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Measuring the Impacts of Information and Communication Technology for Development
Report by UNCTAD, 2011
Measuring the Impacts
of Information and Communication
Technology for Development
U n i t e d n a t i o n s C o n f e r e n C e o n t r a d e a n d d e v e l o p m e n t
U N C T A D C U r r e N T S T U D i e S o N S C i e N C e , T e C h N o l o g y A N D i N N o v A T i o N . N º 3
Measuring the Impacts
of Information and Communication
Technology for Development
U N C T A D C U r r e N T S T U D i e S o N S C i e N C e , T e C h N o l o g y A N D i N N o v A T i o N . N º 3
New York and Geneva, 2011
ii Measuring the iMpacts of inforMation and coMMunication technology for developMent
Copyright © United Nations, 2011
All rights reserved. Printed in Switzerland
The United Nations Conference on Trade and Development (UNCTAD) serves as the lead entity within the United
Nations Secretariat for matters related to science and technology as part of its work on the integrated treatment
of trade and development, investment and finance. The current work programme of UNCTAD is based on
the mandates set at UNCTAD XII, held in 2008 in Accra, Ghana, as well as on the decisions by the United
Nations Commission on Science and Technology for Development (CSTD), which is served by the UNCTAD
secretariat. UNCTAD’s work programme is built on its three pillars of research analysis, consensus-building
and technical cooperation, and is carried out through intergovernmental deliberations, research and analysis,
technical assistance activities, seminars, workshops and conferences.
This series of publications seeks to contribute to exploring current science and technology issues, with particular
emphasis on their impact on developing countries.
The term “country” as used in this study also refers, as appropriate, to territories or areas; the designations
employed and the presentation of the material do not imply the expression of any opinion whatsoever on the part
of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its
authorities, or concerning the delineation of its frontiers or boundaries. In addition, the designations of country
groups are intended solely for statistical or analytical convenience and do not necessarily express a judgment
about the stage of development reached by a particular country or area in the development process. Mention of
any firm, organization or policies does not imply endorsement by the United Nations.
The material contained in this publication may be freely quoted with appropriate acknowledgement.
This paper explores why measuring the impacts of information and communication technology (ICT) is important
for development – and why it is statistically challenging. Measuring impacts in any field is difficult, but for ICT
there are added complications because of its diversity and rapidly changing nature. A number of impact areas
are identified in section 1, and their relationships explored, in the context of their place in the social, economic
and environmental realms. The result is a complex web of relationships between individual impact areas, such
as economic growth and poverty alleviation, and background factors, such as a country’s level of education and
Existing measurement frameworks are described in section 1, and relevant statistical standards examined. The
latter includes internationally agreed standards for the ICT sector, ICT products and ICT demand. The contribution
of the Partnership on Measuring ICT for Development and its member organizations to ICT measurement, and its
goals for measuring ICT impacts are outlined.
Methodologies used in the measurement of ICT are discussed and compared in section 2 of the paper, and
empirical evidence reviewed, in section 3. Most research conducted has found positive effects of ICT in the
impact areas investigated. However, research has tended to focus on positive, rather than negative impacts;
therefore, the latter tend to be indicated by anecdotal evidence. There is relatively little evidence from developing
countries and there are indications that findings in respect of developed countries may not apply to developing
countries. In respect of both developed and developing countries, there are few studies that provide internationally
The difficulties of ICT impact measurement, major data gaps and the lack of clear statistical standards suggest
several issues for consideration. These are presented in the final section of the paper.
iv Measuring the iMpacts of inforMation and coMMunication technology for developMent
This paper was prepared by the UNCTAD Secretariat and submitted for discussion at the CSTD 2010–2011
Intersessional Panel held on 15–17 December 2010. Sheridan Roberts was the lead consultant. The paper was
finalized by Torbjörn Fredriksson and Diana Korka. Anne Miroux and Mongi Hamdi provided overall guidance.
The cover and graphics were done by Sophie Combette and Laurence Duchemin. Desktop publishing was
done by Laurence Duchemin and the Measuring the Impacts of Information and Communication Technology for
Development was edited by Lucy Annette Deleze-Black.
Useful comments and material were provided by Mariana Balboni and Nestor Bercovich of the Economic
Commission for Latin America and the Caribbean (ECLAC), Seema Hafeez of the United Nations Department
of Economic and Social Affairs (UNDESA), Vincenzo Spiezia and Pierre Montagnier of the Organisation for
Economic Co-operation and Development (OECD), Susan Teltscher of the International Telecommunication
Union (ITU) and Rami Zaatari of the Economic and Social Commission for Western Asia (ESCWA).
Abstract .................................................................................................................................................. iii
1. introduction and conceptual fraMeWorK ............................................................. 1
1.1. World Summit on the Information Society .......................................................................................... 1
1.2. Partnership on Measuring ICT for Development ................................................................................ 1
1.3. Challenges in measuring the impacts of ICT ..................................................................................... 2
1.4. Measurement frameworks ................................................................................................................. 2
1.5. A note on the digital divide ................................................................................................................. 4
1.6. Impact areas of ICT and their relationships ...................................................................................... 4
2. hoW the iMpacts of ict are Measured ......................................................................... 6
2.1. Analytical techniques ......................................................................................................................... 6
2.2. Case studies ...................................................................................................................................... 6
2.3. Statistical surveys ............................................................................................................................... 6
2.4. Panel studies ...................................................................................................................................... 7
2.5. Controlled experiments ...................................................................................................................... 7
2.6. Administrative data ............................................................................................................................. 7
2.7. Other methodologies and data sources ............................................................................................ 7
2.8. Strengths and weaknesses of the different approaches and data sources ...................................... 8
3. eMpirical evidence ....................................................................................................................... 9
3.1. Impacts of ICT on economic performance ........................................................................................ 9
3.2. Impacts of ICT on employment ........................................................................................................ 12
3.3. Relationships between ICT and innovation ...................................................................................... 13
3.4. Impacts of ICT on privacy and security ............................................................................................ 13
3.5. Impacts of ICT on education ............................................................................................................ 13
3.6. Impacts of ICT on health .................................................................................................................. 14
3.7. Impacts of ICT on citizen participation, individuals and communities ............................................ 15
3.8. Impacts of ICT on the environment .................................................................................................. 16
4. suMMary and issues for consideration .................................................................17
4.1. Key issues for consideration ............................................................................................................ 17
1. Introduction and conceptual
Information and communication technology (ICT)
offers the promise of fundamentally changing the lives
of much of the world’s population. In its various forms,
ICT affects many of the processes of business and
government, how individuals live, work and interact,
and the quality of the natural and built environment.
The development of internationally comparable ICT
statistics is essential for governments to be able to
adequately design, implement, monitor and evaluate
ICT policies. This need was emphasized in the Geneva
Plan of Action, paragraph 28, from the first phase of
the World Summit on the Information Society (WSIS):
“A realistic international performance evaluation and
benchmarking (both qualitative and quantitative),
through comparable statistical indicators and
research results, should be developed to follow up the
implementation of the objectives, goals and targets
in the Plan of Action, taking into account different
national circumstances.” (ITU, 2005)
While much progress has been made in measuring ICT
infrastructure and use, measurement of the impacts
of ICT presents a number of statistical challenges.
Against this background, CSTD, at its thirteenth annual
meeting in May 2010, identified measuring the impacts
of ICT for development as a priority area of work
and asked the UNCTAD secretariat1 to prepare this
background paper on the topic. The paper is divided
into four sections. The first provides some background
to why it is important to measure the impacts of ICT
and the challenges involved in that measurement. It
also presents frameworks for conceptualizing and
measuring the impacts of ICT. The second section
discusses different methodological approaches to
measuring ICT impacts. The third section briefly
reviews the empirical evidence in selected impact
areas. The final section concludes and proposes a set
of questions to consider.
1.1. World Summit on the Information Society
The Tunis Commitment from the second phase of the
World Summit on the Information Society expressed
a strong belief in the development potential for ICT,
“The Tunis Summit represents a unique opportunity
to raise awareness of the benefits that Information
and Communication Technologies (ICTs) can bring to
humanity and the manner in which they can transform
people’s activities, interaction and lives, and thus
increase confidence in the future.” (ITU, 2005).
The Geneva Plan of Action, paragraph 6, included 10
targets to be achieved by 2015, of which 6 were to
improve connectivity, for instance, between villages,
educational institutions, libraries, hospitals and
government organizations. There were three targets
on ICT access (radio and television, other ICTs and
the Internet) by the world’s population and a target on
adapting education curricula to meet the challenges
of the information society.2 From the targets, some
important impact areas can be inferred:
• Impacts of ICT access, especially on poor and rural
• Impacts of ICT use on educational outcomes and
the importance of school curricula in preparing
students for the information society;
• Impacts of ICT networks on health institutions and
• Various impacts arising from the availability of
• Impacts of improving access to information and
knowledge by suitable access to electronic content.
The Geneva Plan of Action, paragraphs 14–22,
also suggested a number of action lines, including
the promotion of ICT applications that can support
sustainable development.3 The Tunis Commitment,
paragraph 2, included statements on the potential
benefits of ICT to the world’s population, linking them
to achievement of the Millennium Development Goals
1.2. Partnership on Measuring ICT for Development
Much of the progress in measuring ICT to date is
linked to the work of the Partnership on Measuring ICT
for Development and its member organizations.4 The
Geneva Plan of Action referred to the development
of statistical indicators for “international performance
evaluation and benchmarking” (para. 28). The
Partnership was subsequently launched at UNCTAD
XI in June 2004. The Tunis Agenda for the Information
Society (para. 114) specifically mentioned the
Partnership and its role in the measurement of ICT
The work of the Partnership is directed towards
achieving internationally comparable and reliable
ICT statistics which, among other things, will help
1. INTRODUCTION AND CONCEPTUAL FRAMEWORK
2 Measuring the iMpacts of inforMation and coMMunication technology for developMent
countries assess ICT impacts (Partnership, 2008a).
