metadata: authors: 0: author: Le Goff, Maelan
1: author: Singh, Raju Jan
count: Africa
docna: 0: docna: Does trade reduce poverty ? a view from Africa
docty: Policy Research Working Paper
subtopic: Educational Sciences,International Trade and Trade Rules,Poverty and Trade,Inflation,Inequality
teratopic: Private Sector Development,Macroeconomics and Economic Growth,International Economics and Trade,Poverty Reduction
abstracts: cdata!: Although trade liberalization is being
            actively promoted as a key component in development
            strategies, theoretically, the impact of trade openness on
            poverty reduction is ambiguous. A more liberalized trade
            regime is argued to change relative factor prices in favor
            of the more abundant factor. If poverty and relative low
            income stem from abundance of labor, greater trade openness
            should lead to higher labor prices and a decrease in
            poverty. However, should the re-allocation of factors be
            hampered, the expected benefits from freer trade may not
            materialize. The theoretical ambiguity on the effects of
            openness is reflected in the available empirical evidence.
            This paper examines how the effect of trade openness on
            poverty may depend on complementary reforms that help a
            country take advantage of international competition. Using a
            non-linear regression specification that interacts a proxy
            of trade openness with proxies of various country structural
            specificities and a panel of 30 African countries over the
            period 1981-2010, the analysis finds that trade openness
            tends to reduce poverty in countries where financial sectors
            are deep, education levels high and governance strong.
repnme: repnme: Does trade reduce poverty ? a view from Africa
display_title: Does trade reduce poverty a view
            from Africa
listing_relative_url: /research/2013/01/17194965/trade-reduce-poverty-view-africa
topicv3: Trade and Poverty m1326021 1196,Poverty m1326687 695,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Trade m1326924 698,Education m1327048 470
publishtoextweb_dt: 2013-01-01T00:00:00Z
historic_topic: Private Sector Development,Macroeconomics and Economic Growth,International Economics and Trade,Poverty Reduction
no_of_pages: 27
model_extractions: WPS6327 Policy Research Working Paper 6327 Does Trade Reduce Poverty?

_Maëlan Le Goff Raju Jan Singh_ The World Bank Africa Region Poverty Reduction and Economic Management Unit January 2013
Policy Research Working Paper 6327

# **Abstract**

Although trade liberalization is being actively promoted as a key component in development strategies, theoretically, the impact of trade openness on poverty reduction is ambiguous. A more liberalized trade regime is argued to change relative factor prices in favor of the more abundant factor. If poverty and relative low income stem from abundance of labor, greater trade openness should lead to higher labor prices and a decrease in poverty. However, should the re-allocation of factors be hampered, the expected benefits from freer trade may not materialize. The theoretical ambiguity on the effects of openness is reflected in the available empirical evidence. This paper examines how the effect of trade openness on poverty may depend on complementary reforms that help a country take advantage of international competition. Using a non-linear regression specification that interacts a proxy of trade openness with proxies of various country structural specificities and a panel of 30 African countries over the period 1981–2010, the analysis finds that trade openness tends to reduce poverty in countries where financial sectors are deep, education levels high and governance strong.

This paper is a product of the Poverty Reduction and Economic Management Unit, Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at rsingh9@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **DOES TRADE REDUCE POVERTY? A VIEW FROM AFRICA**<sup>1</sup>

## **Maëlan Le Goff**

## **Raju Jan Singh**

**JEL Classification Numbers** :  F02, F15, O11, O55 **Keywords:** Trade, poverty, governance, Africa **Sector Board:** EPOL

Author’s E-mail Address: <u>rsingh9@worldbank.org; maelan.legoff@cepii.fr</u>

> 1 We would like to thank Richard Baldwin, Daniel Lederman and Sherry Stephensen for their helpful comments. We would also like to thank participants at the Center for the Study of African Economies Conference, March 18-20, 2012, Oxford and at the Poverty Reduction, Equity, and Growth Network’s Conference, September 6-7, 2012, Dakar for suggestions on earlier versions. The usual disclaimer applies. Maëlan Le Goff is affiliated to the CEPII ( _Centre d’Etudes Prospectives et d’informations Internationales_ ), Raju Jan Singh is with the World Bank.
2

