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Liberalizing Agriculture by OECD Countries : Welfare, Growth and Distributional Impact in Developing Countries

Report by Hossain, Sharif M., 2011

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Although it is often argued that liberalization provides opportunities for growth and development in all over the world, there are divergent views about the effects of agricultural trade liberalization on growth and income distribution in developing countries. The developing countries’ main complaint in this regard is that trade distorting activities in agriculture by developed countries adversely affecting their exports and consequently growth, and income and employment of the people therein. There is a general perception among the policymakers and academia that the developing countries would gain much from the removal of existing distortion in the agricultural market because of the tremendous importance of the agricultural sector in their economies. The current paper has analyzed the effect of trade liberalization in agriculture on welfare, growth and income distribution in developing countries, using a computable general equilibrium (CGE) model and indicates that the effect is not similar for all the developing countries.

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Liberalizing Agriculture by OECD Countries: Welfare, Growth and
Distributional Impact in Developing Countries


Sharif M. Hossain
Lecturer, Department of Economics


Jagannath University, Dhaka 1100, Bangladesh
Tel: 880-171-3388-954 E-mail: smhossain@gmail.com



Received: May 9, 2011 Accepted: May 31, 2011 doi:10.5539/ijef.v3n3p167

Abstract
Although it is often argued that liberalization provides opportunities for growth and development in all over the
world, there are divergent views about the effects of agricultural trade liberalization on growth and income
distribution in developing countries. The developing countries’ main complaint in this regard is that trade distorting
activities in agriculture by developed countries adversely affecting their exports and consequently growth, and
income and employment of the people therein. There is a general perception among the policymakers and academia
that the developing countries would gain much from the removal of existing distortion in the agricultural market
because of the tremendous importance of the agricultural sector in their economies. The current paper has analyzed
the effect of trade liberalization in agriculture on welfare, growth and income distribution in developing countries,
using a computable general equilibrium (CGE) model and indicates that the effect is not similar for all the
developing countries.
Keywords: Trade liberalization, Agriculture, GTAP, CGE Model
1. Introduction
Agriculture is the most important sector of the economies of developing countries. The sectoral contribution of
agriculture to GDP is within the range of 30 to 60 percent in about two thirds of the developing countries. It is also
providing employment to the large segment of the population ranging from 40 to 90 percent in most of the
developing countries and the principle sources of foreign exchange amounting 25 to 95 percent in three fourth of
developing countries (FAO 2002, p. 7). Thus a sustainable agriculture is the fundamental to ensure food security,
poverty alleviation and overall growth and development in developing countries. Strong backward and forward
linkages between agriculture and non agriculture sector further stimulate growth and development. In most of the
developing countries agro and agro based products are the main export items. An increase in trade of these items is
expected to contribute not only to growth of agriculture sector but also to manufacture and service sectors, because
of strong linkages between these sectors. Although trade provides the opportunity of economies of scale,
specialization and utilization of abundant factors, the relationship between trade and growth are complicated. In
economic literature there are divergent views about the effects of agricultural liberalization on growth and income
distribution in developing countries. Although it is often argued that liberalization provides opportunities for growth
and development in all over the world, the developing countries, and particularly the least developed countries
(LDCs) have yet to get any benefits of trade liberalization. In fact, the share of agricultural export by LDCs as a
percentage of world agricultural export has been declined from 3.2 percent in 1970-79 to 1.9 percent in 1980-89 and
a more 0.9 percent in 2000-04 (FAO 2007, p. 5).
The negotiations of liberalization in agriculture were initiated in the “Doha Round” of the World Trade Organization
(WTO). But the governments of the member countries were far away from the Agreement on Agriculture (AoA)
which sets the quantitative targets for reduction in trade distorting activities i.e., import tariff, domestic support and
export subsidies. While significant progress has been made in liberalizing manufacturing products among developed
member countries, little progress has been made on export interest to developing countries (Orden et al. 2002). The
Cancun Ministerial meeting also failed because of the inflexibility on the part of the developed countries to
withdraw hefty subsidies given to agriculture in these countries through various means. The developing countries’
main complaint in this regard is that such subsidies in the developed countries keep the prices of their farm products
low acting as a kind of barrier against the entry of such commodities from the developing countries. In cases where
a developing country is dependent on the export of one or two major agricultural commodities such as cotton in
some of the Sub-Saharan African nations, the tariff wall against its entry into the developed countries may be very
high adversely affecting their exports and consequently growth, and income and employment of the people therein.1




