with a bottom-up, consensus-building approach,
the NABW held regional meetings throughout Malawi to learn about the most press-
ing needs of women entrepreneurs. Meeting attendance exceeded expectations, with
some meetings drawing well over a hundred participants. Just as important, they
included a large proportion of women from rural areas, where the majority of Malawi’s
women-owned businesses are located.


The NABW has complemented the information it obtained at the grassroots level
with detailed background studies of its own. The studies contain not only specifi c data


—Continued




230 ENTERPRISING WOMEN


on the problems businesswomen face in the most important sectors but also specifi c
recommendations on the legal and institutional policies that must change if women-
owned businesses are to prosper.


Armed with these data, the NABW invited key government offi cials and agencies
to participate in its membership meetings, where the sectoral development plans and
recommendations are discussed and fi ne-tuned. An impressive array of policy makers
participated, including offi cials from various ministries and other relevant government
bodies.


Turning government offi cials into stakeholders in the reforms that the NABW
advocates is paying off handsomely. Several laws and policies that hurt Malawi’s
businesswomen have been changed. Special government extension services are now
available to women running agribusinesses. The Ministry of Finance has increased the
funding of several ministries to carry out programs that benefi t women entrepreneurs.
A new land law policy is up for parliamentary review. One of its key provisions would
enable women to obtain property titles, which they could then use as collateral to
secure commercial loans.


The NABW is keeping close tabs on the reform process. With fi nancing from CIPE,
it has launched a watchdog communications service that reports on its own efforts
and those of other stakeholders in implementing the sectoral development programs
it has drafted. The service consists of periodic newsletters called “ Business Alerts,”
distributed to NABW members as well as all key government offi cials and agencies,
nongovernmental organizations, and—for good measure—the local media.


The NABW has gained considerable clout in offi cial circles. The government has
included association executives in the high-level task force studying changes to the
country’s small and medium enterprises in a major effort with the United Nations
Development Programme. The NABW also has representatives on the boards of para-
statal organizations that affect women-owned businesses. And it participates in local
and international trade fairs through the Malawi Export Promotion Council.


The main lessons taught by the NABW’s experiences are these:


• Advocacy campaigns are more powerful when initiated from the bottom.
• Background studies complement grassroots information.
• Government agencies have to be stakeholders in the advocacy process.
• The campaign has to be accompanied by newsletters and continual communications.
• Donors can bring in their media expertise and reputation vis-à-vis the government.
Source: CIPE Promotion Council, http://www.cipe.org.


BOX 10.3 c o n t i n u e d




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 231


Bringing Women into Public-Private Dialogue


Given the dialogue between the public and private sectors to improve the busi-
ness climate, enabling women to participate more can boost the chances of
making their voices heard when government and business leaders articulate
and implement investment reform priorities.


Role and Structure of Public-Private Dialogue
Th e IFC developed its PPD program to facilitate interactions between private
and public actors as they identify and address obstacles to an improved business
environment (box 10.5). Oft en anchored at the highest level of government,
PPD facilitates the business-environment reform process and the implementa-
tion of specifi c investment-climate reforms. Investors identify and implement
reforms and assess the impact of those reforms on the business environment,
empowering constituencies and building trust and transparency among key
stakeholders. Th e PPD tool kit shows that PPD programs take diff erent forms,
depending on the structure of the private sector, the power of diff erent branches


BOX 10.4


Resources for Country-Level Advocacy
The International Labour Organization’s WEDGE (Women’s Entrepreneurship Develop-
ment and Gender Equality) program promotes the “Month of the Woman Entrepre-
neur” in African countries (so far, Ethiopia, Tanzania, Uganda, and Zambia), organizes
events to promote awareness about women’s entrepreneurship, shares experience,
and designs strategies to assist women entrepreneurs and strengthen the capacities
of their associations. The media are central to these events. In Tanzania and Uganda,
workshops were held on the role of the media in women’s entrepreneurship develop-
ment. The media were also active in the events. In Tanzania, newspaper, radio, and
television journalists attended the launch of the month’s events, and a “road show”
toured Dar es Salaam.


The Community of Women Entrepreneurs is a website hosted and moderated by
the U.S. Center for International Private Enterprise, a forum for sharing ideas, experi-
ences, best practices, and resources to empower women economically and politically.
Members of this community are leading entrepreneurs and business advocates who
share their knowledge and in return receive ideas from their peers. Discussions in this
community focus on supporting a culture of entrepreneurship, expanding the opportu-
nities for women in business, and advocating for a better business environment.


Source: Simavi, Manuel, and Blackden 2010.




232 ENTERPRISING WOMEN


of government, and the degree to which the groups are well organized (Herzberg
and Wright 2006). Th ey follow no template.


Th irty countries have adopted the IFC’s PPD programs (Toland 2009), and
practitioners and academics have a wide array of tools and techniques for con-
ducting them,5 with annual workshops providing a forum for exchanging global
experience.


A common institutional approach, prevalent in most productive PPD pro-
grams, involves a dedicated secretariat and working groups that meet oft en to
devise recommendations for periodic plenary sessions. Th e secretariat orga-
nizes meetings, coordinates research eff orts and other logistics, sets agendas,
rallies members, manages communication and outreach strategies, and is a
point of contact for others who want to join.


Th rough working groups, a range of public and private sector actors defi ne
critical issues and reform strategies. Th e groups are typically organized by
industry cluster (for example, agriculture, tourism, or manufacturing), by pol-
icy issue (for example, deregulation, taxation, or labor), or by location, enabling
them to focus and call on greater technical expertise.


PPD, in regular roundtables or investment council meetings, can take place
between central government and private sector organizations representing
national and international corporations, and at the local level between local
authorities and businesses. Outside these formal structures, government and
private sector representatives oft en network informally.


BOX 10.5


Public-Private Dialogue for Investment-Climate Reform
Governments that listen to the private sector are more likely to promote sensible,
workable reforms; and entrepreneurs who understand what the government is trying
to achieve in its reforms are more likely to support them.


Talking is thus the best way for the public and the private sectors to set the right
priorities—and support common interests. Meeting regularly builds trust and under-
standing. But a failure to communicate leads to distrust, which leads to ineffi ciency and
waste, inhibiting growth, investment, and poverty reduction.


PPD promotes good public and corporate governance. It sets an example of
transparency and dynamism. It also sheds light on the workings and performance of
government institutions, and it improves the quality of the advice government receives
from the private sector by diversifying sources and promoting more evidence-based
advocacy.


Source: Gamser, Kadritzke, and Waddington 2005.




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 233


PPD can enlarge the reform space by ensuring greater inclusion of
stakeholders in reform deliberations and facilitating greater local ownership of
reform measures (fi gure 10.1). Th e potential for PPD to promote gender inclu-
sion among stakeholders, and contribute to enlarging the reform space, is thus
considerable.


Unfortunately, women’s participation in PPD seems very low—a topic that
we now turn to.


Women’s Participation in Public-Private Dialogue
It is hard to assess how extensively women are represented in PPD programs,
not least because the programs initially had little or no explicit focus on women
as participants or on gender issues. In the early years, women’s presence appears
to have been either negligible or unspecifi ed, and attention to gender diff erences
in investment-climate reform was correspondingly low.


Many of the early case materials and assessments of PPD hardly mentioned
women, though some referred to women’s groups or women’s business associa-
tions. Th e 1998 IFC Good Practice Manual on public consultation and disclo-
sure includes a few exhortations about ensuring that the voiceless and powerless
(including women) are heard, but provides no specifi c examples, substantive
guidance, or practice pointers (IFC 1998). In 2005, when the World  Bank
evaluated the presidential investors’ advisory councils that it supported in


Figure 10.1 Public-Private Dialogue Enlarges the Reform Space


Source: Adapted from World Bank 2004, 68.
Note: The figure represents the difference between the reform space when PPD is absent (left) and when it is
present (right). Region A represents the set of potential reforms or actions that demonstrate administrative and
political feasibility as well as policy desirability—and hence are most likely to be implemented. Regions B, C, and
D represent the sets of policies where at least two of the desirability and feasibility features are present. The
aim of PPD is to expand region A—that is, to expand the set of actions that have all three of the desirability and
feasibility features.


Learning about
good practice


Capacity building


Policy
desirability


Policy
desirability


Administrative
feasibility Political


feasibility


Most
effective


reform space


BB


D


D


A
cc


Political
feasibility


Reform management


Administrative
feasibility




234 ENTERPRISING WOMEN


several African countries, women’s associations were mentioned only in an
appendix on country responses in Uganda (Dewah 2007). Indeed, unless gender
was explicitly addressed as a part of the program, the experience of PPD pro-
grams suggests very low levels of women’s participation in PPD mechanisms,
and equally low activity on the part of PPD institutions either to promote gender
inclusion or to make space for identifying and tackling business-environment
issues of particular interest to women (Gamser, Kadritzke, and Waddington
2005; IFC 2005).6


In 2008 the IFC recognized the need to integrate an explicit gender dimension
into both the process and content of PPD work. It organized a workshop in
April 2008 in Dakar, Senegal, for all PPD practitioners, and it included a session
on addressing gender issues in PPD. At the conclusion of the workshop, PPD
practitioners were invited to prepare work plans outlining ways in which coun-
try PPD programs would address gender issues. Based on these work plans, the
workshop proposed that country PPD programs could consider incorporating
one or more of the following actions in their work plans:


• Prepare an inventory of women’s business associations, women entre-
preneurs, and the distribution of men and women in the institutions and
organizations involved in PPD, including in the PPD secretariat and in
working groups formed to discuss specifi c issues. Th is will provide a base-
line for outreach to, and dialogue with, women’s business groups.


• Invite women entrepreneurs and women’s business associations to a dialogue
event to discuss the principal issues and constraints in the business environ-
ment faced by this constituency, with a view to outlining a program of action,
including further dialogue and/or more-detailed analysis and research as
required, to address them. Th is will provide a foundation for addressing
gender-focused issues as a PPD task.


• Review, in the context of existing or planned PPD dialogue focus areas,
where gender issues are or might be relevant, so as to inform the process.
Th is will provide entry points for gender-focused work within existing PPDs.


Th is agenda has been pursued in the context of the Liberia Better Business
Forum, and its impact has been signifi cant. A similar agenda is being pursued in
Rwanda, internationally recognized as a leader in promoting gender equality in
the region. Rwanda has made considerable progress in improving the business
environment for women (see IFC 2008).