Its members are involved in various activities
directed towards that goal, including developing and
maintaining a core list of ICT indicators (Partnership,
2010), compiling and disseminating ICT data
(Partnership, 2008b), and the provision of technical
assistance to developing countries. The Partnership
has several task groups, including the Task Group on
Impacts, which is led by OECD and aims “… to give
an overview of the economic and social impacts of
ICTs, how these impacts can be measured and what
the data requirements are”. Its terms of reference
recognize both economic and non-economic impacts
and a variety of methodologies and data sources.5
1.3. Challenges in measuring the impacts of ICT
It may seem obvious that there are significant impacts
of ICT. However, as stated succinctly by ITU (2006):
“You want to know the difference information and
communication technologies make? Try to live without
them… .” Nevertheless, illustrating impacts of ICT
statistically is far from simple, for several reasons:
• There are a number of different ICTs, with different
impacts in different contexts and countries. They
include goods, such as mobile phone handsets,
and services, such as mobile telecommunications
services, which change rapidly over time;
• Many ICTs are general-purpose technologies, which
facilitate change and thereby have indirect impacts;
• It is difficult to determine what is meant by “impact”.
For example, a model proposed by OECD for ICT
impacts (figure 1) highlights the diversity of impacts,
in terms of intensity, directness, scope, stage,
timeframe and characterization (economic, social
or environmental, positive or negative, intended or
unintended, subjective or objective);
• Determining causality is difficult. There may be a
demonstrable relationship and a positive correlation
between dependent and independent variables.
However, such a relationship cannot readily be
proven to be causal.
Many studies have categorized ICT impacts as eco-
nomic, social or (less frequently) environmental. How-
ever, the picture is usually more complex than this. For
example, while some direct impacts of ICT use can
be described as economic, there may be indirect im-
pacts that are social or environmental.6 In addition, di-
rect impacts may be both economic and social, relat-
ed through human capital, which is defined by OECD
as “productive wealth embodied in labour, skills and
knowledge”. From the perspective of the economy,
human capital is a necessary condition for economic
growth and competitiveness (World Bank, 2009). The
use of ICT can enhance human capital in a number of
ways, including through its roles in education, literacy,
acquisition of knowledge and skills, and the develop-
ment of human networks. Economic and social ben-
efits will usually accrue to individuals who are gaining
skills and knowledge by using ICT.
There are other economic benefits of ICT resulting
from its use by households and individuals, described
by OECD (2009a) as follows:
• Final demand for ICT goods and services by
households is an important component of overall
demand, which may stimulate the growth of the ICT
sector and industries that rely heavily on ICT, for
example, media and entertainment;
• The diffusion of ICTs among households may
create a critical mass allowing firms to realize the
full benefits of switching to ICT, for example, in the
delivery of products;
• Use of various ICTs at home may allow firms to
introduce teleworking, which potentially brings
economic, social and environmental benefits.
1.4. Measurement frameworks
It is useful to consider where impacts lie in a broader
information society conceptual model. The model
used by OECD to illustrate the information society
(OECD, 2009a) identifies the following inter-related
segments: ICT demand (use and users), ICT supply
(the ICT sector), ICT infrastructure, ICT products,
information and electronic content and ICT in a wider
social and political context.
Further, OECD (2007) discussed the impacts
components of the conceptual model as follows:7
• Impacts of ICT access and use on individuals, or-
ganizations, the economy, society and environment;
• Impacts of ICT production and trade on ICT
producers, the economy, society and environment;
• Impacts of use and production of content (in
particular, electronic or digital content, which only
exists because of ICT) on the economy, society and
• Influence of other factors on ICT impacts, for
example, skills, innovation, government policy and
regulation, and existing level of ICT infrastructure.
31. INTRODUCTION AND CONCEPTUAL FRAMEWORK
In reference to projects relating to information and
communication technologies for development
(ICT4D), an ICT4D value chain has been proposed
as a basis for impact assessments (Heeks and Molla,
2009). It starts with precursors and proceeds to inputs,
deliverables, outputs, outcomes and development
impacts. The authors consider the last three to be
impacts and distinguishes them as follows:
• Outputs are the micro-level behavioural changes
associated with the ICT4D project;
• Outcomes are the specific costs and benefits
associated with the project;
• Development impacts are the contribution of the
project to broader development goals.
Assessment frameworks relating to ICT4D proj-
ect impacts often include (Heeks and Molla, 2009)
cost-benefit analysis, assessment against project
goals, assessment of the effectiveness of communi-
cations (on changing behaviour or attitudes), assess-
ment of the impact of ICT on livelihoods, assessment
of whether ICT is meeting information requirements,
cultural-institutional impacts and impacts on enter-
prise performance, relations and value chain.8
INFORMATION SOCIETY IMPACTS
Impacts from sectoral
dimension (production and products)
Impacts from demand
dimension (users and usage)
CONTENT AND MEDIA
Sector and products,
Sector and products,
EASIER TO MEASURE?
• Economic impacts
• Strong (impact)
• Micro and meso (narrow)
impacts or individual entities
• Positive impact
• Short-term impacts
• Intented impacts
• Direct impacts
• Intermediate impacts
• Subjective measures
HARDER TO MEASURE?
• Social impacts
• Weak (influence)
• Macro (broad) impacts
- national economy,
• Negative impacts
• Long-term impacts
• Unintented impacts
• Indirect impacts
• Final impacts
• Objective measures
Access, use and
Figure 1. Information society impacts measurement model
Source: OECD, 2007.
4 Measuring the iMpacts of inforMation and coMMunication technology for developMent
An important aspect of measurement frameworks are
definitions and classifications applying to its separate
elements. The following paragraphs provide a brief
overview of key international standards that define ICT
products and the ICT sector, as well as the concept of
ICT demand applied in this paper.
The term “ICT” covers a diversity of ICT products –
goods and services – that are primarily intended to
fulfil or enable the function of information processing
and communication by electronic means, including
transmission and display (OECD, 2009a). These
products have most recently been classified by
OECD in terms of the United Nations Central Product
Classification (CPC) Version 2 and can be broadly
grouped into ICT equipment, such as computers and
peripherals, communication equipment, consumer
electronics and components; manufacturing services
for ICT equipment; business and productivity software
and licensing services; information technology
consultancy and services; telecommunication
services; and other ICT services.9 Components of ICT
are also present in a variety of non-ICT products, such
as scientific and medical equipment, motor vehicles
and manufacturing equipment.10 The manufacture
and use of such products is not usually captured in
ICT impact studies.
The ICT sector includes industries in ICT manufacturing
and ICT services, including wholesaling of ICT
products. The most recent version is based on the
international standard for classifying industries, the
United Nations ISIC11 Rev. 4.12
The concept of ICT demand for the purposes of
this paper is broad and follows OECD (2009a).13 It
includes the following:
• Use of various ICTs at different levels of intensity and
for various purposes;
• Use of, and access to, ICT by individuals, households,
businesses, government and other organizations;
• Financial aspects, such as ICT asset value of, and
investment by, individuals, businesses, government
and other organizations;
• Use of ICT components as intermediate inputs to
production by the ICT and non-ICT sectors (for
instance, electronic components embodied in
It is useful to distinguish the incidence of use (for
example, the proportion of individuals using the
Internet) and the intensity of use. While investment
in ICT is an indicator of intensity, there are a number
of measurement issues that make international
comparison problematic at both the micro and macro
levels. The Partnership’s work on developing core
ICT indicators has resulted in policy-relevant and
comparable indicators of ICT use by businesses and
individuals. While they are of the incidence type, they
range from simple indicators, for example, use of
computers, to more sophisticated applications, such
as receiving orders via the Internet.
1.5. A note on the digital divide
An area that has received significant attention from
policymakers is the question of a digital divide between
individuals, organizations and countries. A major
preoccupation of WSIS was to narrow the digital divide.
For instance, the Geneva Declaration of Principles
referred to the goal of the Declaration as “… bridging
the digital divide and ensuring harmonious, fair and
equitable development for all…” Concern over digital
divides is based on the assumption that ICT is, on
balance, beneficial and that those without access to it
are relatively disadvantaged. For individuals, negative
impacts may range from inconvenience to more
serious outcomes, such as employment disadvantage
due to lack of familiarity with ICT. For economies, the
lack of ICT access may make existing country divides
greater, as the global economy relies increasingly on
ICT to function efficiently and effectively.
While this paper does not discuss studies on the
digital divide, it recognizes its resolution as underlying
much of the impetus for measuring the impacts of ICT.
1.6. Impact areas of ICT and their relationships
The ICT impact areas discussed in this paper and
their relationships are shown in the simplified model
below (figure 2). The model indicates the web of
relationships between impact areas and with the
broader economy, society and environment. Impacts
of ICT arise through ICT supply and ICT demand and,
at a country level, are likely to be influenced by the
• Existing ICT infrastructure, which enables an ICT
critical mass that can amplify impacts;
• Country level of education, skills and income;
• Government ICT policy and regulation, and the level
51. INTRODUCTION AND CONCEPTUAL FRAMEWORK
Figure 2. ICT impact relationships
Government ICT policy and
Level of education, skills, incomeExisting ICT infrastructure
POSITIVE AND NEGATIVE AREAS OF ICT IMPACT
THROUGH ICT SUPPLY AND DEMAND
6 Measuring the iMpacts of inforMation and coMMunication technology for developMent
2. How the impacts of ICT are measured
This section looks at the methodologies and data
sources used in measurement of ICT impacts. It con-
cludes with some comments on strengths and weak-
nesses of the different approaches. The approaches
considered are not mutually exclusive. For example,
analytical techniques will generally use existing survey
or administrative data and case studies may use data
from several sources.
2.1. Analytical techniques
Various analytical techniques have been used
to measure the economic impacts of ICT at the
macroeconomic, sectoral and microeconomic (firm)
level. The main techniques are econometric modelling
using regression, growth accounting and input-
output analysis. Econometric regression models
have also been used in other areas of measurement,
for example, to measure the impacts of ICT use on
educational outcomes (see section 3).