# **I. INTRODUCTION**

Most economists accept that, in the long run, open economies fair better in aggregate than do closed ones, and that relatively open policies contribute significantly to development. Many commentators fear, however, that in the shorter run, one of the steps towards openness – trade liberalization – harms the poorer actors in the economy, and that even in the longer run successful open regimes may leave some people behind in poverty. Africa remains the poorest continent of the world. Yet, at the same time, African countries have experienced significant improvements in trade liberalization. It seems that the large gains expected from opening up to international economic forces have, to date, been limited in Africa, especially for poor people.

While the traditional trade theory predicts welfare gains from openness at the country level through specialization, investment in innovation, productivity improvement, or a better resource allocation, the theoretical impact of trade on the poor remains uncertain. Besides, empirical results do not converge on this point and it seems that developing countries are not equally able to make use of the opportunities arising out of increased access to markets in the developed world.

The contribution of this paper lies in providing new cross-country empirical evidence focused on Africa on how the poverty reduction effect of greater trade openness depends on a variety of structural characteristics, including some that are subject to reform. Using a panel of African countries over the period 1981-2010 and testing for non-linearities in the trade-poverty relationship, this paper explores the empirical link between trade openness and poverty. Its results uncover an interesting pattern of reform complementarity: trade openness tends to reduce poverty in countries as their financial sector grows deeper, their education level higher and their governance stronger.

Our concern is with poverty, not inequality. Since trade liberalization tends to increase the opportunities for economic activity, it can very easily widen income inequality while at the same time reduce poverty. Consequently, statements about its effects on inequality cannot be translated directly into statements about its impact on absolute poverty. There may be sound positive and normative reasons for interest in inequality, but they are not the concerns of this paper.

The rest of the paper is organized as follows. Section II reviews the impact of trade on poverty by focusing on the transmission channels and the conditional variables that can influence the trade-poverty relationship. Section III sets up the empirical analysis of the non-linear trade-poverty relationship. Conclusions are presented in Section IV.
3

# **II. TRADE OPENNESS AND POVERTY: DISCUSSION OF THE LITERATURE**

Bhagwati and Srinivasan (2002) distinguish two broad strands of argumentation when discussing the effects of freer trade on poverty: static and dynamic. In the former case, we examine how freer trade effects poverty taking resources and technology as given. In the latter case, we consider growth effects and the evolution of poverty over time.<sup>2</sup> Following the static approach, the Stolper-Samuelson theorem, in its simplest form, suggests that the abundant factor should see an increase in its real income when a country opens up to trade. If the abundant factor in developing countries is unskilled labor, then this framework suggests that the poor (unskilled) in developing countries have the most to gain from trade. Krueger (1983) has used this insight to argue that trade reforms in developing countries should be pro-poor, since these countries are most likely to have a comparative advantage in producing goods requiring unskilled labor.

However, for comparative advantage to increase the incomes of the unskilled, they need to be able to move out of contracting sectors and into expanding ones. Davis and Mishra (2006), Goh and Javorcik (2006) and Topalova (2006) suggest that labor in the real world may not be as mobile: there are too many barriers to entry and exit for firms, and too many barriers to labor mobility for workers.

Focusing on urban Colombia, Attanasio, Goldberg and Pavenik (2004) find for example that the probability of being unemployed is more important in traded-good sectors than in nontraded-good sectors. Trade openness may also increase the size of the informal sector (Goldberg and Pavenik, 2003). Being more exposed to foreign competition, firms may be incited to reduce their costs by hiring temporary workers instead of permanent ones, or even to lay off workers, who may in turn obtain informal jobs. Depending on the wage differences between sectors, this could lead to an increase in poverty.

In addition, if the poor are mostly completely unskilled, while it is semi-skilled labor that is on increased demand, poverty will be unaffected – or possibly, worsened. Trade liberalization may even be accompanied by skill-biased technical change, which can mean that skilled labor may benefit relative to unskilled labor. Lower prices for capital goods or increased competition following trade liberalization could encourage firms to import

> 2 See Winters and McKay (2004) for a detailed discussion on the possible various channels for freer trade to affect poverty.
4 machines and increase their demand for skilled labor (Acemoglu, 2003; Behrman, Birdsall, and Szekely, 2000; Harrison and Hanson, 1999). Furthermore, many developing countries are rich in natural resources. Trade would stimulate this sector rather than labor-intensive ones.