How to Ensure Successful Public-Private Dialogue
A distinction needs to be made between the presence of women in PPD struc-
tures and the extent to which women contribute to setting the agenda of the
dialogue. Th e mere presence of women, however important, does not translate




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 235


into discussion of gender-specifi c concerns in the business environment. Other
proactive steps must be taken to ensure that the gender dimensions of the issues
being tackled in PPD are identifi ed—and that gender-responsive measures can
be articulated and acted on, as discussed in the rest of this chapter.


Gamser, Kadritzke, and Waddington (2005) provide a useful summary of
the key factors that lead to successful PPD (box 10.6). Th e IFC evaluation of its
PPD programs also identifi es several factors (some of which overlap with those


BOX 10.6


Keys to Effective Public-Private Dialogue
Effective champions drive successful PPD. Active, motivated, and persuasive champions
keep processes on course when obstacles are encountered. They keep participants feel-
ing engaged and valued, so that when changes are agreed to, they are implemented.
They are focused on results but fl exible enough to respond to PPD contributions
(as opposed to using these meetings as a vehicle to advance individual agendas). It is
diffi cult to sustain PPD without active work from both a public and a private champion.


Buy-in by both the public and private sector is essential. Both have to commit
resources to PPD. The process cannot depend on donor backing; excessive donor sup-
port before local buy-in orients PPD to donor agendas instead of to local priorities and
discourages local ownership.


Balance between interests and contributions sustains PPD. More participants
contribute in successful dialogues, both at the table and in pretable and posttable
research and analysis. If one or two participants do most of the work, they tend to have
little infl uence, even if the more active parties are genuinely trying to work on behalf
of the whole group.


Planning is vital. There is more to PPD than simply providing space and persuading
people to sit together. Agendas should be set well ahead of meetings (and well adver-
tised). Evidence-based materials should be provided to inform and enliven discussions.
Timetables should be set for group outputs wherever possible, to support planning and
to pressure the group to produce results.


Results drive PPD in the longer term. Dialogue without change cannot be sustained
for very long. Careful setting of priorities and sequencing of group activities works
better than trying to tackle a large wish list of reforms all at once. The more successful
PPD initiatives focus early on low-hanging fruit, where political resistance to change is
low and where reforms can be agreed on over short time spans. This strategy builds
momentum for tackling tougher, less tractable problems.


Respect keeps groups coming back to the table. In the best PPD processes all parties
feel motivated to contribute, and feel that their contributions can make a difference. If
groups come to feel that they are brought into a dialogue just to make them change


—Continued




236 ENTERPRISING WOMEN


in Gamser, Kadritzke, and Waddington) that are critical to success, such as hav-
ing eff ective champions, having a well-run secretariat, ensuring government
commitment to follow-up actions, and using evidence-based analysis, research,
and impact evaluation (Toland 2009). Another factor in achieving success is
ensuring that PPD addresses sector-specifi c issues.


Enlarging the Reform Space: Strengthening Gender Inclusion in
Public-Private Dialogue
Integrating gender into PPD can occur in several ways. At the policy level, the
task is to apply a gender lens to legal and regulatory reforms of the business
environment. Th is approach is complemented by ensuring a gender-friendly
PPD process, including appropriate gender representation in, and engage-
ment with, all components of a PPD’s structure. Th e gender lens can also
identify sector-specifi c gender issues, or involve traditional leaders in societ-
ies where cultural biases against women may make formal PPD and appli-
cation of an across-the-board gender approach impractical. None of these
approaches has been fully tested yet. But PPD programs are clearly making an


their minds, they tend not to come back for more—and to harden their contrary
positions. Institutions managing the “neutral space” can maintain atmospheres of
mutual respect.


Measurement is a key to getting PPD in focus. More-successful dialogues do not just
hear complaints and plaudits, they look hard at the costs and benefi ts of the situation
and at possible future scenarios. The mathematics need not be fancy, but there should be
some attempt to quantify problems and opportunities in the enabling environment. Reg-
ulatory impact assessments are one of many tools that can promote more-effective PPD.


Public relations and communications are vital to change. No matter how carefully
PPD participants initially are selected, implementing reform requires bringing more
parties to the table. This wider audience should include other parts of government (and
parliament), private sector associations, and key civil society groups.


Private sector associations may not be essential to PPD in the short run, but PPD
cannot be sustained without capable private sector association participation. In the
short run PPD can compensate for association weakness by direct appeals to business.
Enlightened entrepreneurs can provide the information and political support to initi-
ate PPD and tackle initial issues. But in the longer run it is too expensive to continue
custom-assembling the private sector side of the dialogue as issues evolve. Capable
business associations take on this cost in countries with better business environments
and more-positive government-business relations.


Source: Gamser, Kadritzke, and Waddington 2005.


BOX 10.6 c o n t i n u e d




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 237


eff ort to address gender gaps much more rigorously than in the past. Actively
engaging in and monitoring gender issues and women’s leadership in PPD
processes—for example, by using guiding questions such as those listed in
box 10.7—is now an explicit part of PPD programs (Simavi, Manuel, and
Blackden 2010).


Making Sure Women’s Voices Are Heard and Acted On
Making women’s voices heard and acting on what women say have the poten-
tial to transform the business environment. It is important to build on existing
initiatives and dialogue where possible. But if these do not exist, are weak, or


BOX 10.7


Guiding Questions on Gender in Public-Private Dialogue and
Business-Environment Reforms


• Presence of women in the PPD. How well represented are women/women’s busi-
nesses in the structures of the PPD—in working groups, secretariat, meetings, and
other forums? Are any PPD participants tasked with representing the interests of
businesswomen? What (if any) are the links between the PPD and women’s business
associations? What are the obstacles and opportunities for including women in PPD?


• Gender dimensions of PPD issues. To what extent has the PPD process recognized
and/or addressed any gender dimensions of the issues with which it is concerned?
For example, incentives and opportunities to formalize (register) businesses can be
quite different for men and women. What are the obstacles and opportunities for
addressing the gender dimensions of PPD issues?


• Active focus on gender issues in the business environment. Has there been any real
outreach to women in business (and their associations)? Has the PPD provided space
to address issues affecting women in business? What has been the experience of the
PPD (if any) in addressing issues of particular concern to women? What issues that
affect women has the forum discussed in the last six months or year? What success
stories are there? What are the obstacles and opportunities for active outreach to
women in PPD processes?


• Distilling the lessons of experience—what works. Are top-down or bottom-up
approaches better? Is it better to mainstream gender concerns into existing PPD
approaches, or to have parallel structures focused on gender issues? What does
the experience of getting women’s voices heard in efforts to improve the business
climate tell us about how to do it better?


Source: Based on Simavi, Manuel, and Blackden 2010.




238 ENTERPRISING WOMEN


do not represent the interests of businesswomen, it may be useful to initiate
new forums, strengthen an existing forum, or simply provide a mechanism for
consultation with women in business. Care should be taken to ensure the pro-
cess includes very small businesses, which may not be organized into formal
associations (Simavi, Manuel, and Blackden 2010).


Uganda shows the importance of not only getting women to the table
but also focusing more strategically on the tables that matter. Th e Uganda
Investment Authority Women Entrepreneurs Network, set up in 2000 to
create a forum for networking and sharing success stories among women
entrepreneurs, has more than 300 female entrepreneurs in varied small,
medium, and large enterprises. Its major role is to strengthen women’s
networking, information sharing, mentoring, and capacity building in
business and leadership skills.


Th e members are women in business, professionals, and corporate chief
executives who meet regularly. Th e network has brought women into the
Presidential Investors Round Table, the apex policy dialogue body between
the president and the private sector. A total of 22 (11 local and 11 foreign)
chief executive offi cers advise the president on how to improve the investment
climate. During the roundtable’s fi rst phase in 2004, the Uganda Investment
Authority had one domestic and one foreign female entrepreneur. In its third
phase, the roundtable has fi ve female members. Th e goal is to have 11 female
entrepreneurs represented—half the roundtable’s membership.


Th ese examples show that women’s voices in shaping and improving the
business environment can be amplifi ed. A combination of bottom-up advocacy
work, better networking opportunities among businesswomen, and support at
the highest level of government can bring more women to the table and ensure
that issues of importance to them—with a specifi c gender angle or not—are
discussed.


Th is agenda needs continuing support: women’s voices will not automatically
be included, though the default exclusion of women’s voices is shift ing in many
countries. Examples of success provide role models for others to follow, and the
positive track record reinforces the wider benefi ts of businesspeople’s listening
to (and acting on) businesswomen’s voices.


Notes
1. Th is work uses “business environment” and “investment climate” interchangeably


to refer to conditions external to the fi rm that aff ect its performance, for example,
infrastructure services, regulations, access to fi nance, governance, security, and
property rights.


2. Similar studies were carried out in Bosnia and Herzegovina (Cutura 2008), Vietnam
(IFC 2006a), and Indonesia (IFC–IWAPI 2001).


3. Directory of Development Organizations, http://www.devdir.org.




STRENGTHENING WOMEN’S VOICES IN BUSINESS-ENVIRONMENT REFORMS 239


4. Th e countries are Benin, Cameroon, Chad, Côte d’Ivoire, Democratic Republic of
Congo, Gabon, Guinea, Mali, Mauritius, and Senegal. For more information see the
association’s website (http://www.fcem.org/www/en/home.asp, accessed February
2011). Th e association also has six observer/affi liate countries in Africa.


5. These tools and techniques are accessible at the PPD website (http://www
. publicprivatedialogue.org).


6. Attention to gender issues was not, for example, initially part of the IFC evaluation
of PPDs (Toland 2010).


References
Bowman, C., J. Cutura, A. Ellis, and C. Manuel. 2009. Women in Vanuatu. Washington,


DC: International Finance Corporation.
Catalyst. 2009. Statistical Overview of Women in the Workplace. New York: Catalyst


Quick Takes.
Cutura, J. 2008. Voices of Women Entrepreneurs in Bosnia-Herzegovina. Washington, DC:


International Finance Corporation.
Dewah, E. 2007. Case Study: Reform in Botswana. Washington, DC: Center for Interna-


tional Private Enterprise.
Ellis, A., M. Blackden, J. Cutura, F. MacCulloch, and H. Seebens. 2007. Gender and


Economic Growth in Tanzania: Creating Opportunities for Women. Washington, DC:
World Bank.