The usual objective of an ICT impact analysis is
to examine the relationship15 between ICT and
productivity, economic growth or employment. The
analysis usually includes other determinants such
as labour, non-ICT capital and, for firm-level studies,
factors such as firm characteristics, skills and
innovation. Included in ICT are the ICT-producing
sector, often split into manufacturing and services,
and ICT diffusion, measured by ICT investment and/
or use. Productivity measures relate a measure of
output (gross output or value added) to one or more
inputs. Economic growth is usually defined in terms
of change in gross domestic product (GDP) or value
added. Employment refers to jobs generated through
the direct and indirect impacts of ICT.
The methodological approaches to measuring pro-
ductivity can be categorized as parametric (such as
econometric techniques) and non-parametric (such
as growth accounting) (OECD, 2001). Economet-
ric techniques estimate parameters of a production
function using a regression model. Growth account-
ing attributes growth in GDP to increases in physical
inputs, such as capital and labour, and advances or
improvements in production technology (ITU, 2006).
It measures multi-factor productivity growth residually
(OECD, 2001). Input-output matrices can be used to
calculate the multiplier effects of ICT.16
Many ICT impact studies examine labour productivity,
that is, how productively labour is used to generate
output (gross output or value added). While relatively
easy to measure, it captures the joint influence of a
number of factors and change cannot be attributed
to any one factor (such as technological change or
productivity of individual workers) (OECD, 2001).
In recent years, much attention has been paid to
firm-level studies of ICT impacts. Such studies can
provide insights not available from macro-level
data, for example, the complementary roles of skills
and organizational change (OECD, 2004). Firm-
level studies are based on analysis (usually based
on econometric regression models) of data at the
individual firm level. Data often come from different
statistical sources and are linked at the firm level.
They include firm performance, ICT investment, ICT
use (varying from use of computers to advanced
e-business applications), firm size and age, skill level,
organizational factors and other forms of innovation.17
In some countries, these data are brought together
in longitudinal databases, which provide data over
different points in time. Economic impacts studied
include labour productivity, multifactor productivity
and value added.
2.2. Case studies
Much of the work on measuring ICT impacts is based
on case studies, often small scale and project based.
They may be longitudinal, examining changes over
time. They are generally very detailed and can involve
a number of qualitative and/or quantitative data
sources. They can take advantage of a number of
existing, as well as new, data sources. Case studies
can be used to explore causation within their scope.
At the same time, case study findings are bound by
the context in which they are conducted. While their
results will not usually be generalizable beyond their
context, they may indicate hypotheses or topics that
could be assessed more broadly.
2.3. Statistical surveys
Data needed to measure ICT impacts can come from
various statistical surveys, including the following:
• Household surveys18 that collect information about
the household entity, including its characteristics,
income, expenditure, and access to ICT;
• Household surveys that collect information from
individuals, including their characteristics, income,
expenditure, how they spend their time, how they
use ICT and their perceptions of particular ICTs;
72. HOW THE IMPACTS OF ICT ARE MEASURED
• Surveys of businesses, including those in the ICT
sector, that collect information such as employment,
economic performance, innovation, expenditure on
ICT, use of ICT and perceptions of ICT impacts;
• Surveys of other entities such as government orga-
nizations that gather information such as employ-
ment details, economic performance, expenditure
on ICT, use of ICT and electronic services offered.
Perception questions provide causal information on
the impacts of ICT, but lack objectiveness (see box
1). However, in respect of individuals’ perceptions, it
has been argued that without subjective indicators,
measurement efforts are bound to be inadequate
2.4. Panel studies
Panel studies are longitudinal and may be survey
based, in contrast with cross-sectional surveys, which
collect data at a point in time across a population. A
panel is selected at the start of the study and data are
collected about its members, for example, individuals
or businesses, during successive periods. Such stud-
ies can be useful in examining impacts, as they can
provide good baseline data and account for time lags.
2.5. Controlled experiments
Controlled experiments can establish causality by
controlling all the independent variables. Therefore,
the experimenter can alter a condition and observe
the effect. In general, the types of studies of interest
for ICT impact analysis cannot be controlled to the
degree necessary to determine a cause-and-effect
relationship. However, where the conditions are
limited, a controlled experiment may be possible.
2.6. Administrative data
An important data source in the field of ICT statistics
is administrative data collected primarily for non-statis-
tical purposes but used to form statistical indicators.
The main examples are telecommunication or ICT in-
frastructure data collected by ITU from member Gov-
ernments, merchandise trade data compiled by the
United Nations Statistics Division and ICT-in-education
data compiled by UNESCO’s Institute for Statistics. All
three sources are used for the Partnership’s core ICT
indicators (ICT infrastructure and access, trade in ICT
goods and ICT in education indicators respectively).
Even though these administrative data are not usually
collected for statistical purposes, through the efforts of
organizations such as ITU, the United Nations Statistics
Division and the Institute for Statistics, classifications
and definitions can be applied to administrative data
collection to enable statistical output.20
2.7. Other methodologies and data sources
Other methodologies and data sources include the
use of focus groups, direct observation and document
examination (Heeks and Molla, 2009). Scenarios may
be used to establish impacts in different situations,
using different sets of assumptions. Forecasting may
be used to estimate the future impacts of ICT and can
involve a number of techniques, data sources and
Box 1. Use of surveys to measure perceived impacts of ICT
Surveys can be used to directly measure impact by collecting self-reported perception data on the benefits and
disadvantages of ICT. The 2005 OECD Model Survey of ICT Use by Businesses includes a question on the benefits of
selling over the Internet. Response categories include reduced transaction time, increased quality of customer service
and lower business costs (OECD, 2009a). Eurostat’s 2008 model questionnaire for the Community Survey on ICT Usage
and E-commerce in Enterprises included a module on perceived benefits of new ICT projects (Eurostat, 2010).
Some official household surveys have asked individuals about their perceptions of the impact of ICT. An interesting
example is a set of questions in the international Adult Literacy and Life Skills surveys of 2003 and 2006 that probed
respondents’ attitudes to computers.19 The surveys are run periodically by several countries in conjunction with
Statistics Canada and OECD (OECD, 2007).
The 2009 Survey on the Internet Usage conducted by the Korea Internet & Security Agency collected data on individual
Internet users’ perceptions of the Internet by asking whether they agreed or disagreed with several positive and negative
propositions about the Internet, including “Internet is important to daily life”, “Information on the Internet is reliable” and
“Groundless rumours are easily created and spread through the Internet” (Korea Internet & Security Agency, 2009).
8 Measuring the iMpacts of inforMation and coMMunication technology for developMent
2.8. Strengths and weaknesses of the different
approaches and data sources
It is clear that there are a number of different meth-
odological approaches and data sources used in
the measurement of the impacts of ICT. Each has
strengths and weaknesses, as described below.
The main analytical techniques used to measure the
impacts of ICT are econometric regression techniques,
growth accounting and input-output analysis. They use
existing data and are therefore likely to be inexpensive,
compared with other approaches. However, they will
be limited to the extent that models are imprecise or
input data are inconsistent, inaccurate or lacking in
availability. A number of data problems relating to use
of analytical techniques for measuring ICT impacts
should be noted (OECD, 2001, 2004):
• Measurement of hours worked for productivity
measures, especially by industry;
• Data from input-output tables may be missing,
dated or not integrated with national accounts;
• Lack of comparable data on ICT investment, espe-
cially those on software,21 and deflators adjusted for
quality change (hedonic price deflators);22
• A number of assumptions are required to estimate
the services from ICT capital;23
• In studies of the ICT sector, lack of value added and/
or production data and hedonic deflators of output
for industries in the ICT sector;
• In respect of some ICT-using services sectors,
productivity growth is difficult to show because of
weaknesses in measures of output, for example,
banking, insurance and health;
• In respect of firm-level studies, comparability
between countries is challenging because of the
diversity of input data and methodologies used. A
number of problems arise from the use of unit record
data, including confidentiality constraints, difficulties
linking records from different data sources, and
small and possibly biased samples because of the
limited overlap between sources.
Case studies can be flexible and shed light on particu-
lar situations. They may be used to explore causation
within their scope applying a variety of data sources,
including perceptions surveys conducted as part of
the study. While their results will not usually be gener-
alizable outside their context, they may indicate other
avenues of enquiry. The cost of case studies is highly
variable; they may be expensive if additional data col-
lection is required.
Well-conducted statistical surveys can provide
representative data about the population being
measured. Their output can be cross-classified by a
number of characteristics such as age of individuals,
or industry of a business. While surveys are generally
expensive to conduct, their results are essential inputs
to many of the analyses discussed in this section.
Survey results are subject to a number of sources
of sampling and non-sampling errors, and a high
degree of harmonization of statistical standards is
required to enable international comparison of survey
output. National statistical surveys of households and
businesses are the basis for the Partnership’s core
indicators on ICT use. 24
Panel studies can be very useful in following change
over time in individual units, for example, people or
businesses. One of their advantages is that such data
enable investigation of causality where the phenom-
ena being investigated are subject to time lags. How-
ever, panel studies can be expensive, especially if the
panel is large, and suffer from attrition, that is, loss
of units over time. For example, individuals may wish
to withdraw from the study, businesses may cease to
Controlled experiments are problematic for this topic,
as the number of factors involved in an ICT impact
can be very large, and some unknown. However, a
couple of examples are presented in this paper and
their results are interesting. Like case studies, results
are likely to be limited in scope but may indicate areas
that could be explored more broadly.
Administrative data on ICT form the basis of many of
the Partnership’s core indicators. Telecommunication
or ICT indicators from ITU and goods trade data from
the United Nations Statistics Division are available
for many countries, are readily accessible and have
long time series of data. They are not indicators of
impact but may be used as inputs in analyses or case
studies. Their usefulness may be limited because
their primary purpose is not statistical. For example,
subscriber data from ITU’s telecommunications/ICT
indicators are often used to measure the penetration
of ICT. However, subscribers are not equivalent to
users25 and impacts will arise from the use of ICT, not
through subscription to ICT services per se.