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There is a general perception among the policymakers and academia that the developing countries would gain much
from the removal of existing distortion in the agricultural market because of the tremendous importance of the
agricultural sector in their economies (Koning & Andersen 2007, pp. 1-2). However, policy interests are not similar
among developing countries. Some net exporters of agricultural commodities, such as Brazil and Argentina, would
benefit from trade liberalization and multilateral removal of domestic support. In contrast, the net food importing
countries, such as Egypt and Middle East countries, benefit from existing distortion because it depressed the world
price of food imports (Fabiosa et al. 2005, p. 318). Against this backdrop one pertinent question may be raised:
whether trade liberalization in agriculture by the developed countries will affect them similarly? For countries which
are net food importers the question is more specific. Will they benefit from such withdrawal as a food importing
country? The paper tries to address these questions using computable general equilibrium (CGE) model. This paper
also analyzed the effect of trade liberalization in agriculture on growth and income distribution in developing
countries.
The paper is organized as follows. Following the introduction section 2 gives an overview of the trade liberalization
under WTO agreement on agriculture. Section 3 analyzes the linkages between trade liberalization and growth in
developing countries. Implications of agricultural trade liberalization using a computable general equilibrium model
are analyzed in section 4 while section 5 draws the conclusion.
2. Trade Liberalization under WTO Agreement on Agriculture
The establishment of WTO in 1995 first introduced the rules of international trade in agricultural commodities under
the Uruguay Round Agreement on Agriculture (AoA). The support to agriculture is provided in more than one way
in the developed countries. There is the usual tariff against imports from the developing countries thus discouraging
competition within the domestic market. Export subsidy is provided for exporting certain farm goods. Output price
support is a major element of the support while subsidy is provided also for lowering the price of inputs. All these
are to be withdrawn according to certain formula under AoA. Therefore, the AoA has three supports namely market
access, domestic support and export competition under which all WTO member countries except LDCs are
committed to reduce the trade distorting activities according to following schedule.
[Insert Table 1 here]
The Article 4 of the AoA affirmed that all barriers to imports should be subject to tariffs only. Therefore, before
implementing the tariff reduction schedule, countries had to convert all non-tariff measures to their tariff equivalents
– a process called tariffication. After completing the tariffication and establishing the tariff equivalents, tariff
reduction were applied to bound tariffs. Developed countries were committed to reduce tariff by an average of 36
percent with a 15 percent minimum tariff cut for any specific product, over a six year period. Developing countries
had lower targets of 24 percent reduction with a 10 percent minimum tariff cut over ten years. Similar efforts were
made to reduce the distorting effect of domestic support. All sort of domestic supports were classified into three
categories by the degree of distortion: the Amber Box, the Blue Box and the Green Box.2 Amber Box supports
became the core of the negotiation and are subject to WTO reduction commitments. Supports in this category are
expressed in terms of Aggregate Measurement of Support (AMS) which includes all support in one single figure.
The developed countries were committed to reduce AMS by 20 percent within six years, while developing countries
to reduce it by 13 percent within ten years. Countries with no Amber Box supports agreed not to use supports over a
de minimis level of 5 percent (10 percent for developing countries) of the total value of agricultural production. The
AoA decided to treat export subsidies separately from domestic support. The developed countries were to reduce the
value and volume of export subsidies by 36 percent and 24 percent respectively over a period of six years. For
developing countries, the value and volume of export subsidies to be reduced by 24 percent and 10 percent
respectively over a ten year period (Table 1). The LDCs are exempted from all the reduction commitments
(ActionAid 2004, pp. 3-5).
While the AoA made some significant progress in specifying initial commitments on reduction of tariffs and
domestic supports, developed countries has shown no willingness to reduce subsidies and other protectionist
measures in agriculture. The total support provided to agriculture in the OECD countries, measured by Total
Support Estimate (TSE), increased from US$ 374 billion in 1996 to US$ 382 billion in 2005. The support provided
to producers was US$ 280 billion in 2005. More than 70 percent of farm support in OECD countries is provided in
the form of trade distorting market price support and payments linked to production. In 2005, the respective value of
TSE in EU and USA were US$ 153 billion and US$ 105 billion respectively (Mouhamad 2008, pp. 3-7). EU tops
the list in providing the farm support. Of the worldwide total producers support, EU provided 40 percent of the total.
The respective shares of USA, Japan and Korea had been 21, 20 and 7 percent. The support to farmers in these
countries is such that in Switzerland, Norway, Korea and Japan for every one hundred dollars of farm earning, 60-70