Ellis, A., J. Cutura, N. Dione, I. Gillson, C. Manuel, and J. Th ongori. 2007. Gender
and Economic Growth in Kenya: Unleashing the Power of Women. Washington, DC:
World Bank.


Ellis, A., C. Manuel, and M. Blackden. 2006. Gender and Economic Growth in Uganda:
Unleashing the Power of Women. Washington, DC: World Bank.


Gamser, M., R. Kadritzke, and R. Waddington. 2005. Reforming the Business Envi-
ronment: Mechanisms and Processes for Public Sector Dialogue. London: Bannock
Consulting, U.K. Department for International Development.


Hedditch, S., and C. Manuel. 2010. Gender and Investment Climate Reform Assessment:
Pacifi c Region. Washington, DC: International Finance Corporation.


Herzberg, B. 2008. “PPD Product Review.” PowerPoint presentation, International
Finance Corporation, Washington, DC, November.


Herzberg, B., and A. Wright. 2006. Th e PPD Handbook: A Toolkit for Business Envi-
ronment Reformers. U.K. Department for International Development, World Bank,
International Finance Corporation, and OECD Development Centre. http://www
.publicprivatedialogue.org/papers/PPD%20handbook.pdf.


IFC (International Finance Corporation). 1998. Doing Better Business through Eff ective
Public Consultation and Disclosure: A Good Practice Manual. Washington, DC: IFC
Environment Division.


. 2005. Building the Capacity of Business Membership Organizations: Guiding
Principles for Project Managers. Washington, DC: IFC.


. 2006a. Voices of Vietnamese Women Entrepreneurs. Washington, DC: IFC.




240 ENTERPRISING WOMEN


. 2006b. Voices of Women Entrepreneurs in Kenya. Washington, DC: IFC.
. 2007a. Voices of Women Entrepreneurs in Ghana. Johannesburg: IFC.
. 2007b. Voices of Women Entrepreneurs in Tanzania. Washington, DC: IFC.
. 2008. Voices of Women Entrepreneurs in Rwanda. Washington, DC: IFC.
IFC–IWAPI (International Finance Corporation–Indonesian Women’s Business Asso-


ciation). 2001. Voices of Women in the Private Sector. Jakarta: IFC–IWAPI.
McKinsey and Co. 2007. Women Matter: Gender Diversity, a Corporate Performance


Driver. Paris: McKinsey and Co.
Richardson, P., R. Howarth, and G. Finnegan. 2004. “Th e Challenges of Growing Small


Businesses: Insights from Women Entrepreneurs in Africa.” SEED Working Paper 47,
International Labour Offi ce, International Labor Organization, Geneva.


Simavi, S., C. Manuel, and M. Blackden. 2010. Gender Dimensions of Investment Climate
Reform: A Guide for Policy Makers and Practitioners. Washington, DC: World Bank.


te Velde, D. W. 2006. “Measuring State-Business Relations in Sub-Saharan Africa.” IPPG
Discussion Paper Series 4, Research Programme Consortium for Improving Institu-
tions for Pro-Poor Growth, Manchester, U.K.


Toland, M. 2009. “Independent Evaluation of 30 WBG-Supported Public Private Dia-
logue and Reform Platforms for Private Sector Development.” PowerPoint presenta-
tion, International Finance Corporation, Vienna, Austria, April 28–30.


. 2010. “Gender and Private Public Dialogue.” PowerPoint presentation, Interna-
tional Finance Corporation, Vienna, Austria, June 1–3.


World Bank. 2004. World Development Report 2005: A Better Investment Climate for
Everyone. Washington, DC: World Bank.


. 2007. Doing Business 2007. Washington, DC: World Bank.




241


Chapter 11


Toward an Action Agenda


Th is concluding chapter outlines some areas where policy reforms could
improve women’s opportunities for entrepreneurship in Sub-Saharan Africa.1
It focuses on key areas that aff ect the gender-diff erentiated patterns. Th e aim
is to enable women to engage in larger, formally registered businesses in
higher-value-added lines of business. Th e emphasis is on reforms of women’s
legal status and property rights. Gender gaps in rights limit women’s business
opportunities. As development is not suffi cient to close these gaps, they require
proactive measures.


Th e chapter also highlights measures to improve women’s access to fi nance,
their fi nancial literacy, and their managerial skills. It discusses broader
investment-climate reforms, addressing constraints to growth in areas where
women’s economic activities are concentrated. And it proposes measures to
strengthen women’s participation in policy dialogue, which would improve the
business environment for everyone.


Reforming the Business Environment


Reforming the business environment expands opportunities for growth, higher
productivity, and employment—for all. Broader reforms, such as improving
infrastructure, tax administration, and regulations, are likely to benefi t both
women and men. Th e extent of the benefi ts can have indirect gender eff ects, of
course, depending on the types of enterprises that benefi t most from reform.
For example, lift ing constraints on smaller fi rms and encouraging formalization
should help women disproportionately.


Constraints to entrepreneurship that aff ect women more than men— strongest
in areas of property rights, access to fi nance, and harassment—reduce half the
population’s potential to participate and compete equally in productive activi-
ties, lowering aggregate growth. Particularly if those constraints distort fi nancial
markets, so that capital is not allocated to the most productive activities, they
have a broader eff ect on stunting competitive pressures, lowering innovation,
and cutting aggregate productivity growth. And they restrict higher-potential




242 ENTERPRISING WOMEN


women’s enterprises the most (Schoar 2010). Th ere is thus an intrinsic and
instrumental case for removing gender-based constraints to entrepreneurship.


Increasing Women’s Right to Own and Control Assets


Th e earlier chapters make a strong case for improving the business environment
for women through legal reform. Important areas of law, notably family law,
place women at a disadvantage in their ability to own property, enter contracts,
go to court, and use the justice system more generally. Th e responsiveness of the
justice system to women’s concerns can be improved both for substantive law
and in procedural and administrative areas.


To ensure women’s equal rights, substantive law reforms are needed along
several dimensions. As shown in the Women–LEED–Africa database, countries
need to bring consistency and coherence to their judicial practice. Governments
should be encouraged not only to ratify international treaties and conven-
tions (including the Maputo Protocol, the Convention on the Elimination of
All Forms of Discrimination against Women, and key International Labour
Organization conventions), but also to “domesticate” and then enforce them.
Within a coherent international framework, governments should examine
their constitutions to address discriminatory provisions, enhance provisions
for gender equality, review how the legal system recognizes customary law and
customs, and ensure in particular that constitutional nondiscrimination provi-
sions are applied in family law and property rights in marriage. Contradictory
and inconsistent provisions in the law also need to be addressed.


Integral to improving the gender responsiveness and consistency of statu-
tory reforms is the need to tackle discriminatory provisions in family law that
reduce women’s ability to engage in business. Tackling such provisions applies
especially in countries where family law discriminates against married women
by assigning the position of “household head” and decision maker exclusively to
the man, and where statutory provisions specifi cally limit married women’s legal
capacity. Governments need to pay special attention to laws governing marriage,
divorce, and succession. Although the framing of business laws and regulations
is generally gender neutral, their application is sometimes gender biased, and
regulatory reforms can be carried out in a more gender-responsive way.


Key items to address include the following:


• Giving women equal say over the administration and transfer of marital
property


• Limiting or removing head-of-household laws that allow husbands to deny
permission to their wives to engage in a trade or profession, or to choose the
marital home




TOWARD AN ACTION AGENDA 243


• Removing provisions requiring a husband’s signature to enter contracts or
open a bank account


• Enabling married women to testify equally in court
• Recognizing women’s rights to marital property on divorce or in inheritance
• Applying constitutional provisions of nondiscrimination in areas of


marriage, property, and inheritance
• Building awareness of gender bias, and measures to counteract such bias,


among judges and within the broader legal community
Reforms in the administration of law and in the institutions responsible for
delivering justice can improve women’s access to justice and the capacity of
the system to respond to women’s concerns. One such reform is facilitating
physical access to justice through more, and more appropriately focused, courts,
as for family matters and small claims. A second is increasing the participa-
tion and representation of women throughout the justice system. And a third is
enabling those administering and dispensing justice at all levels to respond to
the diff erent constraints and priorities of men and women. Such action requires
political will and determination to address the power relations and abusive
practices that can undermine the eff ectiveness of the legal system.2


Expanding Women’s Access to Finance


A repeated fi nding in this book is that the line of business, its size, and its
formality emerge as more important drivers than gender in entrepreneurs’
access to formal fi nance. However, it is not that gender does not matter. Rather,
it comes into play in deeper sources of inequality. Women tend to have less
access to collateral, education, and prior work experience—all of which are
signifi cant predictors of initial bank loans. Th us with less ability to gain credit,
women may be more constrained in their choice of business line, the scale and
formality of their business, and even the ability to become an entrepreneur at all.
Th is cycle can then perpetuate itself as the choice of enterprise reduces the likeli-
hood of qualifying for credit in the future. In the longer term, breaking the cycle
involves tackling underlying gaps in legal rights and in access to human capital.


Measures to improve women’s access to fi nance include the following:
• Enriching women’s human capital. Th is underlies the agenda of expanding


women’s access to fi nance.
• Improving property rights for women. Th is will strengthen women’s control


over assets and their capacity to provide collateral for bank loans.
• Building property registries that include movable property. Th is will also


strengthen women’s ability to use movable property as collateral.




244 ENTERPRISING WOMEN


• Setting up credit registries that capture women’s credit history and repayment
records in microfi nance. Th is will benefi t women disproportionately, given
their greater reliance on microfi nance.


• Targeting fi nancing mechanisms at women, including microfi nance and
mobile banking.


Enriching Managerial and Financial Skills


Formal education is important for building women’s human capital, but
other dimensions also matter, especially in building business-specifi c skills
and capacity. Recent years have seen dramatic declines in education gaps for
boys and girls, which is a very promising indicator for the next generation
of women entrepreneurs. But more needs to be done. Specifi cally, today’s
women have a lower level of fi nancial literacy and use more- limited sets
of management skills. Women who do have higher fi nancial literacy and
management training benefi t from them as much as their male colleagues,
so eff orts to expand such training for women entrepreneurs should broaden
their opportunities. However, as the evaluation literature points out, the
method of teaching and content need to be tailored to the initial level
of business knowledge. While more training is not suffi cient to ensure
success, more  knowledgeable  entrepreneurs are better positioned to grow
their business.