93. EMPIRICAL EVIDENCE
3. Empirical evidence
This section reviews empirical evidence on the
impacts of ICT, with particular emphasis on developing
countries and the alleviation of poverty. The structure
of the section follows figure 2 and includes a number
of impact areas, covering the economic, social
and environmental realms. The areas covered
are the impact of ICT on economic performance,
employment, innovation (including research and
development), privacy and security, education, health,
citizen participation, individuals and communities,
and the environment. It is important to note that the
coverage does not aspire to be comprehensive.
Moreover, the different impact areas are not mutually
exclusive. For example, innovation is an important
factor in firm performance, which is described in the
first impact area, and education is a key element in
3.1. Impacts of ICT on economic performance
This section discusses the impact of ICT on economic
growth and productivity at the macro, sectoral and
firm levels. Effects on poverty alleviation are also
considered, although the concept of poverty extends
beyond the economic dimension. Following most
studies on the economic impact of ICT, the paper
distinguishes economic impacts arising from an ICT
sector and from ICT diffusion throughout the economy.
Positive macroeconomic impacts of ICT in terms of
increases in productivity and growth can arise from
the following sources (OECD 2004, 2008a):
• Increase in the size and productivity of the ICT
sector, and associated effects such as growth in
industries that provide inputs to ICT production;
• ICT investment across the economy, which
contributes to capital deepening and leads to a rise
in labour productivity;
• Multifactor productivity growth across the economy,
which arises from the role of ICT in helping firms
innovate and improve their overall efficiency.
A growing ICT sector can contribute to aggregate
increases in productivity, GDP and trade. An OECD
study (2004) reported increases in aggregate labour
productivity (value added per person employed)
attributable to a strong ICT sector in some OECD
countries between 1990 and 2002. For example,
Finland’s contribution of ICT manufacturing industries
was 0.2 percentage points during 1990–1995 and 0.8
percentage points during 1990–1995. The relative
figures for the Republic of Korea were 0.8 and 1.0
percentage points. The contribution of ICT services
industries to aggregate labour productivity growth
was typically less than for ICT manufacturing in the
A review of research on macroeconomic impacts
of ICT found that productivity gains in developing
countries were mainly generated by the ICT sector,
rather than through ICT use. The opposite tends to
apply for developed countries, however (UNCTAD,
There is some evidence that the development of
a strong ICT sector has led to poverty reduction,
although there are few targeted studies on this
(UNCTAD, 2010). Opportunities exist, not least in
ICT microenterprises, such as very small businesses
providing mobile phone and Internet services, ICT
repair and ICT training. While not in the ICT sector,26
businesses retailing ICT goods, such as used mobile
phones and recharge cards, will also be created as a
consequence of increased ICT penetration in society.
Banking services related to ICT, such as mobile
money, are also activities suited to small businesses
in low-income countries. Much of this activity is in
the informal sector and, while the activities are not
well measured,27 anecdotally they provide benefits
for proprietors and customers and occupy niches
in which larger formal businesses are not interested
Economic impacts of ICT diffusion have been assessed
in a variety of studies at the macroeconomic, sectoral
and firm levels. The diffusion of ICT includes use,
access and financial aspects. It may be measured
directly through surveys28 or indicated by the levels of
ICT penetration measured by administrative data.
In macroeconomic terms, a direct link has been
established for developed countries between
aggregate labour productivity based on value added
and income per capita, a measure of living standards
(OECD, 2001). In respect of developing countries,
UNCTAD (2010) notes the recent deployment of ICT
networks and the lack of available data to perform
extensive macro-level analysis of the impact of ICT
diffusion. The critical mass effect,29 whereby impacts
of ICT use will only be seen once a certain level of ICT
penetration is reached, is likely to affect the outcome
in developing countries.
10 Measuring the iMpacts of inforMation and coMMunication technology for developMent
Macro-level research has generally shown a positive
link between ICT investment and growth in GDP. Data
for several developing countries on the contribution of
ICT capital to GDP growth over the period 1990–2003
suggested that, in all cases, the impact was modest
relative to the contribution from other capital and
labour (UNCTAD, 2007). In part, that result may have
been due to relatively low levels of ICT penetration in
the countries investigated.
Firm-level studies have been used extensively,
especially in developed countries, to examine the
impact of ICT on firm performance. They typically
involve a number of variables covering ICT, firm
performance and non-ICT factors that might affect
performance. In developed countries, many firm-level
studies have been conducted on the impact of ICT.
They have generally found that use of computers, the
Internet and broadband have a positive relationship
with productivity. However, this varies among
individual businesses according to other factors, such
as skills and innovation. A particular challenge of firm-
level studies is measuring the effect of intangibles,
such as good management and marketing (UNCTAD,
2007). A number of studies have found that ICT has
most impact when accompanied by complementary
investments and changes, for example, in human
capital, organizational change and other forms of
innovation (OECD, 2004). Box 2 describes a study of
firm impacts in a number of European countries.
The results from developed-country firm-level studies
may not always be generalizable to developing coun-
tries. One difference is the level of sophistication of
ICT use. In developed countries, firm-level studies are
increasingly focusing on higher level ICTs such as net-
works and broadband. In developing countries, lower-
level ICTs such as computers are likely to be at least
as significant (UNCTAD, 2008). For an example of a
firm-level study in a developing country, see box 3.
Case study evidence indicates that small and
microenterprises in low-income countries can benefit
from mobile phone use for business purposes,
including improving communication with customers
and obtaining information on inputs and markets
(UNCTAD, 2010).30 Other case studies have indicated
that the provision of Internet access alone may not
bring significant benefits to microenterprises; other
support and tailored information appear to be needed.
The Internet is generally far less accessible to poor
communities than mobile phone technology, especially
in rural areas. However, the Web and Internet e-mail
offer significant potential for communication and
information delivery. It appears that use of the Internet
by small businesses for more advanced applications,
such as e-commerce in developing countries, is
still rare. Several projects have successfully used
combinations of technologies in agricultural areas
of developing countries, for instance, using mobile
phones and radio programmes to provide information
and web platforms to sell produce (UNCTAD, 2010),
Larger enterprises in developing countries may
benefit from the use of more sophisticated ICT
applications (such as web-based e-commerce and
other e-business applications). These benefits may be
transferred to the poor in various ways, for example,
Box 2. Firm level impacts in European countries
The most ambitious firm-level study to date was conducted from 2006 to 2008 and was led by the Office for National
Statistics of the United Kingdom of Great Britain and Northern Ireland. The project included data from 13 European
Union countries and variables on ICT use and relevant non-ICT factors. For each country, firm-level data were drawn
from three basic data sources: ICT usage (from the harmonized European Union community survey on ICT use),
economic characteristics and firm performance (from structural business surveys) and firm population information from
business registers. The productivity measures were labour productivity and multifactor productivity. Metrics using ICT
were computer use, e-sales, e-purchases, fast Internet-enabled and Internet-using employees. Data were compiled by
each country using common methodologies and computer codes to run regressions. Countries that had additional data
collaborated in topic groups; for instance, the Nordic countries worked together on skills.
The results showed that ICT use had reasonably consistent and positive labour productivity effects for manufacturing
firms. For services firms, ICT use had mixed productivity impacts. Finally, industry analysis by country indicated that high-
speed Internet use by employees was positively correlated with productivity in countries where ICT adoption is highest,
but negatively related to labour productivity in three other countries. The authors suggest that returns depend on critical
mass network effects.
Source: Franklin et al. (2009).
113. EMPIRICAL EVIDENCE
by intermediary services for small businesses. In
China, UNCTAD (2010) reported that 20,000 small
businesses work through China’s main e-commerce
platform, Taobao.com, to advertise and sell online.
There may also be spillover benefits. For instance,
in the Ugandan cut flower industry, ICT investment
in a larger enterprise benefitted the whole sector,
expanding employment opportunities for growers.
There may furthermore be gains from ICT diffusion
along the supply chain. However, suppliers who are
not connected may be disadvantaged.
Different ICTs will have different impacts, depending
on a number of factors, including the development
level of a country. Several studies have indicated that
under the right conditions, more advanced ICTs, such
as broadband, can have a greater economic impact
than simpler technologies. At the same time, many
low-income countries still have very limited access
to the Internet, especially at broadband speed (ITU,
2010b). Thus, in these cases, more widely diffused
ICTs, such as radios and mobile phones, may offer
the greatest scope to contribute to poverty alleviation
in the short term, including in combination with other
ICTs (UNCTAD, 2010). The mobile phone can be seen
as a leapfrogging tool, with particularly important
impacts in rural areas – home to three quarters of
the world’s poor (World Bank, 2009). In addition, in
contrast with ICTs such as computers and the Internet,
mobile phone use does not require basic literacy skills
or a high income.
In 2008, the World Bank conducted an econometric
analysis across 120 countries to investigate the
impact of higher penetration of broadband and
other ICTs on economic growth (the average growth
rate of per capita GDP) between 1980 and 2006
(World Bank, 2009).31 It estimated that impacts were
somewhat greater in developing countries than in
developed countries. For developing countries, every
10 percentage point increase in the penetration of
broadband services was associated with an increase
in per capita GDP of 1.38 percentage points; Internet
and mobile phone penetration were associated with a
1.12 and 0.81 percentage point increase, respectively.
The author made the point that the results of such an
analysis may in part be attributed to two-way causality,
where demand for ICT rises with wealth, which leads
to increased penetration, and in turn increases wealth.
Broadband is essential to enable enterprises to make
full use of Internet-based services and applications. In
the United States of America, broadband users were
20 per cent more likely to make online purchases than
narrowband users in 2004 (OECD, 2008b). In Sweden,
enterprises with a high-speed Internet connection
made more use of the Internet, which in turn helped
raise productivity (Statistics Sweden, 2008). Case-
study evidence confirms that broadband use in
developing countries has had positive economic
impacts (World Bank, 2009). For instance, a 2005
study on broadband use by 1,200 companies in six
Latin American countries showed an association with
considerable improvements in e-business processes,
such as process automation through network
integration, better data processing and information
Broadband is also associated with ICT convergence
and this has implications for ICT use. An example is
the convergence of telephone networks and Internet to
enable Voice over Internet Protocol (VOIP) telephone
calls, significantly reducing the cost of telephone-
Negative economic impacts associated with ICT
diffusion have received relatively little attention from
statisticians. They include a range of privacy and
security impacts (see below), as well as systems
Box 3. Firm-level impacts in Thailand
A 2007 study by UNCTAD and the Thai National Statistical Office analysed the impact of ICT on labour productivity in
urban firms with 10 or more employees in the Thai manufacturing sector. A simple comparison showed that firms with
greater ICT use had higher sales per employee and that sales increased with use of more sophisticated ICT (computer to
Internet to Web presence). An econometric analysis, controlling for non-ICT factors, showed that firms with a combined
use of computers, the Internet and the Web had on average 21 per cent higher sales per employee than firms without
any of these ICTs. The greatest increase was noted for firms with computers. The study also found that the link with ICT
is strongest in large firms, though Internet access had the most effect on small firms, and the link with computers was
greatest in young firms.