From a dynamic perspective, economic growth is key to sustained poverty alleviation and trade liberalization is argued to lead to the needed increases in productivity to sustain growth. Freer trade provides greater incentives for investment, the benefits of scale and competition, limitation on rent-seeking activities favored by trade restrictions and openness to new ideas and innovations (Berg and Krueger, 2003; Grossman and Helpman, 1991; Lucas, 1988).

Empirically, cross-county growth regressions have produced mixed evidence. Using either trade shares or indices of trade liberalization, Sachs and Warner (1995), Edwards (1997), Frankel and Romer (1999) Dollar and Kraay (2001) and Lee et al. (2004) find a positive association between liberalization and growth. However, noting that trade liberalization often occurs at the same time than other policy reforms, Rodriguez and Rodrik (2001) have criticized the literature which associates trade openness measured by trade shares with more rapid growth. Considering trade policy measures instead, Harrison (1996), Edwards (1997), and Irwin and Terviö (2002) find a significant negative effect of trade on economic growth, while Vamvakidis (2002) still shows that trade enhances growth.

Examining the effect of trade on poverty more directly, Krueger (1983) shows in her case studies that developing countries’ manufactured exports were, indeed, labor-intensive, but that the employment effects of freer trade policies were generally rather limited. A number of cross-country studies on poverty, while not dealing with trade explicitly, incorporate trade openness as a control variable and showed similar results: at best the benefits of greater trade openness seem to have bypassed the poor.

Looking at developing countries only, Beck et al. (2007) and Kpodar and Singh (2011) find no effect on the poor. Similarly, Dollar and Kraay (2001) find a lack of any evidence of an impact of openness on the income of the poorest quintile in a sample of advanced and developing economies. By contrast, looking at a sample of developing countries, Guillaumont-Jeanneney and Kpodar (2011) find a negative relationship between trade openness and the income of the poorest quintile. Similarly, Singh and Huang (2011) focusing on a sample of sub-Saharan African countries suggest that greater trade openness increases headcount poverty, widens the poverty gap, and reduces the income of the poorest quintile.
5 This lack of any clear correlation between openness measures and poverty indicators in aggregate could be because there is too much heterogeneity in the effects of trade reforms on the poor. Since poor workers in import-competing sectors lose from reforms, while poor workers in export-oriented sectors gain, it could be that in the aggregate these different effects cancel each other. Similarly, cross-country studies have tended to favor larger samples and focus on developing countries at best. While using a broader sample increases the degrees of freedom, it may also introduce unwanted heterogeneity if factors explaining poverty differ between country groups.

Another possibility suggested by Winters and McKay (2004) is that trade liberalization almost certainly requires combination with other appropriate policies. The sort of policies envisaged would be those that encourage investment, allow effective conflict resolution, and promote human-capital accumulation. Linear regression models would not capture such complementary dynamics. A number of recent studies emphasize the importance of complementary policies in determining the benefits or costs of trade reforms for developing countries. For example, Bolaky and Freund (2008) show that trade reforms actually lead to income losses in highly regulated economies. Excessive regulations restrict growth because resources are prevented from moving into the most productive sectors and to the most efficient firms within sectors. Similarly, Sindzingre (2005) suggests that institutions could help explain the heterogeneity in the globalization-poverty relationship. She argues that domestic political structures and institutions (such as oligarchic or predatory regimes) may prevent the poor from benefiting from globalization.

More recently, Haltiwanger (2011) and McMillan and Verduzco (2011) argue that benefits of trade depend to a large extent on national institutional settings. The process of tradeinduced growth entails a continual reallocation of resources away from less productive activities to more productive ones. Many things can go wrong in this reallocative process if economies are distorted, for instance if transportation or communication infrastructure are not sufficiently developed, if ineffective (or non-existent) competition policy does not prevent large firms from abusing their market power, or if financial markets are not sufficiently developed to fund new and expanding businesses. In such distorted economic environments, there is little chance that the benefits of greater trade openness materialize and – in extreme cases – a “de-coupling” may take place, i.e. cases in which policy reforms induce downsizing and exit of some firms but do not lead to the expansion of other firms.