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dollars is a hand out from the government. In EU, it is 35 dollars while in the USA and Canada these are lower at
around 20 dollars. In some countries such as Norway, Japan and South Korea the level of support provided to
agriculture more or less matched its contribution to GDP in those countries (Asaduzzaman 2004, p. 929).
The WTO negotiations notwithstanding, the fact remains that despite some noises by some countries and groupings,
the level of support is likely to remain the same in some disguise or other. For that matter, there are EU proposals to
decouple some of the support from production decisions. However, others contend that if farmers are given money
not to produce, they will remain in farming and over-produce. In USA, the signs are more ominous. With the Farm
Security & Rural Investment Act 2002 in USA farmers have been given guaranteed prices for rice, wheat, corn,
soyabean & cotton for a period of six years. This is highly trade-distorting, to say the least, and this in a country
which preaches free-market principles to others.
3. Linkage between Trade Liberalization and Growth in Developing Countries
Poverty reduction is the main objective of the government policy in most of the developing countries. In the current
globalized world it is widely accepted by the policymakers and academia that trade liberalization can enhance
economic growth and reduce poverty through redistribution of income and wealth (Dollar 1992; Dollar & Kraay
2004; Sachs & Warner 1995; Michaely et al. 1991; Onafowora & Owoye 1998). In contrary, some argue that in
short run trade liberalization is harmful for growth and poverty reduction, and increase inequality in the developing
countries (Weller & Hersh 2002; Sala-I-Martin 1997; Anwar 2002; Akmal et al. 2007). Open economy usually leave
the poor segment of the population behind the poverty line. This is because developing countries usually suffer from
negative adjustment and distributional effects from trade liberalization. The linkage between trade liberalization and
growth is not simple. Although there are some empirical evidences for the argument that liberalization enhance
economic growth and reduce poverty by increasing income, it is not widely accepted nor proved. At the same time
also there is no proof that liberalization is of destructive to growth (Winters et. al. 2004, p. 74). Liberalization has
both direct and indirect effect on economic growth and income distribution. Following export-led growth strategy, it
is expected that export growth can generate economic growth and foster poverty reduction. If protectionist measures
are beneficial for the wealthy segment of population, then liberalization generally distribute income and wealth in
favor to poor. But the assumption behind this conception is less relevant in the current globalized world (CUTS
2004, p. 1).
In a liberalized world commodity prices are determined by the world market prices. A change in border prices
arising from trade liberalization directly transmitted to domestic market. This change in prices may affect the terms
of trade which is considered as the primary determinant of growth of a country (Chemingui & Thabet 2008, p. 9).
Now the question is whether the changes in price are really transmitted down to the poor segment of the population.
If it does not the effect of liberalization on distribution of income are likely to be weak. Liberalization is also often
related with the creation and destruction of the local market. While liberalization can create opportunities to produce
large numbers of commodities because of increased demand in world market and positive terms of trade effects, at
the same time some industries may cease to exist as a result of increased import competition. When liberalization
creates markets a country can experience welfare gain form technological change and diffusion of knowledge. But
when liberalization destroys markets poor people suffer from substantial income loss (Winters et. al. 2004, pp.
87-89). The changes in prices also change the wages of workers. According to Stolper-Samuelson model an
increased price of labour intensive commodities will increase the wage of workers in that industry. But the
Stolper-Samuelson model is only true if all market are functioning properly (Chemingui & Thabet 2008, p.9).
Furthermore, even if unskilled-labour wages is increase as a result of increased prices it will have positive
distributional effect only if poor household are depends on the unskilled-labour wage earners (Winters et. al. 2004, p.
97).
In recent years, agricultural trade liberalization and its impact on growth and distribution in developing countries
have attracted growing attention. A recent study by Pereira et. al. (2010) simulated the WTO agricultural production
and export subsidy reduction requirement, and the application of the Harbinson approach, and Swiss formula to
reduce import tariffs.3 The paper concludes that Brazil and China experience a positive GDP growth rate while India
shows a negative GDP growth rate in all scenarios, except in that which replicates the Uruguay Round. Brockmeier
& Pelikan (2008) reveals that the heights of the agricultural tariff cuts and the kind of tiered formula applied are
most important for the outcome of the Doha Round. While manufacturing protection has declined worldwide
following substantial reforms of trade policies, most industrial countries still protect agriculture at high level (Aksoy
& Beghin 2005, p. 1). Trade protection usually introduces anti-agricultural bias, so removal of price controls on
agriculture will raise the income of poor farmers in rural area. But higher food prices and removal of consumer
subsidies may hurt rural landless (in the short-run) and urban poor consumers (Anwar 2002, p. 6). From the
preceding discussion it is obvious that the effect of agricultural trade liberalization on growth and distribution in