Source: UNCTAD (2008).
12 Measuring the iMpacts of inforMation and coMMunication technology for developMent
failures, data loss or corruption, inadvertent disclosure
of data and loss of productivity because of employees’
use of ICT, particularly the Internet, during work time. A
possible indirect negative impact is a productivity trap
resulting from updating ICT too frequently to enable
3.2. Impacts of ICT on employment
Information and communication technology has roles
in the creation of employment and self-employment
opportunities. Impacts can be direct, through growth
of the ICT sector33 and ICT-using industries,34 and
indirect through multiplier effects. In economies
increasingly dependent on ICT, individuals will benefit
by having requisite ICT skills, thereby enhancing their
opportunities for employment. Arguably, ICT can also
lead to loss of employment as tasks are automated.
In respect of the ICT sector in low-income countries,
telecommunication services might offer the greatest
opportunities for employment creation (UNCTAD,
2010). Only a small number of developing countries
have a well-developed ICT sector. For those that do,
ICT manufacturing can be significant in employment
terms, sometimes involving the poor. In China, for
example, the ICT sector provides employment to about
26 million internal migrant workers, with evidence that
a large portion of their earnings is remitted to poor
rural and remote areas. Mobile telephony penetration
is increasing dramatically in developing countries (for
example, see ITU, 2010b). In Nigeria, the positive
economic impacts of a growing mobile telephony
industry include growth in the industry itself and
associated industries, creation of direct and indirect
employment, and development of labour force skills
(Pyramid Research, 2010).
Broadband penetration can increase employment in
at least three ways (Katz, 2009). The first is the direct
effect of jobs created in order to develop broadband
infrastructure, the second is the indirect effects of
employment creation in businesses that sell goods or
services to businesses involved in creating broadband
infrastructure and the third is induced effects in other
areas of the economy. The second two ways can
be expressed, through an input-output model, as
multiplier effects. The relationship between broadband
diffusion and employment through these mechanisms
is a causal one, although the estimate of employment
growth relies on a number of assumptions. Data are
presented for Argentina and Chile comparing regional
broadband penetration and employment growth that
show a moderately positive linear relationship.
The Economic and Social Commission for Western
Asia examined the impact of telecentres on the eco-
nomic development of poor communities (ESCWA,
2009). Many of the impacts were on employment op-
portunities. In Egypt, survey data from 2009 indicated
positive impacts accruing to IT Club members, for
example, improving ICT skills and having better job
opportunities. In Jordan, a 2007 survey-based evalua-
tion of the impact of the Knowledge Stations Initiative
on community development showed positive impacts,
affecting males and females almost equally, and indi-
rect employment opportunities through better access
to microloans. In the Syrian Arab Republic, cultural
community centres have trained a large number of
people and appear to have enhanced indirect em-
The potential impacts of IT services and ICT-enabled
services on poverty reduction include employment
and its multiplier effects.35 Because workers in IT
services and ITES industries tend to be relatively well
educated, indirect employment may be the major
employment benefit for the poor (UNCTAD, 2010).
According to the World Bank (2009), women in India
and the Philippines benefit disproportionately from
employment opportunities in IT services and ITES,
with women accounting for about 65 per cent of
professional and technical workers in the Philippines,
and 30 per cent in India. Both are higher participation
rates than in other service industries.
Evidence from six Latin American countries suggests
that Internet use by individuals is associated with
increased earnings (Navarro, 2010). Controlling
for factors, such as education, that relate to wealth
before Internet adoption, the study found significant
differences between salaried and self-employed
workers. For the former, there was a large and
statistically significant positive return to Internet use
on earnings for all countries except Paraguay, where
the difference was large but not statistically significant.
The earnings advantage ranged between 18 per cent
in Mexico to 30 per cent in Brazil and Honduras.
Results showed a positive and statistically significant
effect of use only at work and this was always greater
than the return to use only at other places, including
home. However, use at work as well as other places
displayed higher returns than use only at work. For
self-employed workers, results were similar, with
Internet users having higher earnings. Difficulties
133. EMPIRICAL EVIDENCE
controlling for pre-existing characteristics indicate
that the results show an upper bound on the impact of
Internet use on earnings.
3.3. Relationships between ICT and innovation
Innovation is a broad concept, defined by the Oslo
Manual (OECD and Eurostat, 2005:46) as “the
implementation of a new or significantly improved
product (good or service), or process, a new
marketing method, or a new organizational method
in business practices, workplace organization or
external relations”. Innovation can occur in all sectors
of the economy, including government and higher
education, and includes all forms of research and
experimental development as defined by the Frascati
Manual (OECD, 2002).36
There are several relationships between innovation
and ICT. We saw above that a key determinant of
business and macro-level productivity is innovation,
especially organizational change. More broadly, there
is clearly a strong impact of innovation, especially
research and development, on the development of
ICT goods and services. A study by OECD (2010a)
explored the effects of ICT use as an enabler of
innovation across nine member countries using a
common methodology. Data from business use of
ICT surveys and innovation surveys were linked at the
firm-level and analysed using an econometric model
provided by OECD. Results indicated that higher
ICT use, measured as the number of web facilities,
generally increases the probability of innovation,
with variations on the strength of the relationship by
country, industry (manufacturing or services) and the
type of innovation.
The importance of ICT in research is reflected in WSIS
target 3, which aims “to connect scientific and research
centres with ICTs”. It can be expected to have a strong
impact on research and development activities in all
sectors, as a general purpose technology, although
there seem to be few studies in this area.
3.4. Impacts of ICT on privacy and security
There are a number of adverse impacts of ICT on the
privacy and security of individuals and organizations.
They include commercial losses from denial of service
attacks, data loss through theft or corruption and
disclosure of confidential data. The OECD model
business and household surveys (OECD, 2009a)
and Eurostat’s 2010 model community surveys of
enterprises and households (Eurostat, 2010) included
questions on the incidence of harmful security
incidents. Such questions do not quantify the extent
of impact, although they are useful in measuring
how widespread the problems are. Far more serious
potential negative impacts could arise because of
the increasing reliance of critical infrastructure on
ICT and the serious consequences of failure. Such
impacts can affect societies and economies, as well
as individual businesses (OECD, 2008c).
3.5. Impacts of ICT on education
There is considerable policy interest in the benefits
that ICT can bring to education, which is a particular
focus of the Millennium Development Goals and WSIS
outcomes. The impact of ICT in education has been
assessed in various studies, with mixed results (see
the discussion in Institute for Statistics, 2009).
For example, ICT may deliver significant educational
benefits by providing tools for the teaching and
learning process and by providing the skills needed in
a society that is increasingly reliant on ICT. Conversely,
students who enter such a world without those skills
may be unable to fully participate and suffer from a
digital-divide effect. The digital divide is likely to be
a greater problem for developing countries, where
access to ICT is generally lower than for OECD
countries. Other possible benefits of ICT in education
are improved attitudes to learning, development of
teachers’ technology skills and increased access of
the community to adult education and literacy (OECD,
2010b; Kozma, 2005).
Empirical experiments that are highly controlled can
help establish causal relationships between ICT
use and educational outcomes (Kozma, 2005). In
Vadodara, India, in 2000, 100 primary schools were
each provided with four computers. A controlled
experiment commenced in 2002–03 and ran for two
years. Half the schools were randomly allocated with
training and educational software. Students in those
schools played educational computer games for
two hours a week and scored significantly higher on
mathematics tests than students in the control schools.
The bottom group of students benefitted most, with
girls and boys benefitting equally (Abhijit et al., 2007).
Controlled experiments from the United States, Kenya
and Uganda also showed positive impacts on student
learning arising from some types of use of computers
in specific school subjects, while more general
14 Measuring the iMpacts of inforMation and coMMunication technology for developMent
availability and use of computers at school did not
affect student learning (Kozma, 2005). An analysis
of learning outcomes from the Khanya project in
South Africa showed a positive relationship between
use of the ICT-based Master Maths programme and
mathematics scores on standardized tests (James
and Miller, 2005). The analysis was controlled, with
comparisons made between a random sample of
experimental and control schools. The study found
that scores for learners on the ICT-based mathematics
programmes were significantly better than for other
An OECD study (2010b) reviewed empirical experi-
ments and correlation studies. The conclusion was
that results of the former indicate that ICT in the class-
room improves performance “if certain pedagogical
conditions are met” and the latter, that there is no
demonstrated consistent relationship between ICT
availability and use at school and educational attain-
ment. It is argued that more intensive use of ICT needs
to go hand in hand with an increase in the social capi-
tal of students as measured by other complementary
educational assets. It is clear from OECD’s discussion
that the impact of ICT on school performance is a very
complex topic and not easily measured.
The Programme for International Student Assessment
(PISA) is a triennial study of the knowledge and skills
of 15-year old children in mathematics, reading,
science and general problem-solving.37 It is possibly
the best available vehicle for studying the impact of
ICT on learning outcomes. Results from the 2003 PISA
surveys showed that the mathematics performance
of students without home access to computers was
significantly below that of those with home access. The
gap was significant for all countries in the study and,
in 23 out of 31 countries, a performance advantage
persisted even after accounting for different socio-
economic backgrounds of students (OECD, 2005b).