Similarly, reviewing the new wave of research under the International Collaborative Initiative on Trade and Employment, Newfarmer and Sztajerowska (2012) conclude that the benefits of trade do not accrue automatically, and policies that complement trade opening are needed. Policies that embed trade reforms in a context of macroeconomic stability and a sound investment climate on the one hand and, on the other, protection for
6 workers, maintenance of high-quality working conditions, and facilitation of labor transitions, can play an important role in realizing the potential wage, employment, and income gains associated with trade.

Finally, Agénor (2004) examines whether the effect of globalization on poverty depends on the degree of liberalization. Introducing a square term of globalization index in his base model, he finds that under a certain level globalization is detrimental for the poor and that beyond this threshold, globalization appears to reduce poverty (illustrating an inverted U- shaped relationship between globalization and poverty). One explanation suggested by Agénor (2004) is that at the first stage, globalization generates a decrease in the output of import-competing sectors, while at the next stage, output increases thanks to the development of the exportable sector induced by greater globalization. Using endogenous threshold regression techniques to investigate the trade-poverty relationship in China, Liang (2006) reaches similar results: globalization promotes poverty-reduction in Chinese provinces only after the economy has reached a certain level of globalization.
7

# **III. EMPIRICAL ANALYSIS**

## **A- Sample**

Our empirical objective is to examine how the poverty reduction effect of openness may depend on a variety of country characteristics, including some that are subject to reform. For this purpose, we work with pooled cross-country and time-series data for 30 African countries averaged over five-year periods from 1981 to 2010. Summary statistics and the correlation matrix for the variables used in our estimation exercises are provided in Appendix 1. Following the same approach as Chang (2009), we start with a linear regression specification and then extend it to account for interaction terms between an openness measure and proxies for various county characteristics (financial depth, education and governance).

These three dimensions (finance, education, and governance) should characterize an economy’s ability to reallocate resources away from the less productive sectors to the more productive ones and, hence, take advantage of the opportunities offered by greater trade openness. A more developed financial sector, as measured by the private sector credit-toGDP ratio, would allow a faster identification of new and promising sectors and a redirection of credit. A more educated population, as measured by primary completion rates, would be more able to acquire the new skills sought by growing sectors and adjust more rapidly to the new conditions of the labor market. Finally, better governance, as measured by the rule of law, would allow contracts to be made and conflicts to be resolved more easily.

## **B- Model and Definition of Variables**

## _Model_

<mark>We use the basic growth–poverty model suggested by Ravallion (1997) and Ravallion and Chen (1997) as well as the frameworks posited by Dollar and Kraay (2001) and Berg and Krueger (2003). Our point of departure can be written as:</mark> <mark>Poverty</mark> i,t <mark>= β</mark> 1 <mark>TO</mark> i,t <mark>+ β</mark> 2 <mark>X</mark> i,t <mark>+ φ</mark> t <mark>+ μ</mark> i <mark>+ ε</mark> i,t <mark>(1)</mark> where the subscripts i and t represent country and time period, respectively, Poverty is the log of a poverty indicator, _X_ is the matrix of control variables, TO is a measure of trade openness, φt corresponds to time effects, μi denotes unobserved country-specific effects, ε the error term. and i,t
8 Following Chang (2009), we then extend the regression specification by allowing the poverty reduction effect of openness to vary with some country characteristics represented in the control set (financial depth, education, and governance). We do this by interacting the openness measure with each of these conditional variables in turn. The regression equation with the interaction terms is the following:

# Povertyi,t = β1TOi,t + β2Xi,t + β3TOi,t × xi,t + φt + μi + εi,t     (2)

where xi,t represents one of the control variables.