Expanding women’s human capital can reinforce a virtuous cycle too. Having
role models and being part of a network of entrepreneurs are associated with
running more profi table enterprises. Currently these connections benefi t men
more than women, in part as fathers have tended to pass on their connections
and practical knowledge to their sons. As more women are successful entrepre-
neurs and as more fathers apprentice their daughters, more women will be able
to take advantage of these connections and skills.


Key activities to build managerial and fi nancial skills include the following:


• Encouraging opportunities for sharing experiences among businesswomen
• Developing a stronger cadre of female role models in business
• Strengthening management training and increasing access to consulting


services
• Pairing fi nancial literacy and business skills training with access to fi nance;


tailoring programs to increase women’s participation (for example, choice of
time, location, provision of child care services)


• Promoting mentoring and other networking opportunities to facilitate
business contacts, marketing opportunities, and product development




TOWARD AN ACTION AGENDA 245


Strengthening Women’s Voices in Business-Environment
Reform


Proactively including women business owners and associations in public-
private dialogue (PPD) and advocacy eff orts can ensure that women’s unique
constraints are considered in the reform process. PPD is most successful when
there are eff ective champions; a well-run secretariat; government commitment
to follow-up actions; and available evidence-based analysis, research, and
impact evaluation. To ensure that women’s voices are included, it is important
both to strengthen the presence of women in PPD institutions and structures,
and to build the capacity of women to inform and infl uence the substantive
agenda.


Equally important is engaging a wider set of policy makers in addressing
the gender dimensions of business-environment reform, beyond national
women’s machineries and gender advocates. Th is approach means engaging
with the key economic management ministries and mainstream private sector
actors and business associations on the front lines of business-climate reforms.
Disseminating the fi ndings of studies such as this one to a wider audience of
stakeholders and policy makers is therefore one means of using evidence-based
analysis to inform policy dialogue and decision making.


Measures to strengthen women’s voices in business-climate reform include
the following:


• Encouraging women business owners and associations to join PPD
• Encouraging greater participation of women in business associations
• Building the capacity of business associations to provide better services to


members and to contribute more to advocacy for policy reforms
• Carrying out a systematic, gender-informed analysis of business-


environment obstacles to highlight issues of concern to businesswomen and
then integrating this analysis into dialogue and policy making


• Strengthening the presence of women in PPD institutions and structures,
and building the capacity of women to infl uence the agenda of the PPD itself


Areas for Research


Gaps in the data hamper researchers’ ability to undertake gender-disaggregated
analyses. Two are particularly relevant. Th e fi rst relates to the need to know
more about how constraints in the investment climate, particularly in access
to fi nance, shape the entry decision. Th ere are scarce data at the individual (as
opposed to household) level on constraints facing those who do not decide




246 ENTERPRISING WOMEN


to  become entrepreneurs. One way to acquire more data would be to add
relevant questions to household surveys.


Th e second relates to transitions between entrepreneurship and wage
employment. Work in Latin America (for example, Maloney 2004) shows that
there can be a fair amount of mobility for men and single women. Much less
is known about these transitions in Sub-Saharan Africa. To learn more would
require panel surveys of individuals and their labor force decisions.


Notes
1. Th e World Development Report 2012: Gender Equality and Development (World


Bank 2011) provides a global perspective on women and addresses additional
gender issues such as health, violence, and rural development.


2. Hallward-Driemeier and Hasan (2012) elaborate on this agenda in more detail.


References
Hallward-Driemeier, M., and T. Hasan. 2012. Empowering Women: Legal Rights and


Economic Opportunities in Africa. Washington, DC: World Bank and Agence Française
de Développement.


Maloney, W. 2004. “Informality Revisited.” World Development 32 (7): 1159–78.
Schoar, A. 2010. “Th e Divide between Subsistence and Transformational Entrepreneur-


ship.” In Innovation Policy and the Economy, vol. 10, edited by Josh Lerner and Scott
Stern, 57–81. Chicago: University of Chicago Press and National Bureau for Economic
Research.


World Bank. 2011. World Development Report 2012: Gender Equality and Development.
Washington, DC: World Bank.




Appendixes






249


Appendix A


Sources of Data


Enterprise Data


Enterprise Surveys. Administered by the World Bank to large stratifi ed random
samples of registered fi rms in key industrial centers in a country, Enterprise Surveys
cover both manufacturing and services and include information on the owner of
the enterprise, enterprise performance measures, and measures of constraints
facing the enterprise. As the samples are based in urban centers, it is not possible to
make comparisons with formal enterprises in rural areas. Th e Enterprise Surveys—
microenterprises also include a parallel survey of microfi rms, of which 98  percent
have fi ve or fewer employees, for 25 African countries. Th e survey for this subset is
targeted toward informal fi rms and in the analysis is labeled as informal.


Enterprise Surveys—gender module. For fi ve countries that had completed an
Enterprise Survey, the World Bank fi elded an additional module to capture more
information on the background of the entrepreneur, the motivation for start-
ing a business, the means of starting or acquiring a business, and  indicators of
management techniques. Th e modules also refi ned measures on the gender of
both the principal owner and the person running the business. Th e fi ve countries
are Ghana, Mali, Mozambique, Senegal, and Zambia.


Survey of new entrepreneurs. A new survey was fi elded by the World Bank
covering fi rms operating in the formal and informal sectors in four countries
(Côte d’Ivoire, Kenya, Nigeria, and Senegal). Detailed background information
on the entrepreneur was collected, such as the motivation for starting a busi-
ness, the means of starting or acquiring a business, and indicators of management
techniques used. Some additional measures on the constraints faced in setting up
a business were also included.


Individual Data


Household surveys and labor force surveys. Th irty-nine Sub-Saharan countries
administer their own surveys, which are compiled in the International Income




250 ENTERPRISING WOMEN


Distribution Database (I2D2) along with surveys from 62 other countries. While
not strictly comparable because countries use diff erent questionnaires (although
most adhere to the International Labour Organization defi nitions of labor) and
somewhat diff erent sampling strategies, they have been standardized for a core
set of questions to allow cross-country patterns to be examined. Th ese data
inform inclusion in diff erent employment categories. More details are available
in Montenegro and Hirn (2009).


Household survey—enterprise modules. For those in the households who
identify as having an enterprise, additional questions are asked in 20 countries
in Sub-Saharan Africa. Th ese data can be used to examine fi rm performance,
particularly for more informal businesses, those operating out of the house, and
those with household members working in them. It should be noted that the
enterprises covered through the household survey are not necessarily all run
out of the home; many indeed are not. Rather, the basis for the sampling of the
enterprises is the household, not the enterprise.


FinScope


FinScope surveys are nationally representative samples of individuals that
collect information on respondents’ perceptions of fi nancial services and
issues associated with access to fi nance. Th ey also collect information on
income, education, and location. Administered in both urban and rural
areas, they ask respondents to provide information on their use of formal
and informal fi nancial services, thus allowing for a more complete analy-
sis of fi nancial markets than would be possible with information on formal
services only. Because the surveys sample individuals, the data also allow
for comparisons of those who are excluded from fi nancial markets. Th e sur-
veys are a FinMark Trust initiative, established in 2002 and funded primarily
by the United Kingdom’s Department for International Development. More
information is available at http://www.fi nscope.co.za.




SO
U


RC
ES O


F D
ATA





251


Table A.1 Microdata Used


Country Income Level (2011) Enterprise Survey
Enterprise Survey—


gender module
Survey of new


entrepreneurs
Household/labor


force survey
Household survey—


enterprise module FinScope


Angola Lower middle income 2006 — — — — —


Benin Low income 2009 — — 2003 — —


Botswana Upper middle income 2006 — — — — 2004


Burkina Faso Low income 2006, 2009 — — 2003 2003 —


Burundi Low income 2006 — — 1998 1998 —


Cameroon Lower middle income 2006, 2009 — — 2007 2007 —


Cape Verde Lower middle income 2006, 2009 — — 2000 — —


Central African
Republic


Low income — — — 2003 — —


Chad Low income 2009 — — 2002 — —


Comoros Low income — — — 2004 2004 —


Congo, Dem. Rep. Low income 2006, 2009 — — — — —


Congo, Rep. Lower middle income — — — 2005 2005 —


Côte d’lvoire Lower middle income 2009 — 2010 2002 2002 —


Eritrea Low income 2009 — — — — —


Ethiopia Low income 2006 — — 2005 — —


Gabon Upper middle income 2009 — — 2005 — —


Gambia, The Low income 2006 — — 1998 1998 —


Ghana Lower middle income 2007 2009 — 2005 2005 —


Guinea Low income 2006 — — 2002 2002 —


Guinea-Bissau Low income 2006 — — — — —


Kenya Low income 2007, 2009 — 2010 2005 — 2009


—Continued




252


EN
TERPRISIN


G
W


O
M


EN


Table A.1 continued


Country Income Level (2011) Enterprise Survey
Enterprise Survey—


gender module
Survey of new


entrepreneurs
Household/labor


force survey
Household survey—


enterprise module FinScope


Lesotho Lower middle income 2009 — — 2002 — —


Liberia Low income 2009 — — 2007 — —


Madagascar Low income 2009 — — 2004 2004 —


Malawi Low income 2005, 2009 — — 2005 2005 2008


Mali Low income 2007 2009 — 2003 — —


Mauritania Lower middle income 2006 — — 2000 — —


Mauritius Upper middle income 2009 — — — — —


Mozambique Low income 2007 2009 — 2003 — —


Namibia Upper middle income 2006 — — — — 2004


Niger Low income 2005, 2009 — — 2007 2007 —


Nigeria Lower middle income 2007 — 2010 2003 2003 —


Rwanda Low income 2006, 2008 — — 2005 2005 2008


Senegal Lower middle income 2007 2009 2010 2001 — —


Sierra Leone Low income 2009 — — 2003 2003 —


South Africa Upper middle income 2007 2009 — 2005 — 2008


Swaziland Lower middle income 2006 — — 2000 2000 —


Tanzania Low income 2006 — — 2006 2006 2009


Togo Low income 2009 — — 2006 — —


Uganda Low income 2006 — — 2005 2005 2006


Zambia Lower middle income 2007 — — 2003 2003 2005


Note: — = not available.