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developing countries is not clear-cut. The effects on developing countries depends crucially on which countries
(developed or developing) are liberalizing there agriculture and in what extent. At the same time the effects might be
different depending on the agricultural activities of different developing countries.
4. Implications of Agricultural Trade Liberalization – A CGE Analysis
In this section Global Trade Analysis Project (GTAP) model and data have been used to find out the implications of
agricultural trade liberalization on developing countries. GTAP is a multi-country Computable General Equilibrium
(CGE) model which confines different aspects of global economic activities. This is a linearized comparative static
model for CGE analysis. GTAP provides opportunities to policy makers and academicians to use the global model
and database for policy formulation and implementation.
4.1 An Overview of GTAP Model4
In GTAP model each region has a single representative household. The income of these households mainly depends
on factor income and tax revenue. The allocation of expenditure of these households is classified as private
expenditure, government expenditure and savings, according to a Cobb-Douglas aggregate utility function. In GTAP,
private consumption and government consumption expenditures are described by Constant Difference of Elasticities
(CDS) expenditure function and Cobb-Douglas function respectively. Constant Elasticity of Substitution (CES)
function is applied to substitute same type of domestic and foreign produced goods.
In case of production, GTAP model applies constant returns to scale production function. Leontief and CES function
is applied to describe the technology. Two broad categories of inputs are used to maximize profits by producers;
these are intermediate inputs and primary factors. For a given level of output the input allocation assumed to be done
efficiently to minimize the total cost of production. The factor movement is restricted among the region but
intermediate input can be used from domestically produced or imported input goods. The GTAP database covers all
the bilateral trade, transport and protection data that link 113 country/regional economic databases. These transport
and protection data drive a wedge between prices in regions, i.e., the same products may be more expensive in one
region than in another because of the protection. International trade is modelled by tracing all bilateral flows. In
GTAP, international capital flows are governed by a global bank. This bank collects savings and uses these for
international investments. Since savings are polled by the global bank before being sued for investments there is no
tracing of bilateral capital flows. The version 7 of GTAP database (which is used to analyze the impact of
agricultural trade liberalization in this paper) represents the world economy in 2004. This version has 113 regions,
57 commodities and 5 factors of production.
4.2 Region and Commodity Aggregation
The main objective of this paper is to assess the impact of agricultural trade liberalization by OECD countries on
developing countries. Keeping this view in mind OECD countries and developing countries are separated as
different regions. Developing countries are divided into five regions namely East and South East Asia (ESEA),
South Asia (SA), Latin America and Caribbean (LAC), Middle-East and North Africa (MENA) and Sub-Saharan
Africa (SSA). The strategy for this aggregation is to separate developing countries according to different stage and
patterns of development to analyze how the countries are affected by liberalization. In case of commodity
aggregation agricultural commodities are separated from manufacturing and service sector. Therefore, 57
commodities are aggregated into 3 namely Agriculture, Manufacturing and Service (Table 2). There are five factors
of production in GTAP model which are kept unchanged. The factors of production include land, unskilled labor,
skilled labor, capital and natural resources.
[Insert Table 2 here]
4.3 Simulation Scenarios
In this paper four simulations have been performed to examine the agricultural trade liberalization by OECD
countries. Full liberalization of all agricultural support by OCED countries is considered in simulation 1 where
OECD countries eliminated all three types of agricultural support i.e., import tariff, domestic support and export
subsidies of their agricultural production and trade. Simulation 2 implements a 50 percent liberalization of all
agricultural support by OECD countries. However, an instant policy that removes all agricultural supports is not
plausible for a country. Therefore, two more simulations have been designed by eliminating some of these supports.
Simulation 3 eliminates import tariff and input subsidies while only import tariff is eliminated in simulation 4.
Simulation scenarios are summarized in Table 3.
[Insert Table 3 here]
4.4 GTAP Simulation Results of Agricultural Trade Liberalization
In this section, the results of GTAP simulation are presented and analyzed. In GTAP welfare effects are measured as
equivalent variation (EV) which is equal to the difference between expenditure required to obtain the new level of