# _Variables_

**Poverty** . Poverty is a complex and multidimensional phenomenon, and there is considerable controversy in the literature about how it should be defined and measured. The majority of the empirical economic literature on poverty tends to adopt on absolute income or consumption metric. Therefore, while recognizing that there are many legitimate approaches to the measurement of poverty, we will follow this approach. In this regard, the most popular indicator is the poverty headcount index which measures the percentage of the population living with consumption or income per person below a certain poverty line. It is a measure of absolute poverty. Another popular measure is the poverty gap, which measures the mean distance below the poverty line as a proportion of the poverty line. As dependent variable, we use the poverty headcount and the poverty gap considering the $1.25 poverty line.

**Trade openness** . Two main categories of trade openness measures can be found in the economic literature. Spilimbergo et al. (1999) distinguish for instance between incidencebased measures of openness, based on tariff data and trade policy, and outcome-based measures of openness, based on trade data. Calderón et al (2005) make a similar distinction between policy or legal measures and outcome or de facto measures of openness. In this paper we focus on the impact of actual globalization on poverty and we have chosen as our dependent variable ( _Trade openness_ ) an ex-post measurable and objective definition of globalization, namely effective trade openness (measured as the sum of exports and imports as a share of GDP), and not a measure of liberalization policies. Such an indicator is arguably better than legalistic (de jure) measures to the extent that the latter are difficult to summarize in a single indicator (there are multiple tariff rates, multiple non-tariff barriers, multiple trade agreements) and even more difficult to adjust for the strength with which they are enforced.
9

**Control variables** . We also include a set of control variables that are commonly used in poverty equations: overall income per capita ( _GDP per capita_ ) to control for economic development, a measure of human capital level ( _Education_ ); a variable of financial deepening ( _Private credit/GDP_ ); growth of the consumer price index ( _Inflation_ ) to control for the macroeconomic environment; and an indicator of institutional quality ( _Law and order_ ) drawn from the International Country Risk Guide (ICRG) database which measures the strength and impartiality of the legal system, and the popular observance of the law.

Data sources are provided in Appendix 3.

# **C- Methodology**

The poverty regression presented above poses several challenges for estimation. The first is the presence of unobserved period- and country-specific effects. The second challenge is that most explanatory variables could be jointly endogenous with poverty, so we need to control for the biases resulting from simultaneous or reverse causation. For this purpose, we estimate the coefficients of our model by using the System Generalized Method-ofMoment (GMM) estimator developed by Blundell and Bond (1998). The estimator combines two sets of equations. The first set includes first-differenced equations where the right-hand-side variables are instrumented by the levels of the series lagged one period or more. The second set consists of the equations in levels with the right-hand side variables being instrumented by lagged first or higher-order differences.

The consistency of the GMM estimators depends on whether lagged values of the explanatory variables are valid instruments in the poverty regression. We examine this issue by considering the Hansen test of over-identifying restrictions. The no rejection of the null hypothesis implies that instrumental variables are not correlated with the residual and are satisfying the orthogonality conditions required. A serial correlation test is also carried out and demonstrates that the errors exhibit no second-order serial correlation.

# **D- Results**

A look at the plots in Appendix 4 which compare the trade-poverty relationship in the top country group and the bottom country group in terms of financial development, education and governance,<sup>3</sup> suggests that the effect of trade openness on poverty would depend on a variety of country characteristics. Indeed, for each conditional variable considered, the

> 3 Countries are classified in the top (bottom) group if they belong to the top one-fourth (bottom threefourths) of a rank distribution given by each conditional variable (financial development, education level and quality of institutions).
10 slope for the relationship between trade openness and poverty appears negative and steeper in the top group than in the bottom group.

To control for other poverty determinants and endogeneity issues, we now test our model through an econometric analysis. Results of the basic regression with no interaction term (equation 1) are presented in Tables 1 (for the poverty headcount) and 2 (for the poverty gap), columns 1. The log transformation of all the variables allows us to interpret the coefficients as elasticities. A positive sign in the corresponding coefficient indicates an increase in the poverty headcount (or poverty gap), corresponding to a worsening in the situation of the poor.