The performance difference associated with school
access to computers was generally less marked,
with a positive association seen in only about half the
The intensity and type of computer use has also been
found to be related to PISA scores. In the 2003 survey,
the highest performances in both mathematics and
reading tended to be from students with a medium
level of computer use, indicating that excessive
computer use could have a negative impact on
school performance. The 2003 survey also measured
students’ confidence in using computers and the
Internet. For most countries, it found a strong positive
relationship between performance on the mathematics
test and confidence in Internet and routine ICT tasks,
such as opening and saving files. This could suggest
that the quality rather than the quantity of ICT usage
is a more important determinant of the contribution of
ICT to student performance (OECD, 2005b).
Findings from the 2006 survey were similar and
showed positive relationships between science
scores and length of time using computers, frequency
of computer use at different places (with a stronger
relationship associated with home use), a moderate
level of usage and higher levels of ICT confidence.
A more detailed analysis of 2006 data found that for
most countries, the groups of variables that affected
the science score were as follows: students’ char-
acteristics, such as science interest and motivation;
parents’ characteristics; household characteristics;
school characteristics, not including access to ICT;
and frequency of computer use at home and school.
For all countries, average science scores rose with in-
creased frequency of computer use (OECD, 2010b).
3.6. Impacts of ICT on health
Health is mentioned in WSIS documents as an
area where ICT is expected to bring major benefits.
According to ITU (2010a), e-health ICT applications
include electronic health records, telemedicine,
m-health (the use of mobile devices such as mobile
phones for health purposes), decision-support
systems, e-learning and e-journals. In OECD (2007),
the use of ICT was also cited as enabling complex and
networked medical equipment. The study points out
that the Internet can be a useful source of information
about health from an individual’s point of view. There
is no doubt that ICT can also have negative effects
on health, for instance, occupational overuse injuries
associated with computer use. Recycling of e-waste38
is a particular problem for some developing countries,
with adverse health impacts.
The World Health Organization (WHO, 2009:7) has a
broad scope for e-health, defining it as “the use of
information and communication technologies (ICT)
for health” and stating that “eHealth works to improve
health by enhancing patient services and health
systems”. Through its Global Observatory for eHealth,
the Organization has plans to establish indicators
for monitoring e-health and assessing its impact on
health systems (WHO, 2010).
153. EMPIRICAL EVIDENCE
The World Bank (2009) described the impact of mobile
phones on health outcomes in developing countries.
It cited examples of drug inventory management and
monitoring programmes, using the mobile phone as
an interface. According to the World Bank, broadband-
enabled telemedicine is widespread in developed and
developing countries, yet there are few studies on its
effectiveness. It described an eye hospital in southern
India that connects rural communities using a wireless
broadband network. The rural clinics screen about
1,500 patients a month using a web camera. Doctors
at the hospital are able to diagnose problems and
distinguish minor problems that are able to be treated
locally, from more serious problems. This is of great
benefit to individuals, providing rapid diagnosis and
treatment, and in many cases saving the cost and
inconvenience of travel.
The socio-economic and financial impacts of interop-
erable electronic health records and e-prescribing
systems were investigated via several case studies
in Europe and the United States (European Commis-
sion, 2010). Evaluation was based on cost–benefit
analyses; for all cases, the socio-economic gains to
society exceeded the costs. A common feature of all
the studies is that interoperability between electronic
health records and other clinical and non-clinical sys-
tems is a prime driver of benefits. The benefits were
found to be distributed unevenly, with health provider
organizations benefitting most, with an average of 61
per cent of the benefits; patients and medical staff
each gained, on average, 17 per cent of the benefits.
Important observations are that benefits to providers
tend to be long term – with an average seven years
before a net positive benefit occurs – and that solu-
tions are context-specific.
3.7. Impacts of ICT on citizen participation,
individuals and communities
Information and communication technology can facili-
tate democratic processes and increase participation
by citizens. Such impacts may occur as a result of
greater communication and information dissemina-
tion offered by ICTs, through the use of social net-
working sites, e-mail and mobile phones. They are
also frequently enabled by electronic information and
services offered by government (e-government), usu-
ally via the Internet or mobile phones. Of particular in-
terest is how e-government can improve democratic
processes and encourage citizen participation in de-
According to UNDESA, e-participation can change
the dynamics between government and citizens. It
undertakes an international survey of e-government
every one to three years and collects information on
channels offered for online participation of citizens
in public affairs. Results from the 2010 survey show
that developed countries are leading the way in
e-participation, although there are a small number
of developing countries in the top 20 countries.
Examples of greater electronic participation are
provided for Singapore and China. In the latter case,
senior government officials appear to be soliciting,
and responding to, online suggestions posted by
citizens (UNDESA, 2010).
Many of the impacts on individuals of using ICT can
be seen as intermediate, that is, they concern how
ICT is directly changing activities such as shopping,
banking and dealing with government; how people
spend their income; how they spend their time; and
how they communicate with family, friends and the
broader community. These differ from ultimate or final
impacts, such as cost and time savings.
It is clear that ICT use has both negative and positive
social impacts on individuals and communities. On
the negative side, there is increasing concern about
the impact on children of Internet use, for example,
exposure to undesirable content and the overuse
of Internet applications such as online games (see
ITU, 2010c);40 the use of the Internet to disseminate
images of pornography and violence against women;
Internet-based crime; copyright infringement; and
security and privacy concerns.
Positive impacts are potentially numerous and include
the ease and immediacy of communicating, finding
information and accessing services. For minority
groups and those who are socially disadvantaged,
such impacts may be particularly beneficial. The World
Bank (2009) discussed the potential empowerment of
women when they are able to access public services
electronically at home or in the community, and of
minorities when they are able to gain electronic access
to relevant public information on rights and benefits.
Using case study evidence, ESCWA (2009) summa-
rized the positive social impacts of ICT in poor com-
munities as improving communication, facilitating
knowledge-sharing, networking within and between
communities, and improving the delivery of aware-
16 Measuring the iMpacts of inforMation and coMMunication technology for developMent
Final-level impacts are generally harder to measure
than intermediate impacts (OECD, 2007). However,
some survey data on final impacts exist. Statistics
Finland (cited by OECD, 2007) studied the links
between ICT and social capital and found significant
correlations between ICT use and the components
of social capital, community involvement and size of
the social network. An ITU study (2006) cited similar
evidence from South Africa concerning the use of
mobile phones to improve relationships with friends
In respect of perceived impacts, results from the
international 2003 Adult Literacy and Life Skills surveys
included a comparison of respondents’ perceived
usefulness of computers with their literacy, numeracy
and problem-solving skill levels.41 A study using the
survey data found a positive relationship, though there
was no suggestion of causality (Statistics Canada and
The 2009 Survey on the Internet Usage conducted by
the Korea Internet & Security Agency collected infor-
mation from Internet users about their perceptions of
the Internet. Results showed high levels of agreement
with both positive and negative propositions; for ex-
ample, 72 per cent of respondents agreed (“somewhat
agree” or “agree”) that the Internet is important to their
daily lives. The survey also asked about complaints
about using the Internet and included response cat-
egories such as leakage of personal information (31
per cent of respondents) and exposure to obscene
contents’ (26 per cent of respondents) (Korea Internet
& Security Agency, 2009).
A perceptions survey of 1,500 mobile phone users in
Nigeria found that a high proportion reported savings in
travel time and lower costs for travel or entertainment.
Uses of mobile phones included education, health
and entertainment purposes (Pyramid Research,
3.8. Impacts of ICT on the environment
Measurement of the relationship between ICT and
the environment is a relatively new topic. In OECD
(2009b), positive and negative links between ICT
and the environment are discussed. The scope of
environment is limited to aspects where ICT is likely
to be a strong positive or negative factor, that is,
climate change, energy use and waste. The proposed
conceptual model recognizes the following impacts of
ICT on the environment:
• Positive impacts, such as its potential to improve the
efficiency of a range of energy-using processes and
equipment, facilitation of dematerialization,42 and
ICT’s role in climate change monitoring and model-
ling, dissemination of information, and administra-
tion of carbon-pollution-reduction schemes;
• Negative impacts from energy needs and green-
house gas emissions arising from ICT use, the
manufacturing and transport of ICT products and
pollution from disposal of e-waste.
Some impacts of ICT on environmental outcomes can
be easily demonstrated by using scientific knowledge
and other available information. For example, the
greenhouse gas emissions attributable to power-
hungry data servers can be calculated if their power
use and source of power are known.
For some other aspects, impacts are more difficult
to measure, for example, the impact of Internet
purchasing on greenhouse gas emissions. Indirect
impacts are even more difficult to measure, for
example, the positive role of ICT in facilitating a
knowledge-based society with an awareness of
environmental issues. Some data that are relevant
for measuring the potential impact of ICT on the
environment through dematerialization are already
included in the Partnership’s core set of individual
use indicators, for example, the use of the Internet
for various activities. However, as mentioned above,
assumptions would be required to convert that
information into measures of impact.
Despite the importance of the topic, empirical
evidence on the impact of ICT on environmental
outcomes is lacking. Several analytical studies have
attempted to estimate the impact, for example, the
Climate Group and GeSI (2008) estimated that the
ICT sector and ICT products are responsible for about
2 per cent of global greenhouse gas emissions and
that this will grow unless mitigated. They also found
that the greatest potential for a positive impact of ICT
is its use to increase the energy efficiency of industrial
processes that are high greenhouse gas emitters:
power transmission and distribution, the heating and
cooling of buildings, manufacturing and transport.
A 2004 report commissioned by the European
Commission’s Institute for Prospective Technological
Studies found a greater potential for greenhouse
gas reduction through dematerialization (Institute for
Prospective Technological Studies, 2004).
174. SUMMARY AND ISSUES FOR CONSIDERATION
4. Summary and issues for
This concluding section summarizes the findings
presented above and proposes a set of key issues for
Section 1 explains why measurement of the impacts
of ICT is important for policymakers and why it is
difficult. Reasons for the latter include the diverse
and changing nature of ICT, the complexity of ICT
impacts and the more general difficulties of illustrating
a cause-and-effect relationship between the different
These impacts are also contextual. At a country level,
determining factors include human capital, the level
and availability of ICT infrastructure and government
intervention. At a business level, there is significant
empirical evidence that complementary factors, such
as skills and innovation, are important in determining
the degree, and even the direction, of the impact of
ICT access and use.