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utility at initial prices and the initial expenditure. The equivalent variation associated in each region with the
simulation scenarios is considered here both as total variation, and in its components arising from the changes in the
terms of trade, resource allocation and investment-saving effect, and is presented in Table 4. It shows that only
MENA countries experiences high welfare loss from the first two simulations. The total welfare loss for MENA
countries is 941 million US dollar in simulation 1, in which OECD countries completely liberalized their agriculture
sector. In case of partial agricultural trade liberalization (50 percent reduction of all sort of agricultural support) by
OECD countries, designed in simulation 2, MENA countries experiences a loss of welfare of around 475 million US
dollar. However, in simulation 3, where OECD countries completely eliminated import tariff and input subsidies in
agriculture, MENA countries experience welfare gain amounting US dollar 200 million. Elimination of import tariff
by OECD countries is welfare enhancing for MENA countries while removal of input subsidies are welfare
worsening, which is also confirmed from the results of simulation 4. Therefore, tariff elimination effect outweighs
the removal of input subsidies effect and MENA countries experience a positive welfare gain in simulation 3. ESEA,
LAC and SSA countries experience a substantial welfare gain in almost all the simulations. The welfare gain is
higher in simulation 1 and simulation 3 for these countries. ESEA and SSA countries experience highest welfare
gain in simulation 3 which is around 2601 million US dollar and 522 million US dollar respectively while for LAC
countries, the welfare gain is highest in simulation 1 amounting US dollar 2931 million. The different groups of
developing countries experience different welfare effects based on their trade pattern of agricultural commodities.
Furthermore, tariff and subsidies have diverse effects on different country groups. Removal of subsidies affects
positively to the net importers of agricultural commodities while removal of tariff by OECD countries affects
positively to those developing countries which exports agriculture to OECD countries. MENA countries are net
importers of agricultural commodities and withdrawal of agricultural tariff and all sort of domestic subsidies by
OECD countries is negatively affecting those countries as depicted in simulation 1 and 2. When all sort of domestic
subsidies are removed by OECD countries, subsidy effect outweighs tariff effect and MENA countries experiences
negative welfare effects. However, when only input subsidies are removed by OECD countries tariff effect
outweighs subsidy effect resulting net welfare gain for MENA countries. ESEA, LAC and SSA countries are net
exporter of agricultural commodities, thus experience a positive welfare gain in all the simulations. SA does not
experience a substantial welfare loss because it comprises both net exporting and net importing countries of
agricultural commodities. Therefore, the net welfare gain by exporting countries and net welfare loss of importing
countries offsets each other.
[Insert Table 4 here]
The sources of welfare gain also reported in table 4 which is mainly attributed to allocative efficiency, terms of trade
(TOT) effect and investment-saving (I-S) effect. Allocative efficiency refers to the efficient sector-wise allocation of
scarce resources to produce the optimal combination of output. TOT effect refers the changes in relative prices of
exports and imports and I-S effect refers the changes in price of capital goods and savings (Raihan & Razzaque
2007, p. 20). It is expected that the reduction of agricultural distortion by OECD countries would increase the
allocative efficiency of developing countries. However, Table 4 shows that, in first two simulations, all the
developing country groups except LAC experience loss in terms of allocative efficiency. This is because
liberalization by OECD countries failed to reallocate the resources from the inefficient sectors to the more efficient
sectors and also because of the pre-existing distortion in other sectors (manufacturing and service sectors) of these
counters. For this reason, resource reallocation between agricultural sector and other distorting sectors results a net
loss in terms of allocative efficiency. Unlike first two simulations MENA countries and SSA countries experience
an increase in allocative efficiency in simulation 3. These opposite results are achieved because, efficient
agricultural sub-sectors in MENA and SSA country group become more competitive as a result of elimination of
tariff and only input subsidies by OECD countries. However, as reflected in last simulation, only input subsidy
elimination by OECD countries does not have any positive allocative efficiency for developing country. The second
component of welfare change is terms of trade (TOT) effects. Agricultural trade liberalization raises the food price
in international market (Table 5). This price movement improves the TOT for countries that are net exporters of
protected farm products, while net food-importing countries are expected to lose. The net exporters of agricultural
commodities experience a positive TOT effects because of the increased world price of agricultural commodities. As
expected the TOT effects is positive for all developing country groups except MINA countries in first two
simulations. TOT gains for ESEA, SA, LAC and SSA are 3362 million US dollar, 74 million US dollar, 2744
million US dollar and 307 million US dollar respectively in first simulation. MENA countries which is net food
importer, experience a loss of US dollar 304 million in simulation 1. In simulation 3 the TOT effect for MENA
countries is US dollar 147 million, generated by relative price increase in exportable agricultural sub-sectors in
MENA countries. The I-S effect on welfare is similar to TOT effect, since each region exports capital goods to the