253


Table A.2 Principal Data Sources, Uses, and Limitations


Source


Countries
covered


(number)
Years


covered Strengths Limitations


Use for gender-disaggregated comparisons and analysis


Decision
to be an


entrepreneur
Enterprise


characteristics
Entrepreneur


characteristics


Constraints
(facing


existing
entrepreneurs) Performance


Household
surveys


Country
statistical
offi ces


39 1998–
2008


Representative
coverage; allow
comparisons of
entrepreneurs and
nonentrepreneurs


No information on
constraints; the
surveys do not
track the same
individuals over
time; some variation
in questions and
sampling across
countries


Yes; also include
information
on those
choosing
not to be
entrepreneurs


No Yes, including
household
characteristics


No No


Enterprise
modules of
household
surveys


Country
statistical
offi ces


20 1998–
2008


Information on
gender and family
characteristics;
include informal
and formal
enterprises


The instruments are
not standardized,
so they do not
allow cross-country
comparisons on
many dimensions;
sampling across
countries is also not
strictly comparable


No Yes Yes, including
household
characteristics


No Yes


—Continued




254


Table A.2 continued


Source


Countries
covered


(number)
Years


covered Strengths Limitations


Use for gender-disaggregated comparisons and analysis


Decision
to be an


entrepreneur
Enterprise


characteristics
Entrepreneur


characteristics


Constraints
(facing


existing
entrepreneurs) Performance


Enterprise
Surveys


World Bank 37 2006–10 Standard
questionnaire
and sampling
across countries;
stratifi ed
random sample;
information
on constraints
(subjective and
quantitative) and
performance


Focus largely on formal
sector, with some
microenterprises
in informal sector;
broad defi nition
of “female
participation in
ownership” in
categorizing female
enterprises


No Yes Yes Yes Yes


Gender modules
of Enterprise
Surveys


Commissioned
for report


5 2009 Separate capture of
ownership and
decision-making
authority; detail
on background
of entrepreneur,
motivation
for being
entrepreneur;
information
on managerial
techniques


Available for only fi ve
countries


No, but some
qualitative
information
on why
and how
respondent
became
entrepreneur


Yes Yes, with more
detail on
background
and “deeper
human
capital”


Yes Yes




255


Survey of new
entrepreneurs


Commissioned
for report


4 2010 Separate capture of
ownership and
decision-making
authority; detail
on background
of entrepreneur,
motivation
for being
entrepreneur;
information
on managerial
techniques;
capture of new
fi rms; current
information on
constraints facing
new entrants;
comparison
of formal and
informal sector


Available for only four
countries


No, but some
qualitative
information
on why
and how
respondent
became
entrepreneur


Yes Yes, with more
detail on
background
and “deeper
human
capital”


Yes Yes




256 ENTERPRISING WOMEN


Reference
Montenegro, C., and M. Hirn. 2009. “A New Disaggregated Set of Labor Market Indica-


tors Using Standardized Household Surveys from around the World.” Background
paper, World Bank, Washington, DC.




257


Appendix B


Indexes of Gender Equality
across Countries


United Nations Development Programme’s
Gender Inequality Index


Th e Gender Inequality Index is a composite measure refl ecting inequality
in achievements between women and men in three dimensions:
reproductive health, empowerment, and the labor market. It varies
between 0 (when women and men fare equally) and 1 (when men or
women fare poorly compared with the other in all dimensions). Th e health
dimension is measured by two indicators: the maternal mortality ratio and the
adolescent fertility rate. Th e empowerment dimension is also measured by two
indicators: the share of parliamentary seats held by each sex, and secondary
and higher education attainment levels. Th e labor dimension is measured by
women’s participation in the labor force. Th e index is designed to reveal the
extent to which national human development achievements are eroded by
gender inequality—and to provide empirical foundations for policy analysis and
advocacy eff orts.


Th e index relies on data from major publicly available databases and publica-
tions, including the United Nations Children’s Fund’s State of the World’s Children
(maternal mortality ratio), the United Nations Department of Economic and
Social Aff airs’ World Population Prospects (adolescent fertility), Barro-Lee
data sets (educational attainment statistics), the International Parliamentary
Union’s database on women in parliaments (political representation), and
the International Labour Organization’s LABORSTA database (labor market
participation).


Th e index is available at United Nations Development Programme, Gender
Inequality Index, http://hdr.undp.org/en/statistics/gii/.




258 ENTERPRISING WOMEN


World Bank’s Country Policy and Institutional Assessments
Gender Equality Rating


Th e World Bank’s Country Policy and Institutional Assessments (CPIA) Gender
Equality Rating assesses the extent to which a country has institutions and
programs to enforce laws and policies that promote equal access for men and
women to education, health, the economy, and protection under the law.


Th ese criteria assess the extent to which a country has enacted or put in place
laws, institutions, and programs to enforce equal access for men and women
to human capital development, productive and economic resources, and equal
status and protection under the law.


For human capital development, the focus is on primary school completion
and access to secondary education, access to health care during delivery and to
family planning, and adolescent fertility. For access to economic and productive
resources, the focus is on labor force participation, land tenure, and property
and inheritance rights. For status and protection under the law, the focus is on
individual and family rights and personal security (violence against women,
traffi cking, or sexual harassment) and political participation.


Each dimension is rated separately and receives equal weight in the overall
rating. Th e score captures whether gender diff erences exist in the subject area,
whether policies and laws are obstacles, and whether there have been recent
eff orts to make laws and policies more supportive of gender equality in the
subject area.


Th e Gender Equality Rating ranges from 1 for low equality to 6 for high
equality. It is available at World Bank Group, CPIA database, http://www
. worldbank.org/ida.


Organisation for Economic Co-operation and
Development’s Gender-related Development Index (GDI)
and Social Institutions and Gender Index (SIGI)


Th e Organisation for Economic Co-operation and Development (OECD)
has two indexes. Th e fi rst, the Gender-related Development Index (GDI), is
a version of the OECD’s Human Development Index that not only includes
levels of education and health outcomes, but also includes gender gaps in these
dimensions.


Th e second, the Social Institutions and Gender Index (SIGI), measures
social institutions refl ected by societal practices and legal norms that produce
inequalities between women and men. Th e SIGI is not just an overall measure of
these institutions. Instead of measuring gender inequalities in education, health,




INDEXES OF GENDER EQUALITY ACROSS COUNTRIES 259


economic and political participation, and other dimensions, it measures impor-
tant inputs—social institutions—against such outcome inequalities in non-
OECD countries. Th ese social institutions are conceived as long-lasting codes
of conduct, norms, traditions, and informal and formal laws. Th e index and
its fi ve subindexes are not therefore intended to refl ect fast changes over time.


Each of the subindexes measures a diff erent dimension of social institu-
tions related to gender inequality: family code, civil liberties, physical integrity,
son preference, and ownership rights. As the indicators in the SIGI primarily
measure social institutions that pose problems in the developing world, the SIGI
covers only non-OECD countries.


Th e SIGI is an unweighted average of a nonlinear function of the subindexes.
Th e nonlinear function arises because it is assumed that inequality related to
gender corresponds to deprivation experienced by the women aff ected, and that
deprivation increases more than proportionally when inequality increases. Th us
high inequality is penalized in every dimension. Th e nonlinearity also has the
advantage that the SIGI allows for only partial compensation among its com-
ponents. Partial compensation implies that high inequality in one dimension—
that is, a subindex—can be only partially compensated with low inequality in
another.


Th e nonlinearity in the index is achieved by squaring the distance of the
respective subindex value from 0, the goal of no inequality. Th e sum of the
resulting squared subindex values divided by the number of subindexes then
gives the value of the SIGI. Th is approach implies a choice of equal weights for
the subindexes because there is no obvious reason to value one of the measured
dimensions more or less than the others.


Th e index ranges from 0 for low inequality to 1 for high inequality. It is
available at OECD, Social Institutions and Gender Index, http://www.oecd.org/
dataoecd/52/33/42289479.pdf.


World Economic Forum’s Global Gender Gap Index


With 30 gender-related variables, the Global Gender Gap Index examines the
gaps between men and women in four categories: labor force participation
and opportunity, educational attainment, political empowerment, and health
and survival.


Th ree concepts underlie the index. First, it focuses on measuring gaps rather
than levels. It is designed to measure gender-based gaps in access to resources
and opportunities in individual coun tries rather than actual levels of available
resources and opportunities in those countries. Rich countries have more edu-
cation and health opportunities for all members of society, and measures of
levels thus mainly refl ect this well-known fact, though it is quite independent




260 ENTERPRISING WOMEN


of the gender-related issues faced by each country at its own level of income.
Th e global gender gap index, however, rewards countries for smaller gaps in
access to these resources, regardless of the overall level of resources. For example,
it penalizes or rewards countries based on the size of the gap between male and
female enrollment rates, but not for the overall levels of education in the country.


Th e second concept is that it evaluates countries based on outcome variables
rather than input measures. Th e aim is to provide a snapshot of where men and
women stand on some fundamental outcome variables related to basic rights
such as health, education, labor force participa tion, and political empowerment.


Th e third concept is that it ranks countries according to their proximity to
gender equality rather than to women’s empowerment. Th e aim is to focus on
whether the gap between women and men in the chosen variables has declined,
rather than whether women are “winning the battle of the sexes.” Hence the
index rewards countries that reach the point where outcomes for women equal
those for men, but it neither rewards nor penalizes countries where women are
outperforming men in particular variables.


It is available at World Economic Forum, Global Gender Gap Index, http://
www .weforum.org/issues/global-gender-gap.


Economist Intelligence Unit’s Women’s Economic
Opportunity Index


Constructed from 26 indicators, the Women’s Economic Opportunity Index
is a dynamic quantitative and qualitative scoring model that measures specifi c
attributes of the environment for women employees and entrepreneurs in
113 countries.


Five category scores are calculated from both the unweighted and weighted
means of underlying indicators and are scaled from 0 to 100, where 100 is most
favorable. Th ese categories are labor policy and practice (which comprises two
subcategories, labor policy and labor practice); access to fi nance; education and
training; women’s legal and social status; and general business environment.
Each category features at least four underlying indicators.


Th e unweighted overall score (0 to 100) is calculated from a simple aver-
age of the unweighted category and indicator scores. A weighted overall score
(0 to 100) is also included. Th e weights are generated for the categories, as well
as the indicators falling under each of the categories, through the application
of principal component analysis. Th e overall score is a weighted mean of the
category scores.