Reflecting the complexity of measuring ICT impacts,
there is a variety of methodological approaches
(see section 2), which are not mutually exclusive.
Particular approaches appear to be generally suited
to measuring a particular type of impact. For example,
econometric regression models suit the analysis of
firm-level impacts of ICT and case studies are suited
to the evaluation of small-scale ICT projects.
Most of the empirical research examined in section
3 had found positive impacts – for economies, busi-
nesses, poor communities and individuals. Impacts
are direct and indirect, and include impacts across the
economic, social and environmental realms. There is
case study and some macro-level evidence that ICT
may contribute to poverty alleviation. Mechanisms
include trickle-down effects from overall economic
growth, employment and self-employment opportuni-
ties, establishment of microbusinesses that are in the
ICT sector or related to it, such as the retailing of mo-
bile phone cards, and the use of ICTs, such as mobile
phones by small businesses.
While ICT also produces negative impacts, there has
been less research in this area. Evidence of negative
impacts is more likely to be anecdotal and includes
adverse economic and social impacts on individuals
and organizations, and negative impacts on the
Many data gaps remain in the area of ICT impacts,
particularly with regard to developing countries. Evi-
dence for developed countries has tended to focus on
macro- and micro-level analyses, usually supported by
extensive statistical datasets. While the modelling re-
quired for such studies is not necessary difficult, data
requirements are significant and pose barriers to such
approaches for most developing countries. Much de-
veloping country evidence is provided by local case
studies. Although this is useful, the extension to differ-
ent situations or to a country level is challenging.
It appears that evidence from developed countries
may not apply to developing countries, although the
methods of investigation may. In low-income countries,
access to more advanced ICTs is problematic, leaving
a much greater role for ICTs, such as radio, TV and
mobile phones, to have important economic and
social impacts, at least in the short term. There are still
significant data gaps in developing countries on the
core ICT indicators, especially measures of the ICT
sector, and household and business data on ICT use.
While these data do not directly measure the impact of
ICT, they may be used in the analysis of ICT impacts.
Few studies or surveys provide internationally compa-
rable data on the impacts of ICT. The main exceptions
are macroeconomic analyses carried out by OECD
and the World Bank, firm-level analyses covering
mainly European countries, the OECD’s PISA study
(which in 2006 covered 57 countries) and ICT impact-
perceptions data from some surveys that are harmo-
nized internationally, for example, Eurostat’s 2008
Community survey on ICT usage and e-commerce
in enterprises and the Adult Literacy and Life Skills
There are internationally agreed standards for
many aspects of ICT measurement. While these are
necessary for measuring the impacts of ICT, they need
to be complemented by a framework and standards
specifically targeted at measuring the impacts of ICT.
These could include methodologies for econometric
approaches and model questions for perceived
impacts. The work of the Partnership’s Task Group on
Impacts will be important in overcoming this deficit of
4.1. Key issues for consideration
This paper has examined a number of impact areas
indicated by the WSIS targets. Against the discussion
above, a set of questions for further consideration are
18 Measuring the iMpacts of inforMation and coMMunication technology for developMent
• Given the range of ICT impacts and the fairly low
availability of evidence on impacts, should the
measurement of impact in certain areas be given
higher priority than others in the years leading up to
2015? This question is to be seen also in conjunction
with considerations of feasible and affordable data
• This paper has emphasized the importance of
producing relevant and internationally comparable
data needed to conduct impact studies. What
can governments, development partners and
international organizations – especially those that
are members of the Partnership – do to extend ICT
impact indicators? Examples may include setting
statistical standards, accelerating the building of
capacity for the production of relevant statistics and
allocating sufficient funds to undertake surveys.
• From a policy perspective, what types of impact
studies are the most useful? Possibilities include the
- Extending macroeconomic analysis to developing
countries using methodologies applied by OECD;
- Extending the measurement of firm-level impacts
to more developing countries;
- Considering the use of perceptions questions on
surveys of business and household use of ICT.
Several survey models and further investigation
could be useful in checking the validity and
comparability of results;43
- Extending the PISA programme to more developing
countries to shed light on the impact of ICT on
learning outcomes of 15-year olds.
• What can be done to raise awareness among
different stakeholders about the need for the
measurement of impact of ICT?
Abhijit VB, Cole S, Duflo E and Linden L (2007). Remedying education: evidence from two randomized
experiments in India. The Quarterly Journal of Economics. 122(3). Available from
The Climate Group and GeSI (Global e-Sustainability Initiative) (2008). SMART 2020: Enabling the low carbon
economy in the information age. Available from http://www.smart2020.org/publications/.
ESCWA (2009). Impact of ICT on Community Development in ESCWA Member Countries. Available from
European Commission (2010). Interoperable eHealth is Worth it: Securing Benefits from Electronic Health
Records and ePrescribing. Available from http://ec.europa.eu/information_society/activities/health/docs/
Eurostat (2010). Model ICT use questionnaires, years 2002–2011. Available from http://circa.europa.eu/Public/
Franklin M, Stam P and Clayton T (2009). ICT impact assessment by linking data. Economic and Labour Market
Review: 3(10). Available from http://www.palgrave-journals.com/elmr/journal/v3/n10/pdf/elmr2009172a.pdf.
Global Knowledge Partnerships in e-Waste Recycling (2011). www.ewasteguide.info.
Heeks R and Molla A (2009). Impact Assessment of ICT-for-Development Projects: A Compendium of
Approaches. Paper No. 36, Development Informatics Working Paper Series. Available from
Institute for Prospective Technological Studies (2004). The Future Impact of ICTs on Environmental Sustainability.
Technical report EUR 21384 EN. Available from http://ipts.jrc.ec.europa.eu/publications/pub.cfm?id=1208.
ITU (2005). WSIS Outcome Documents: Geneva 200 –Tunis 2005. Available from
ITU (2006). World Telecommunication/ICT Development Report: Measuring ICT for Social and Economic
Development. Available from http://www.itu.int/ITU-D/ict/publications/wtdr_06/index.html.
ITU (2009). Manual for Measuring ICT Access and Use by Households and Individuals. Available from
ITU (2010a). World Telecommunication/ICT Development Report 2010: Monitoring the WSIS Target – A mid-term
review. Available from http://www.itu.int/dms_pub/itu-d/opb/ind/D-IND-WTDR-2010-PDF-E.pdf.
ITU (2010b). Measuring the Information Society 2010.
Available from http://www.itu.int/pub/D-IND-ICTOI-2010/en.
ITU (2010c). Child Online Protection: Statistical Framework and Indicators.
Available from http://www.itu.int/pub/D-IND-COP.01-11-2010/en.
James T and Miller J (2005). Developing a Monitoring and Evaluation Plan for ICT in Education. In: Wagner DA
et al., eds. Monitoring and Evaluation of ICT in Education Projects: A Handbook for Developing Countries.
infoDev. Available from http://www.unescobkk.org/education/ict/online-resources/e-library/elibrary-themes/
Katz RL (2009). Estimating Broadband Demand and Its Economic Impact in Latin America. Available from
Korea Internet & Security Agency (2009). 2009 Survey on the Internet Usage. Available from
20 Measuring the iMpacts of inforMation and coMMunication technology for developMent
Kozma RB (2005). Monitoring and Evaluation of ICT for Education Impact: A Review. In: Wagner DA et
al., eds. Monitoring and Evaluation of ICT in Education Projects: A Handbook for Developing Countries.
infoDev. Available from http://www.unescobkk.org/education/ict/online-resources/e-library/elibrary-themes/
Navarro L (2010). The Impact of Internet Use on Individual Earnings in Latin America.
Economic Commission for Latin America and the Caribbean. Available from
OECD (2001). Measuring Productivity: Measurement of Aggregate and Industry-Level Productivity Growth.
OECD Manual. Available from http://www.oecd.org/dataoecd/59/29/2352458.pdf.
OECD (2002). Frascati Manual: Proposed Standard Practice for Surveys on Research and Experimental
Development. Available from http://browse.oecdbookshop.org/oecd/pdfs/browseit/9202081E.PDF.
OECD (2004). The Economic Impact of ICT, Measurement, Evidence and Implications. Available from
OECD (2005a). Guide to Measuring the Information Society, 2005.
Available from http://www.oecd.org/dataoecd/41/12/36177203.pdf.
OECD (2005b). Are Students Ready for a Technology-Rich World? What PISA Studies Tell Us.
Available from http://www.oecd.org/dataoecd/28/4/35995145.pdf.
OECD (2007). Measuring the Impacts of ICT Using Official Statistics. Working Party on Indicators for the
Information Society. DSTI/ICCP/IIS(2007)1/FINAL.
Available from http://www.oecd.org/dataoecd/43/25/39869939.pdf.
OECD (2008a). The Contribution of the ICT Sectors to Economic Growth in OECD Countries: Backward and
Forward Linkages. DSTI/ICCP/IIS(2008)2.
OECD (2008b). Broadband Growth and Policies in OECD Countries.
Available from http://www.oecd.org/dataoecd/32/57/40629067.pdf.
OECD (2008c). Shaping Policies for the Future of the Internet Economy. OECD Ministerial Meeting on the Future
of the Internet Economy, Seoul, 2008. Available from http://www.oecd.org/dataoecd/1/29/40821707.pdf.
OECD (2009a). Guide to Measuring the Information Society, 2009.
Available from www.oecd.org/sti/measuring-infoeconomy/guide.
OECD (2009b). Measuring the Relationship between ICT and the Environment.
Available from http://www.oecd.org/dataoecd/32/50/43539507.pdf.
OECD (2010a). Are ICT Users More Innovative? An Analysis of ICT-enabled Innovation in OECD Firms.
OECD (2010b). Are the New Millennium Learners Making the Grade? Technology Use and Educational
Performance in PISA. Available from http://browse.oecdbookshop.org/oecd/pdfs/browseit/9609101E.PDF.