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global bank and imports savings from the global bank. The I-S effect is substantially negative only for ESEA
countries, as reported in Table 4.
[Insert Table 5 here]
Table 5 reports the macroeconomic impact of agricultural trade liberalization on developing countries. It is observed
from the table that all the developing country groups experience an increase in real GDP as a result of increased
agricultural output. Liberalizing agriculture by OECD countries increases the price of agricultural commodities in
world market. Therefore, imports of agriculture become more expensive and exports of agriculture become more
profitable in developing countries. In such a situation, producers get incentives to produce more to substitute import
and promote export in agricultural commodities. This have a positive effect on real GDP growth rate and it can be
argued that agricultural liberalization by OECD countries is growth enhancing for developing countries. It should be
mentioned here that the developing countries achieved higher growth rate when OECD countries completely
liberalized its agricultural sector as depicted in simulation 1. It is observed form the table that all the developing
country groups experience an increase in exports while agricultural imports are both increased and decreased across
country groups and simulations. These changes in export and import along with the changes in world price of
agricultural commodities effects the balance of trade situation in developing countries. Balance of trade situation
improves in ESEA and SA while it becomes worsen in LAC, MENA and SSA countries in almost all the
simulations. Now let us consider the changes of wage in developing countries as a result of liberalized measures
taken by OECD countries. From Table 5 it is observed that both skilled and un-skilled workers experience an
increase in wage rate. However, the wage increase in un-skilled worker is higher than the wage increase in skilled
worker. In most of the developing countries poor household are mainly depends on the income from un-skilled
worker. Therefore, the simulation results of present analysis depict that the income distribution resulting from
agricultural trade liberalization is in favor of poor household in developing countries.
5. Conclusion
The paper analyzes the impact of agricultural trade liberalization on welfare, growth and income distribution in
developing countries. To perform the agricultural trade liberalization all three types of agricultural supports i.e.,
import tariff, domestic support and export subsidies have been considered. For the purpose of present analysis
developing countries are categorized into five groups. The analytical tool has been used in this paper is a global
CGE model. The simulation results depict that the welfare effects are not similar across these country groups. A
complete liberalization of agriculture by OECD countries is welfare enhancing for net agricultural commodity
exporters while net food importing countries experience a welfare loss. These results are only possible when OECD
countries remove all types of subsidies and tariff. The removal of a specific type of agricultural subsidy and tariff by
OECD countries might have different effect on developing countries depending on the nature of each effect and
which one is outweighs other. Furthermore, countries where firm use imported agricultural inputs from developed
countries, may not necessarily increase welfare as it was expected. Because, in such a case rising prices in
agriculture do boost farm gate price and also export prices in developing countries. Therefore, the effects are not as
clear as assumed. It is also observed that agricultural liberalization by OECD countries is growth enhancing for
developing countries as a result of increased agricultural output. However, developing countries achieved higher
growth rate when OECD countries completely liberalized its agricultural sector. There is also a pro-poor
distributional effect of income as a result of complete liberalization in agriculture by OECD countries.
The modeling framework has been used here is a neo-classical full employment model. But developing countries are
in general labor surplus with high unemployment in un-skilled labor. The neoclassical closure used in this model is
full employment and flexible wage rate. The simulation results show that wage rates will increase as a result of
increased demand for labor in developing countries. From this feature, it is argued that in developing countries
employment might be generated by agricultural trade liberalization in OECD countries. These employment
generations might be higher for un-skilled labor as the simulation results reflect a higher increase in wage rate in
un-skilled labor.
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ISSN 1916-971X E-ISSN 1916-9728 174


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WTO Website: http://www.wto.org/
Notes
Note 1. Cotton is the single-most important export from Chad, Mali, Benin and Burkina Faso where its share in total
non-fuel commodity exports varies from just about 80 to 95 percent. Guinea Bissau similarly depends on cashew nut
exports where its share in non-fuel commodity export is 98 percent.
Note 2. Supports that are considered as trade distorting are included in the Amber Box. Subsidies that are provided
to farmers to limit production are included in the Blue Box and subsidies that are considered not to distort trade are
included in the Green Box.
Note 3. The Swiss Formula and Harbinson approach are two mathematical formula designed to cut and harmonize
tariff rates in international trade. Several countries are pushing for their use in WTO trade negotiations.
Note 4. See Hertel & Tsigas (1997) and Brockkmeier (2001) for detail.