It is available at Economist Intelligence Unit, Women’s Economic Opportunity
Index, http://www.eiu.com/sponsor/WEO.




261


Appendix C


Comparing Women–LEED–Africa
and Its Peers




262


EN
TERPRISIN


G
W


O
M


EN


Indicator Women–LEED–Africa (47 countries )
Women, Business, and the Law database,


2010 (28 countries)


Food and Agriculture Organization of
the United Nations Gender and Land


Rights Database (28 countries)


Sources of law Constitutions, international conventions,
statutes—each reported separately


Constitutions, international conventions, statutes—but
no differentiation in the indicators of the source of law
determining the indicator


Constitutions, international conventions,
statutes—each reported separately


Treatment of
customary law


Whether customary law is recognized in
constitution and/or statutes; extent of limitations
on gender-based nondiscrimination protections


Not included Whether customary law is formally recognized


Property and land
rights


Property rights in marriage, on divorce, and
inheritance; land rights


Gender equality in movable and immovable property Land rights


Legal capacity Indicator addresses statutes and recognition of
customary and religious law; equality in separate
transactions (for example, opening a bank account
or working outside the home)


Indicator shows whether “equal” or “unequal,” but
without showing which transactions trip the indicator
(details may be provided in future editions)


Not included


Labor International Labour Organization Conventions,
constitutions, and statutes—separately


Provisions (based on combination of International Labour
Organization Conventions, constitutions, and statutes);
includes parental leave


Not included


Database of laws Yes Yes Yes


Additional material Examples from case law where confl icting and/
or overlapping sources of law apply (to illustrate
how women’s economic rights are interpreted in
practice)


Information on credit bureaus and small claims courts Statistics on land ownership




263


Index


Boxes, fi gures, notes, and tables are indicated by b, f, n, and t following page numbers.


A
Access Bank Nigeria, 189b
access to assets. See assets, ownership and


control of
access to fi nance. See fi nance, access to
Accumulating Savings and Credit
Associations (ASCAs), 191
action agendas, 19–22, 241–46


assets, ownership and control of,
242–43


business-environment reform, 241–42,
245


fi nance, access to, 243–44
managerial and fi nancial skills, 244
research areas, 22, 245–46


adult literacy. See literacy
Advisory Services Program (Access Bank


Nigeria), 189b
Africa. See Sub-Saharan Africa
Africa Businesswomen’s Network, 221,


227, 228–29b
African Charter of Human and Peoples’


Rights, 164
African Women’s Economic Policy


Network, 225b
age


formal and informal sector choices
and, 103–5, 104f


nonagricultural labor force and, 94


agendas for action. See action agendas
agricultural labor, 36
Akoten, J. E., 184b
Armendariz, B., 203n4
ASCAs (Accumulating Savings and


Credit Associations), 191
assets, ownership and control of,


11–14, 159–79. See also fi nance,
access to


action agendas for, 20, 242–43
constraints on entrepreneurs and,


146–47
future goals and recommendations,


174–77, 176–77b
gender gaps in, xxii, xxiii
human capital and, 71–87
principles and practice in, 174
property rights and, 159, 160–61b
regulations and formal law, 162–63
Women–LEED–Africa database and,


163–73
fi ndings from, 166–73
focus of, 159, 163–65
income, 166, 168–69, 169f
inheritance, 170, 171f
labor, 172–73, 173f
land, 170–72, 172f
nondiscrimination, 166–68,


167–68f




264 INDEX


assets, ownership and control of
(continued)


property regime for marriage, 166,
169–70


Aterido, R., 126, 191–92, 203n6, 211, 215,
218n1


B
bank accounts, 183b, 185f, 243
banking, mobile, 21, 244
Beck, T., 126, 193, 203n6
Benin


fi nance, access to, 189b
gender gaps in, 88n10


Berger, M., 183b
Besley, T., 160b
Bigsten, A., 121, 210
Blanchfl ower, D.G., 91
Bloom, N., 210, 218n1
Bosnia and Herzegovina, business skills


training in, 217
Botswana, fi nancial services in, 194
bribes, 148
Bruhn, M., 184b, 203n3, 207, 216–17, 218
Burkina Faso, gender gaps in, 88n10
Burundi


fi nance, access to, 189b
land rights in, 171


business, lines of. See lines of business
business associations, 17, 22, 222,


224–31, 245
business-environment reforms, 16–19,


221–40
action agendas for, 19, 22, 241–42, 245
business associations, 17, 22, 222,


224–31
advantages, 224, 226
Africa Businesswomen’s Network,


221, 227, 228–29b
broadening horizons for, 227
country-level advocacy resources,


231b
membership benefi ts, 226–27
National Association of Business


Women in Malawi, 229–30b


policy advocacy for, 223–24, 225b
public-private dialogue, 18–19, 22,


221, 231–38, 245
guiding questions on, 237b
inclusion issues, 236–37, 237b
investment-climate reform, 232b
participation, 233–34
role and structure, 231–33, 233f
success in, 234–36, 235–36b


women’s voices, 222–23, 237–38
business owners. See sole proprietors
Buvinic, M., 183b


C
Cameroon, business associations in, 226,


228b
case law, 174, 175b
Center for International Private


Enterprise (CIPE), 229–31b
child mortality, 74
Community of Women Entrepreneurs,


231b
Congo, Democratic Republic of, access to


fi nance in, 189b
constitutions


customary and/or religious law
recognized by, 166


discriminatory provisions, review to
address, 242


labor rights, 172
nondiscrimination provisions, 165,


167f
exemptions from, 12, 166


Women–LEED–Africa database
inclusion of, 164


constraints on entrepreneurs, 19, 133–55
action agenda, 241–42
employment category and, 141–53


corruption, 141, 148–52, 149–52f
fi nance, access to, 133–34, 141,


146–47, 146–47f
government offi cials and, 148, 148f
harassment, 152–53, 153f


objective information on, 141,
142–45f




INDEX 265


subjective information on, 135–41,
136–40f


Consultative Group to Assist the
Poor, 188b


consulting services, 217, 244
control of assets. See assets, ownership


and control of
Convention on the Elimination of All


Forms of Discrimination against
Women, 20, 164


corruption, 141, 148–52, 149–52f
Côte d’Ivoire


education in, 102
enterprise size in, 121
entrepreneurs in, 104, 146, 194, 215
fi nance, access to, 189b


Council for Economic Empowerment
for Women in Africa–Uganda
Chapter, 225b


country patterns of entrepreneurship,
9, 65–89. See also individual
patterns of entrepreneurship


gender equality and opportunity,
71–81, 72–74f


gender gaps within employment
categories, 81–87, 82f, 84–86f


human capital, 71–87
income, 66–71, 67–70f
legal and economic rights, 78, 79f, 81
nonagricultural employment, 66–71
women’s literacy and legal and


economic rights, 75–81, 76–77f,
79–80f


Country Policy and Institutional
Assessment (World Bank),
75, 258


credit, access to. See fi nance, access to
credit histories, 21, 189b, 244
customary law


assess to justice and, 174
land access and, 170–71
in legal systems, 12, 159, 161, 164, 242
nondiscrimination and, 166,


168f, 176b
recognition of, 165


D
decision-making processes, 17, 211
Deininger, K., 161b
De Mel, S., 184b
Democratic Republic of Congo, access to


fi nance in, 189b
Development Finance Company of


Uganda (DFCU), 189b
divorced women, 100–101, 102f, 109.


See also marriage and marital
status


Djankov, S., 91
Dominican Republic, business skills


training in, 217
Drexler, A., 217
Dupas, P., 183b


E
Echaria v. Echaria (Kenya), 175b
economic and legal rights. See legal and


economic rights
Economist Intelligence Unit, 71, 75, 260
education


enrollment rates, 75
entrepreneurs and, 16, 95, 98, 98–100b
fi nance, access to, 181–82
formal and informal sector choices,


10, 11f, 102–3, 103f, 108b
income and, 98, 99–100b
individual patterns of


entrepreneurship and, 92
managerial and fi nancial skills and,


209–10, 210f, 244
nonagricultural labor force and, 94–95
primary school completion, 87n6
prior work experience and, 108b
productivity and, 16, 209–10, 210f
self-employment and, 95, 99b, 101f
wage employment and, 95, 99–100b


electricity outages, 141
employers and employment. See also


labor and labor force; self-
employment


constraints on entrepreneurs and,
141–53




266 INDEX


employers and employment (continued)
enterprise size and, 51
gender gaps in, 43–44b, 81–87
gender patterns in, 31–32
as opportunity entrepreneurs, 32
in Sub-Saharan Africa, 39–40f, 39–44


Employment Bill (Uganda), 225b
Empowering Women: Expanding


Economic Opportunities in
Africa (Hallward-Driemeier &
Hasan), 175, 177n2


enterprises, 47–62. See also entrepreneurs
and entrepreneurship


“female” vs. “male,” 48–50b
formality, 53–54, 54–55f
formation, 109–10, 110–11f
industry, 4–5, 54, 56–61, 57–60f
record keeping, 211, 213f


enterprise size
constraints on business and, 135–36,


137–38f, 142–43f
education and experience of senior


managers correlated with, 105–6b
female participation as owner and, 52,


52–53f
fi rm performance, literature review on


diff erences based on, 121
in higher-income countries, 128b
in Sub-Saharan Africa, 126
thresholds attached to, 51–53


Enterprise Surveys (World Bank)
constraints on entrepreneurs and, 133
described, 33–34b, 249
enterprise size and, 126
on female ownership, 47
“female” vs. “male” enterprises, 48–50b
fi nance, access to, 181, 184
gender gaps and, 122, 127
microdata used (by country), 251–52t
principal data sources, uses and


limitations, 254t
entrepreneurs and entrepreneurship


assets, access to, 71–87
constraints on, 133–55. See also


constraints on entrepreneurs


country patterns of, 65–89.
See also country patterns of
entrepreneurship


education and, 16, 95, 98, 98b, 99–100b
experience in, 93, 214–16. See also


prior work experience
family background in, 106–7, 214–15
fi nance, access to, 198–202
gender inequality in, 29–30
gender patterns in, 30–34
human capital, 71–87
income and, 99–100b
individual patterns of, 91–117.