OECD and Eurostat (2005). Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data. Third
Edition. Available from http://browse.oecdbookshop.org/oecd/pdfs/browseit/9205111E.PDF.
Partnership on Measuring ICT for Development (2008a). Task Group on Impacts: Terms of Reference.
Partnership on Measuring ICT for Development (2008b). The Global Information Society: a Statistical View,
2008. Available from http://www.unctad.org/en/docs//LCW190_en.pdf.
Partnership on Measuring ICT for Development (2010). Core ICT Indicators.
Available from http://www.itu.int/pub/D-IND-ICT_CORE-2010/en.
Pyramid Research (2010). The Impact of Mobile Services in Nigeria: How Mobile Technologies Are
Transforming Economic and Social Activities. Available from http://www.pyramidresearch.com/documents/
Statistics Canada and OECD (2005). Learning a Living: First Results of the Adult Literacy and Life Skills Survey.
Available from http://www.oecd.org/dataoecd/44/7/34867438.pdf.
Statistics Sweden (2008). Yearbook on Productivity 2008. Papers presented at the Saltsjöbaden
Conference, October 2008. Available from http://www.scb.se/statistik/_publikationer/OV9999_2008A01_BR_
UNCTAD (2007). Information Economy Report 2007–2008: Science and Technology for Development, the New
Paradigm of ICT. United Nations. New York and Geneva.
Available from http://www.unctad.org/Templates/Webflyer.asp?intItemID=1397&docID=9479.
UNCTAD (2008). Measuring the Impact of ICT Use in Business: the Case of Manufacturing in Thailand.
Available from http://www.unctad.org/en/docs/sdteecb20073_en.pdf.
UNCTAD (2009a). Manual for the Production of Statistics on the Information Economy. Revised Edition.
Available from http://new.unctad.org/templates/Page____885.aspx.
UNCTAD (2009b). Information Economy Report 2009: Trends and Outlook in Turbulent Times. United Nations.
New York and Geneva. Available from http://www.unctad.org/en/docs/ier2009_en.pdf.
UNCTAD (2010). Information Economy Report 2010: ICTs, Enterprises and Poverty Alleviation. United Nations.
New York and Geneva. Available from http://www.unctad.org/ier2010.
UNDESA (2010). E-Government Survey 2010: Leveraging e-government at a time of financial and economic
crisis. Available from http://unpan1.un.org/intradoc/groups/public/documents/un/unpan038851.pdf.
UNESCO Institute for Statistics (2009). Guide to Measuring Information and Communication Technologies (ICT)
in Education. Available from http://www.uis.unesco.org/template/pdf/cscl/ICT/ICT_Guide_EN.pdf.
World Bank (2009). Information and Communication Technologies for Development: Extending Reach and
Increasing Impact. Available from http://go.worldbank.org/NATLOH7HV0.
WHO (2009). Global Observatory for eHealth 2009 Survey.
Available from http://www.who.int/goe/data/global_e-health_survey_2009_en.pdf.
WHO (2010). Global Observatory for eHealth Featured Project. Available from http://www.who.int/goe/en/.
22 Measuring the iMpacts of inforMation and coMMunication technology for developMent
1 The UNCTAD secretariat functions as the CSTD secretariat.
2 ITU assessed progress against the targets in 2010 (ITU, 2010a).
3 These are e-government, e-business, e-learning, e-health, e-employment (including teleworking), e-environment,
e-agriculture and e-science (ITU, 2005).
4 Eurostat, ITU, UNCTAD, UNDESA, the United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute
for Statistics, the World Bank, OECD and four United Nations regional commissions (Economic Commission for Africa,
ECLAC, Economic and Social Commission for Asia and the Pacific, and ESCWA).
5 For further information on the Partnership’s objectives and activities, see http://measuring-ict.unctad.org.
6 ESCWA (2009) discussed the overlap between economic and social impacts, for instance, where communicating and
networking for social purposes result in new business opportunities.
7 See also ITU (2006).
8 Each assessment framework includes information on the nature of data and the requirements of data collection. A particular
framework may accommodate different analytical techniques and data sources.
9 An earlier and broader definition of ICT goods was based on the 1996 and 2002 Harmonized System used for classifying
goods trade (OECD, 2005a).
10 The 2003 definition of ICT goods included many such products, whereas the current version does not.
11 International Standard Industrial Classification of All Economic Activities (ISIC).
12 An earlier version, released in 2002 and based on ISIC Rev. 3.1, was somewhat broader, including also manufacturing of
some goods that use ICT products. For more information, see OECD (2009a), Partnership (2010) and UNCTAD (2009a).
13 A note on terminology. Various terms are used in this area of measurement. ICT use refers to use of ICT by entities (except
households). ICT access refers to availability of ICT and is generally used in the context of household access to ICT. A
business or government organization may also have access to an ICT application (for example, an extranet), though it is
generally assumed that it will also use it. ICT diffusion is generally used in a broad sense, analogous to ICT demand.
14 E-government is not treated as a separate impact area in this paper. In terms of ICT demand, e-government can have
positive impacts on the efficiency of government operations. In terms of ICT supply, government as a provider of electronic
services can influence the outcome in all areas, for example, by encouraging the adoption of electronic processes and by
providing information via the Web or mobile phones.
15 Most analytical techniques are unlikely to be able to demonstrate a causal link, though they can demonstrate strong
relationships, some of which may be attributed to two-way causality.
16 Katz (2009) cited a number of studies that used input-output techniques to calculate the multiplier effects on employment
of broadband diffusion through indirect and induced effects. OECD (2008a) also used them to analyse the impacts of the
ICT sector on economic growth by three channels (final demand increases the output of the ICT sector, the ICT sector’s
intermediate demand from non-ICT industries and the supply of intermediate inputs by the ICT sector to non-ICT industries).
17 The Oslo Manual (OECD and Eurostat, 2005) recognizes four types of firm-level innovation, including new organizational
18 Household surveys include population censuses, which can be a useful source of household ICT data.
19 Questions for 2006 were a set of agree/disagree statements about computers, such as they allow the respondent to do
more in less time they have made it easier to get useful information and they have helped the respondent to communicate
with people (OECD, 2007).
20 Partnership (2010) discusses statistical standards applying to core ICT indicators. The Institute for Statistics (2009) provides
guidelines for collection of data on ICT in education.
21 Chapter 4 of OECD (2004) includes a useful discussion of software measurement difficulties.
22 These adjust for price and quality. For example, for computers, the deflator takes changes in speed and memory into
23 Services from ICT capital are estimated from a number of data sources, including ICT investment. Data on the flow of capital
services are used in growth accounting to measure the contribution of ICT to economic growth. OECD (2004), chapter 4,
discusses the estimation of capital services.
24 Guidance on conducting household and business ICT surveys may be found in manuals produced by ITU (2009) and
UNCTAD (2009a), respectively. The ultimate aim of the manuals is to assist in the production of reliable and internationally
compared ICT indicators.
25 The differences apply in both directions; for example, there may be more than one Internet subscriber in a household or
several individuals may use the same Internet access subscription. In respect of mobile phones, many users have more
than one SIM (subscriber identity module) card, with each one counting as a subscription.
26 Using the definition referred to in section 1, ICT retailing is excluded from the ICT sector.
27 The statistics needed for capturing the informal sector are particularly difficult to collect and typically lacking.
28 For example, surveys of ICT use by businesses, from which the Partnership’s core indicators of business ICT use are
29 This arises because of the network nature of ICT – the more people and firms using the network, the more benefits are
generated (OECD, 2004).
30 A perceptions survey of 1,500 mobile phone users in Nigeria found that, in respect of economic impacts,
80 per cent of respondents reported experiencing financial gains from using mobile services. High proportions also
reported gains from better ability to find jobs and improved communication with clients (Pyramid Research, 2010).
31 The study used ITU data on the penetration of different ICTs and controlled for other factors that could contribute to GDP
32 The World Bank (2009) suggests that convergence could have an enormous impact on economic and social development,
for instance, by increasing productivity, lowering transaction costs and facilitating trade.
33 For example, in some developing countries, such as Egypt, Malaysia and Mauritius, the ICT sector accounts for more than
five per cent of the total business sector workforce (UNCTAD, 2010).
34 Some may be new industries based on ICT-enabled business models, for example, web-based businesses.
35 It is common to make a distinction between IT services and ICT-enabled services. The latter group covers front-office
services, back-office services and various forms of knowledge process offshoring. IT services refer to programming, systems
integration, application testing, IT infrastructure management and maintenance, IT consulting, software development and
implementation services, data-processing and database services, IT support services, data warehousing, and content
management and development (UNCTAD, 2009b).
36 Research and development is defined as “creative work undertaken on a systematic basis in order to increase the stock
of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new
37 The Programme is commissioned by OECD and was conducted in 2000, 2003 and 2006. The 2006 surveys are the latest
for which data are available and covered 400,000 students in 57 countries.
38 E-waste stands for waste electrical and electronic equipment and describes old, end-of-life or discarded appliances using
electricity, including computers, consumer electronics and fridges, which have been disposed of by their original users
(Global Knowledge Partnerships in e-Waste Recycling, 2011).
39 WSIS target 6 refers to the role of e-government in contributing to development by enhancing transparency and accountability
and promoting good governance in the public sector.
40 The proposed statistical framework has few impacts indicators and those are of an intermediate nature, for example, the
proportion of children who have ever “ended up on a porn site accidentally when looking for something else”.
41 The 2003 survey involved Bermuda, Canada, Italy, Mexico, Norway, Switzerland and the United States.
42 Use of the Internet as a substitute for material activities, for instance, downloading online newspapers, Internet banking and
downloading digital content.
43 In order to shed light on the impacts of the digital divide, it may be appropriate that non-users of ICT be asked about the
impacts of lack of access. Both positive and negative impacts should be canvassed.
Measuring the Impacts
of Information and Communication
Technology for Development
U n i t e d n a t i o n s C o n f e r e n C e o n t r a d e a n d d e v e l o p m e n t
U N C T A D C U r r e N T S T U D i e S o N S C i e N C e , T e C h N o l o g y A N D i N N o v A T i o N . N º 3