Table 1. Reduction in agricultural support and protection agreed in AoA.


Developed Countries
6 Years (1995-2000)


Developing Countries
10 Years (1995-2004)


Tariff
i) Average cut for all agricultural
products
ii) Minimum cut per product



36%
15%



24%
10%


Domestic Support
i) Cut of total support (AMS) for sector
ii) De minimis level



20%
5%



13%
10%


Exports
i) Value of Subsidies
ii) Subsidized quantities



36%
21%



24%
14%


Source: WTO Website.





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Published by Canadian Center of Science and Education 175


Table 2. Regional and Commodity Aggregation in GTAP Model
Regional Aggregation


New Region Comprising old regions
OECD Countries Australia; New Zealand; Japan; Korea; Canada; United States of America; Mexico; Chile; Austria; Belgium;


Czech Republic; Denmark; Estonia; Finland; Germany; Greece; Hungary; Ireland; Italy; Luxembourg;
Netherlands; Poland; Portugal; Slovakia; Slovenia; Spain; Sweden; United Kingdom; Switzerland; Norway;
Turkey.


East and South East
Asia (ESEA)


China; Rest of East Asia; Cambodia; Indonesia; Lao People’s Democratic Republic; Myanmar; Malaysia;
Philippines; Thailand; Viet Nam; Rest of Southeast Asia.


South Asia (SA) Bangladesh; India; Pakistan; Sri Lanka; Rest of South Asia.
Latin America and
Caribbean (LAC)


Argentina; Bolivia; Brazil; Colombia; Ecuador; Paraguay; Peru; Uruguay; Venezuela; Rest of South America;
Costa Rica; Guatemala; Nicaragua; Panama; Rest of Central America; Caribbean.


Middle-East and North
Africa (MENA)


Rest of Western Asia; Egypt; Morocco; Tunisia; Rest of North Africa.


Sub-Saharan Africa
(SSA)


Nigeria; Senegal; Rest of Western Africa; Central Africa; South Central Africa; Ethiopia; Madagascar; Malawi;
Mauritius; Mozambique; Tanzania; Uganda; Zambia; Zimbabwe; Rest of Eastern Africa; Botswana; South
Africa; Rest of South African Customs .


Rest of the World Rest of Oceania; Hong Kong; Taiwan; Singapore; Rest of North America; Cyprus; France; Latvia; Lithuania;
Malta; Rest of EFTA; Albania; Bulgaria; Belarus; Croatia; Romania; Russian Federation; Ukraine; Rest of
Eastern Europe; Rest of Europe; Kazakhstan; Kyrgyztan; Rest of Former Soviet Union; Armenia; Azerbaijan;
Georgia; Iran Islamic Republic of.


Commodity Aggregation
New Sector Comprising old Commodities
Agriculture Paddy rice; Wheat; Cereal grains nec; Vegetables, fruit, nuts; Oil seeds; Sugar cane, sugar beet; Plant-based


fibers; Crops nec; Cattle, sheep, goats, horses; Animal products nec; Raw milk; Wool, silk-worm cocoons;
Meat: cattle, sheep, goats, horse; Meat products nec; Vegetable oils and fats; Dairy products; Processed rice;
Sugar; Food products nec; Beverages and tobacco products.


Manufacturing Forestry; Fishing; Coal; Oil; Gas; Minerals nec; Textiles; Wearing apparel; Leather products; Wood products;
Paper products, publishing; Petroleum, coal products; Chemical, rubber, plastic prods; Mineral products nec;
Ferrous metals; Metals nec; Metal products; Motor vehicles and parts; Transport equipment nec; Electronic
equipment; Machinery and equipment nec; Manufactures nec.


Services Electricity; Gas manufacture, distribution; Water; Construction; Trade; Transport nec; Sea transport; Air
transport; Communication; Financial services nec; Insurance; Business services nec; Recreation and other
services; PubAdmin/Defence/Health/Educat; Dwellings.