See also individual patterns of
entrepreneurship


labor force participation and, 34–36
mapping of activities, 4–8
motivation in, 96–98b, 208, 214–16
opportunities, expansion of, 10–19
opportunity vs. necessity, xxi, 32,


96–98b, 215–16, 218
in Sub-Saharan Africa, 36–44
surveys of, 33–34b
training, 216–18
wage employment and, 22, 30b, 246


equality. See gender equality and
opportunities


Ethiopia, legal and economic rights in,
14b, 83, 87b


Exim Bank, 190b
experience. See prior work experience
ExxonMobil Foundation, 228b


F
Fafchamps, M., 147, 183b, 194
family backgrounds in entrepreneurship,


106–7, 214–15
family law, 14b, 161, 161b, 162, 169, 176b,


177, 242
Field, E., 160–61b
FinAccess surveys, 190
fi nance, access to, 14–15, 181–206.


See also assets, ownership and
control of; managerial and
fi nancial skills




INDEX 267


action agendas for, 21, 243–44
constraints on entrepreneurs and,


133–34, 141, 146–47, 146–47f
entrepreneurial choice and, 198–202,


201–2f
entry barriers, 194–97, 195–96f
by individuals, 187–94, 191–92f, 193t


alternative sources, 188b
supply side insights, 188–90b


literature review, 183–84b
loans and, 197–98, 198–200f
in Sub-Saharan Africa, 3, 182–87,


185–86f
fi nancial literacy, 22, 212–14, 216, 217,


244. See also managerial and
fi nancial skills


fi nancial skills. See managerial and
fi nancial skills


Finnegan, G., 183b
FinScope surveys, 190, 203n6, 250


microdata used (by country), 251–52t
Fischer, G., 217
Food and Agriculture Organization,


Gender and Land Rights
database, 262


food preparation industries, 5, 58, 59f
formal and informal sectors, 29–46


data sources, 33–34b
education and, 10, 11f, 102–3,


103f, 108b
expanding opportunities, 30b
formality of enterprises, 53–54, 54–55f
gender diff erences in labor force


participation, 34–36, 35–37f
gender gaps, 42–44b
gender patterns in entrepreneurship,


30–34
types of work, 31b


individual patterns in, 102–10
in Sub-Saharan Africa, 36–44


employers, 39, 39–40f
self-employment, 37–38, 38–40f
wage employment, 39–44, 41f


Fortune 500, 227
Frazer, G., 121


G
Th e Gambia, access to fi nance in, 189b
Gamser, M., 235
garment and textile industries, 58, 59f
GBA (Global Banking Alliance for


Women), 190b
GDP (gross domestic product), 94
Gebreeyesus, M., 121
Gender and Growth Assessment


(GGA), 225b
Gender and Land Rights database


(FAO), 262
gender equality/inequality. See also legal


and economic rights; literacy;
productivity


capturing gender gaps, 42–44b
country characteristics and, 122,


127–29, 129f
creating enabling environment for


gender equality, 30b
cross-country studies of, 29–30
eff ect of gaps in economic rights, xxii,


xxiii
employers and employment, 43–44b,


81–87
fi nance, access to, 183–84b
in human capital, xxi, xxiii, 243–44
indicators of, 71–81
reasons to improve equality, 2–3
in self-employment, 42b, 44b
in wage employment, 37, 40, 41f, 43f,


83, 85f
Gender Inequality Index (UN


Development Programme), 71,
75, 257


Gender Law Library (World Bank), 165
Gender-related Development Index


(OECD), 94, 258–59
gender sorting, 121–31


constraints on entrepreneurs and,
133–55. See also constraints on
entrepreneurs


country characteristics and, 122,
127–29, 129f


in entrepreneurship, 30–34, 63, 157




268 INDEX


gender sorting (continued)
fi rm size and, 128b
in industries, 56
patterns in, 2, 8–10
productivity and, 123–26f, 123–27, 128b
revenue per worker, 124, 124–26f
in self-employment, 31


GGA (Gender and Growth
Assessment), 225b


Ghana
business associations in, 226, 228b
female enterprise ownership in, 50b
fi rm productivity in, 208, 211
investment climate in, 223–24
land rights in, 160b, 171
microenterprises in, 183b


Global Banking Alliance for Women
(GBA), 190b


Global Gender Gap Index (World
Economic Forum), 75, 259–60


Goedhuys, M., 121
Goldstein, M., 160b
Good Practice Manual (IFC), 233
governance, quality of, 127, 134
government offi cials, interactions with,


148, 148f
Goyal, A., 161b
Gray, J., 161b
gross domestic product (GDP), 94


H
Hallward-Driemeier, Mary, xxv, 211, 215,


218n1
harassment, 152–53, 225b
Harding, A., 121
head-of-household status, 20, 94, 165,


168, 169f, 242
Hindu Succession Act, 161b
household shocks, 96–97b
household surveys, 34b, 246, 249–50.


See also surveys as data sources
microdata used (by country), 251–52t
principal data sources, uses and


limitations, 253t
Howarth, R., 183b


human capital
entrepreneurship and, 71–87
fi nance, access to, 21
gender gaps in, xxi, xxiii, 243–44
literacy and, 9, 65, 71
managerial and fi nancial skills and,


207–9, 218


I
Iacovone, L., 126, 193, 203n6
IFC. See International Finance


Corporation
ILO. See International Labour


Organization
income. See also wage employment


country characteristics and, 127
education and, 98, 99–100b
entrepreneurs and, 99–100b
legal and economic rights and, 12–13f,


166, 168–69, 179f
Women–LEED–Africa database and,


168–69
indexes of gender equality across


countries, 257–60
India, fi rm productivity in, 217
individual patterns of entrepreneurship,


9, 91–117. See also country
patterns of entrepreneurship


choice of activity, 91–92, 92b
data collection, 92, 93b
entrepreneur characteristics, 95–102


education, 95, 98, 99–100b, 101f
income, 99–100b
marital status, 98, 100–102, 102f
motivation, 96–98b


formal and informal sector
characteristics, 102–10


age, 103–5, 104f
education, 102–3, 103f, 108b
enterprise formation, 109–10,


110–11f
enterprise scale, 105–6b
marital status, 107, 109, 109f
prior work experience, 105–7,


107f, 108b




INDEX 269


success, measurement of, 112b
line of business, 110–11, 113–15,


113–14f
options not pursued, 114–15


nonagricultural labor force
participation, 94–95


informal sectors. See formal and informal
sectors


inheritance laws, 161b, 165, 170, 171f
interest rates, 212–13
International Finance Corporation (IFC)


fi nance, access to, 187, 188–90b
Good Practice Manual, 233
public-private dialogue and, 222, 223–


24, 225b, 231–32, 234, 235
Women in Business Program, 165


International Labour Organization (ILO),
20, 31b, 164–65, 172, 226, 231b


investments
climate for, 17–18, 22, 133, 222, 232b,


245–46
land and, 160b
start-up capital, 15f, 114, 146–47, 147f,


194–97, 196f


K
Kadritzke, R., 235
Karlan, D., 183b, 207, 216–17, 218
Kenya


bank accounts in, 183b
business associations in, 228b
education in, 102
entrepreneurs in, 104, 146, 194, 215
fi nance, access to, 184b, 189b
informal fi nancial services in, 194
investment climate in, 223–24
marital property in, 175b
microfi nance in, 188b


L
labor and labor force. See also


employers and employment;
nonagricultural labor force


laws on, 165, 172–73, 173f, 176b
market experience, 105–7, 108b


participation in, 31, 34–36
surveys of, 34b


Labour Dispute Bill (Uganda), 225b
Labour Unions Bill (Uganda), 225b
land. See also property rights


investment and, 160b
labor supply and, 160–61b
legal issues, 165, 170–72, 172f
recommendations for closing gaps in


rights, 176–77b
Latin America, mobility between


wage employment and
entrepreneurship, 22


legal and economic rights. See also
individual areas of law (e.g.,
family law)


formal laws and, 162–63
future goals and recommendations for,


176–77b
gender gaps in, 12, 12–13f, 71, 84–85f
income and, 79f, 166, 168–69
labor and, 165, 172–73, 173f
land and, 165, 170–72, 172f
literacy and, 75–81, 80f
principles and practice in, 174
recommendations for closing gaps in,


176–77b
Liberia Better Business Forum, 234
Liedholm, C., 121
lines of business, 110–11, 113–15,


113–14f, 243
literacy


fi nancial, 22, 212–14, 216, 217, 244
gender gaps in, 9–10, 71, 76, 76–77f,


81, 82f, 83
human capital and, 9, 65, 71
self-employment and, 81, 82f, 83, 86f


loans, 146, 169, 184b, 185f, 198–200f, 243
Love, I., 203n3
Lusardi, A., 183b, 219n2


M
Malawi


business associations in, 227, 229–30b
fi nance, access to, 189b




270 INDEX


Malawi (continued)
land rights in, 171
National Association of Business


Women, 229–30b
Malawi Export Promotion Council, 230b
Mali, fi rm productivity in, 208, 211
managerial and fi nancial skills, 16, 207–


20. See also fi nancial literacy
action agendas for, 21–22, 244
education and performance, 209–10,


210f
entrepreneurial training and, 216–18
experience and motivation, 208, 214–16


family background, 214–15
opportunity vs. necessity, 215–16


human capital and, 207–9, 218
measurement of, 210–12, 212–13f


Maputo Protocol, 20
marriage and marital status


formal and informal sector choice
and, 107, 109, 109f


formal laws and, 13, 162–63, 175b
individual patterns of


entrepreneurship and, 93, 98,
100–102, 102f


nonagricultural labor force and, 94–95
polygamous marriages, 170
property regime for, 11–12, 20, 165,


166, 169–70, 242–43
maternal mortality, 74
McKenzie, D., 184b
McPherson, M., 121
MDGs (Millennium Development


Goals), 1, 29
Mead, D., 121
media events, 227, 231b
men


age of, 104, 104f
constraints on entrepreneurs and, 136f
corruption and, 149
education and, 95, 100b, 103, 209, 210f
enterprise size and, 53f
family background and, 106, 214–15
“female” vs. “male” enterprises,


48–50b


fi nance, access to, 15f, 146, 146–47f,
183b


as heads-of-household, 168, 169f
income and, 67f, 68, 69, 70f
individual patterns of


entrepreneurship and, 93
labor force participation of, 35f, 36
land rights and, 170
lines of business and, 114
literacy and, 76, 81
management skills and, 211
mapping of entrepreneurial activities,