Source: GTAP Database



Table 3. GTAP Simulation Scenarios


Simulation 1: Simulation 2 Simulation 3 Simulation 4
Import tariff removed 100% 50% 100% 0%
Export subsidies removed 100% 50% 0% 0%
Output subsidies removed 100% 50% 0% 0%
Input subsidies removed 100% 50% 100% 100%
Land subsidies removed 100% 50% 0% 0%
Capital subsidies removed 100% 50% 0% 0%



Table 4. Decomposition of Welfare Changes (US$ million)


Simulation 1 Simulation 2:
Region Allocative Efficiency TOT Effect I-S Effect Total Allocative Efficiency TOT Effect I-S Effect Total
ESEA -529 3362 -430 2404 -234 1312 -167 912
SA -170 74 31 -64 -75 39 13 -23
LAC 201 2744 -14 2931 77 1173 -8 1242
MENA -416 -560 36 -941 -206 -285 15 -475
SSA -86 307 1 222 -44 135 0 91




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ISSN 1916-971X E-ISSN 1916-9728 176


Table 4 (Continued)
Simulation 3 Simulation 4


Region Allocative


Efficiency


TOT


Effect


I-S Effect Total Allocative


Efficiency


TOT


Effect


I-S Effect Total


ESEA -349 3480 -530 2601 -24 -26 12 -37


SA -133 47 27 -59 -5 1 0 -5


LAC 234 2521 -17 2738 -1 28 0 27


MENA 23 147 30 200 -13 -26 1 -38


SSA 65 456 1 522 -3 4 0 1


Source: GTAP Simulation Results



Table 5. Macroeconomic Impact of Agricultural Trade Liberalization


Changes in ESEA SA LAC MENA SSA


Si
m


ul
at


io
n


1


Real GDP (%) 0.98 0.49 2.11 0.29 0.97
Balance of Trade (US$ million) 4377.74 20.84 -1307.83 -248.91 -158.36
Price of Agricultural Import (%) 1.46 1.39 2.35 3.28 3.21
Agricultural Export (%) 45.2 11.67 26.98 9.37 17.16
Agricultural Import (%) 3.42 -1.17 3.34 -4.44 -3.28
Agricultural Output (%) 4.30 0.58 5.97 1.69 3.52
Un-Skilled wage rate (%) 1.14 0.5 2.13 0.46 1.37
Skilled wage rate (%) 0.18 0.3 1.86 0.22 0.69


Si
m


ul
at


io
n


2


Real GDP (%) 0.43 0.26 0.94 0.16 0.48


Balance of Trade (US$ million) 1849.07 10.68 -564.12 -112.77 -71.49


Price of Agricultural Import (%) 0.71 0.66 1.11 1.63 1.59


Agricultural Export (%) 18.93 5.64 12.07 4.65 8.16


Agricultural Import (%) 1.26 -0.52 1.37 -2.21 -1.68


Agricultural Output (%) 1.81 0.28 2.68 0.84 1.69


Un-Skilled wage rate (%) 0.5 0.26 0.95 0.25 0.67


Skilled wage rate (%) 0.1 0.17 0.83 0.13 0.35


Si
m


ul
at


io
n


3


Real GDP (%) 0.74 0.19 1.71 0.03 0.62
Balance of Trade (US$ million) 3870.85 53.93 -1026.52 -112.22 -100.97
Price of Agricultural Import (%) 0.21 0.59 0.94 0.03 0.17
Agricultural Export (%) 42.11 7.73 24.4 5.45 14.68
Agricultural Import (%) 5.34 -0.16 5.06 0.1 1.87
Agricultural Output (%) 3.85 0.37 5.25 0.35 2.41
Un-Skilled wage rate (%) 0.89 0.2 1.73 0.07 0.87
Skilled wage rate (%) 0.03 0.07 1.5 0.03 0.43


Si
m


ul
at


io
n


4


Real GDP (%) 0.01 0.01 0.03 0 0.02


Balance of Trade (US$ million) 16.02 -5.55 -34.21 -15.4 -6.97


Price of Agricultural Import (%) 0.09 0.06 0.08 0.09 0.08


Agricultural Export (%) 0.44 0.39 0.37 0.43 0.45


Agricultural Import (%) -0.14 -0.1 -0.04 -0.13 -0.1


Agricultural Output (%) 0.05 0.02 0.09 0.06 0.09


Un-Skilled wage rate (%) 0.01 0.01 0.03 0.01 0.03


Skilled wage rate (%) 0 0.01 0.02 0 0.01


Source: GTAP Simulation Results





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