4–8, 4–6f
marital status and, 101–2, 109
opportunities, expansion of, 10–19
in self-employment, 42b


metal and metal products, 5, 58
Mexico, access to fi nance in, 203n3
microfi nance, 21, 188b, 244
Millennium Development Goals


(MDGs), 1, 29
Mitchell, O.S., 219n2
mobile banking, 21, 244
mobile phones, 194
“Month of the Woman Entrepreneur,” 231b
mortality, maternal and child, 74
motivation in entrepreneurs, 96–98b,


208, 214–16
Mozambique


fi nance, access to, 189b
fi rm productivity in, 208, 211
land rights in, 171


N
Nagarajan, H., 161b
National Association of Business Women


(Malawi), 229–30b
Niger


female enterprise ownership in, 50b
fi nance, access to, 189b


Nigeria
business associations in, 228b
education in, 102
entrepreneurs in, 104, 146, 194, 215
fi nance, access to, 188–89b




INDEX 271


microfi nance in, 188b
Nobel Prize for Peace, 1, 29
nonagricultural labor force, 36–44, 36–


37b, 38–39f, 66–71, 94–95
nondiscrimination, principle of, 13, 166–68,


167–68f, 172, 175, 176b, 242–43


O
Occupational Safety and Health Bill


(Uganda), 225b
Okonjo-Iweala, Ngozi, xxii
Organisation for Economic Co-operation


and Development (OECD), 71,
75, 94, 258–59


Oswald, A.J., 91
Otsuka, K., 184b
outreach activities, 229b
ownership of assets. See assets, ownership


and control of


P
Pakistan, business skills training in, 217–18
Peru


land rights in, 160–61b
microfi nance program in, 217


policy advocacy for reform, 17, 222,
223–24, 229b


political participation, 74
PPD. See public-private dialogue
Presidential Investors Round Table


(Uganda), 238
prior work experience, 93, 104, 105–7,


107f, 108b, 110
Private Sector Foundation Uganda, 225b
productivity


education and, 16, 209–10, 210f
family businesses and, 215
gender gaps and, 2, 5, 7, 7f, 119, 121–


27, 123–26f, 128b
opportunity and necessity


entrepreneurs, 215–16
of workers, 103–4


property rights. See also land
economic opportunities and, 14b, 159,


160–61b


marital status and, 11–12, 20, 165, 166,
169–70, 242–43


Women-LEED-Africa database and, 9
“protection” payments, 149, 151–52f
Protocol on the Rights of Women in


Africa (African Charter of
Human and Peoples’ Rights), 164


public-private dialogue (PPD)
guiding questions on, 237b
inclusion issues, 236–37
investment-climate reform, 232b
keys to eff ective action, 235–36b
participation, 233–34
role and structure, 231–33
success in, 234–36
women in, 18–19, 22, 221, 231–38, 245


R
reforms in business environment. See


business-environment reforms
religious law, 164, 165
retail industries, 58, 59f
Richardson, P., 183b
Robinson, J., 183b
Roome, N., 203n4
Rotational Savings and Credit Associations


(ROSCAs), 188b, 191
Roy, S., 161b
rural areas. See urban-rural locations
Rwanda


fi nance, access to, 189b
gender equality in, 234
income diff erences in, 193
investment climate in, 223


S
Savings and Credit Cooperative


Organizations (SACCOs), 191
Sawada, Y., 184b
Schoar, A., 207, 216–17, 218
self-employment


characteristics
education, 95, 99b, 101f
income, 68–69, 69f
literacy, 81, 82f, 83, 86f




272 INDEX


self-employment (continued)
entrepreneurs as last resort, 32
gender gaps in, 42b, 44b, 83
gender patterns in, 31–32
in Sub-Saharan Africa, 3, 6f, 37–38,


38–40f
Senegal


education in, 102
entrepreneurs in, 104, 146, 194, 215
fi rm productivity in, 208, 211
gender gaps in, 88n10
public-private dialogue, women’s


participation in, 234
Sero Lease and Finance Ltd., 190b
sexual favors, 8, 152–53, 153f
Sleuwaegen, L., 121
Social Institutions and Gender Index


(OECD), 75, 94, 258–59
Söderbom, M., 121
sole proprietors


constraints facing, 135, 139–40f
fi nance, access to, 134
gender ownership gaps, 51, 52f
how to designate enterprises as


“female” or “male,” 47, 50b
in informal sector, 54


sorting by gender. See gender sorting
South Africa


business associations in, 228b
Enterprise Surveys in, 33b
microfi nance in, 188b


start-up capital, 15f, 114, 146–47, 147f,
194–97, 196f, 200f


Stevenson, B., 161b
Sub-Saharan Africa. See also specifi c


countries
fi nance, access to, 3, 182–87, 185–86f
focus on, 3
formal and informal sectors, 36–44
self-employment in, 3, 4–6f, 37–38,


38–40f
wage employment in, 3, 39–44


surveys as data sources, 10, 22. See also
specifi c surveys


microdata used (by country), 251–52t


principal data sources, uses and
limitations, 253–55t


sources described, 33–34b, 249–50
Swaziland


land rights in, 171
marital status in, 101, 102f


T
Tanzania


fi nance, access to, 189–90b
informal fi nancial services in, 194
investment climate in, 223–24
media in, 231b


Teal, F., 121
textile and garment industries, 58, 59f
treaties and conventions. See also specifi c


treaties
nondiscrimination provisions, 166,


167f
ratifi cation encouraged to ensure


women’s rights, 242
Women–LEED–Africa database


inclusion of, 164–65
Tufano, P., 183b
“Tumaini” savings accounts, 190b


U
Udry, C., 160b
Uganda


business associations in, 228b, 234
entrepreneurs in, 238
fi nance, access to, 189–90b
gender coalition in, 224, 225b
informal fi nancial services in, 194
investment climate in, 223
land rights in, 171
media in, 231b


Uganda Association of Women
Lawyers, 225b


Uganda Investment Authority, 225b, 238
Uganda Women Entrepreneurs


Limited, 225b
Uganda Women’s Network, 225b
United Nations Development Programme


Gender Inequality Index, 71, 75, 257




INDEX 273


National Association of Business
Women (NABW) in Malawi
and, 230b


United States
divorce laws in, 161b
women in business management in, 227


upfront investments. See start-up capital
urban-rural locations


motivation in entrepreneurship and, 97b
nonagricultural labor force and, 94


V
Valdivia, M., 183b, 217
Van Biesebroeck, J., 121
Van Reenen, J., 210
Vital Voices Global Partnership, 228b
“Voices of Women Entrepreneurs” series


(IFC), 223–24, 226


W
Waddington, R., 235
wage employment. See also income


education and, 95, 99b
entrepreneurship and, 22, 30b, 246
gender gap in, 37, 40, 41f, 43f, 83, 85f
in Sub-Saharan Africa, 3, 39–44


WEDGE (Women’s Entrepreneurship
Development and Gender
Equality), 231b


WGI (Worldwide Governance
Indicators), 94


“What Capital Is Missing in Developing
Countries?” (Bruhn, Karlan, &
Schoar), 207


widows, 101, 102f, 109
Wolfers, J., 161b
women


action agenda, 241–46. See also action
agendas


assets, ownership and control of, 159–
79. See also assets, ownership
and control of


business associations and, 222, 224–31
business-environment reforms,


221–40. See also business-


environment reforms
constraints on entrepreneurs,


133–55. See also constraints on
entrepreneurs


country patterns of entrepreneurship,
65–89. See also country patterns
of entrepreneurship


divorced, 100–101, 102f
enterprises and, 47–62. See also


enterprises
equality and gender gap. See gender


equality/inequality
fi nance, access to, 181–206. See also


fi nance, access to
in formal and informal sectors, 29–46.


See also formal and informal
sectors


gender sorting, 121–31. See also
gender sorting


individual patterns of
entrepreneurship, 91–117.
See also individual patterns of
entrepreneurship


literacy and, 75–81
managerial and fi nancial skills,


207–20. See also managerial and
fi nancial skills


mapping of entrepreneurial activities,
4–8, 4–6f


opportunities for, 2–3, 10–19
pregnancy and, 173
in public-private dialogue, 22, 221,


231–38, 245
widows, 101, 102f, 109


Women, Business, and the Law database
(World Bank), 78, 165, 262


Women In Business program
(Development Finance
Company of Uganda), 189b


Women in Business Program
(International Finance
Corporation), 165


Women–LEED–Africa. See Women’s Legal
and Economic Empowerment
Database for Africa




274 INDEX


The World Bank is committed to preserving
endangered forests and natural resources. Th e
Office of the Publisher has chosen to print
Enterprising Women: Expanding Economic
Opportunities in Africa on recycled paper
with 50 percent post- consumer fi ber, in accor-
dance with the recommended standards for
paper usage set by the Green Press Initiative,
a nonprofi t program supporting publishers in
using fiber that is not sourced from endan-
gered forests. For more information, visit
www.greenpressinitiative.org.


Saved:
• 5 trees
• 2 million British


thermal units of total
energy


• 372 pounds of net
greenhouse gases
(CO2 equivalent)


• 2,019 gallons of waste
water


• 135 pounds of solid
waste


ECO-AUDIT


Environmental Benefits Statement


Women’s Economic Opportunity Index
(Economist Intelligence Unit),
75, 260


Women’s Entrepreneurship Development
and Gender Equality (WEDGE),
231b


Women’s Legal and Economic
Empowerment Database for
Africa (Women-LEED-Africa)


on business regulations, 11
comparing to other databases, 261–62
economic and legal rights, 78
fi ndings from, 166–73
focus of, 159, 163–65
human capital and, 71
income, 168–69
inheritance regime, 170
judicial practice and, 242
labor, 172–73
land, 170–72
nondiscrimination, 166–68
property rights and, 9, 20, 169–70
on women’s legal status, 13


Women’s World Banking (2009), 188b


Woodruff , C., 184b
work experience. See prior work


experience
World Association of Women


Entrepreneurs, 227
World Bank. See also Enterprise Surveys


Country Policy and Institutional
Assessment, 75, 258


gender equality and, 1, 29, 71
Gender Law Library, 165
survey data from, 33b
Women, Business, and the Law, 78
women’s associations and, 233–34
World Development Report (2012), 1,


29, 246n1
World Economic Forum, 71, 75, 259–60
Worldwide Governance Indicators


(WGI), 94


Z
Zambia


fi rm productivity in, 208, 211
land rights in, 171


Zia, B., 217






Login