Overall, the results are consistent with the previous empirical literature. There is a strong negative relationship between income per capita and poverty incidence, suggesting that higher levels of economic development are associated with lower levels of poverty. The proxy for the education level has a negative and significant coefficient, denoting its beneficial impact on poverty reduction. Inflation, financial development, and governance variables do not seem to be robustly linked to poverty. Looking at trade openness, the results are in line with Beck et al. (2007) and Kpodar and Singh (2011): they would suggest that greater trade openness is not significantly associated with either lower or higher levels of poverty.

Since in the basic specification only linear effects are allowed, the coefficient associated with trade openness is an average. To uncover what is behind this average, we examine next the influence of some structural country characteristics in the trade-poverty relationship. The results with the interaction terms are presented in Columns 2, 3 and 4 of Tables 1 and 2. An interesting pattern of reform complementarity emerges: the coefficient on the trade openness proxy suggests that greater trade is associated with higher levels of poverty, but the coefficients on the interaction terms indicate that this adverse relation could be reversed if financial development grows deeper, education levels higher, and governance improves.

We first test whether the trade-poverty relationship would change with the development of the financial sector (columns 2). The coefficient on the interaction term with the financial depth (as measured by the private sector credit-to-GDP ratio) is negative and significant. These results suggest that a greater openness of African economies to trade is associated with lower levels of poverty when the financial system is more developed. In other words, easier access to cheaper credit may allow the poor to benefit more from trade openness. A threshold of 17.7 percent of GDP is estimated for the development of domestic private credit beyond which the poor can benefit from trade openness, which is far below the average of our sample (21.2 percent of GDP). To illustrate, the Central African Republic,
11 Ghana, Malawi and Uganda are under this threshold while South Africa, Algeria and Tunisia are well above it.<sup>4</sup> Column 3 of Tables 1 and 2 shows the results of the estimations testing the role of human capital in the trade-poverty relationship. The beneficial impact of an increase in trade openness on poverty reduction is larger when the investment in human capital is stronger. We find that when the share of the population over age 15 with completed primary education exceeds 46.7 percent (the average in the sample is 55 percent), trade openness starts being favorable to the poor. In other words, with appropriate learning skills, people are better able to take advantage of the new opportunities offered by trade.

Finally, we examine whether the relationship between the openness to trade and poverty may hinge on a country’s institutional environment (columns 4). Results suggest that the negative association between trade openness and poverty could diminish with improvements with respect to law and order, and even reverse. We find that trade openness could be favorable to the poor when institution quality (measured by the _Law and order_ variable) reaches 3.3 (the average of our sample is 2.9).<sup>5</sup> In other words, an environment where laws and contracts are enforced seems to be more favorable for the emergence of new enterprises and the closing of older ones, allowing the economy the needed flexibility to adjust.

# _Robustness tests_

We conducted several robustness tests:

- First, we used an alternative measure of absolute poverty, the poverty gap. The results using the poverty gap confirmed the observations for the poverty headcount ratio (see Table 2);

- We also removed outliers. The results reported in Table A.1 and Table A.2 confirm and reinforce our previous observations.

> 4 See Appendix 6.

> 5 We also used another ICRG indicator measuring Institutional strength and quality of the bureaucracy (ranging from 0 to 4, with a higher figure indicating a bureaucracy which has the strength and expertise to govern without drastic changes in policy or interruptions in government services), as a proxy of the institutional environment. We found similar results.
12

# **IV. CONCLUDING REMARKS**

While trade liberalization is being actively promoted as a key component of development strategies, both theoretically and empirically, its impact on poverty is ambiguous. At best, the benefits of freer trade seem to bypass the poor. By focusing on African countries and taking into account possible non-linearities, this paper attempted to reach more robust results.

While on average trade does not seem to be associated with lower poverty, this observation hides important non-linearities and an interesting pattern of policy complementarities. More openness results in a reduction in poverty when the financial sector is deeper, education levels are higher, and governance is stronger.

These results are consistent with the recent literature arguing that the benefits of trade are not automatic and that policies to accompany trade opening are needed. These policies would aim at encouraging the financing of new investment, the effective resolution of conflicts, and the ability to adjust and learn new skills. This accompanying policy agenda would allow resources to be reallocated away from less productive activities to more promising ones.

Trade liberalization should therefore not be seen in isolation and additional policies will be needed to enhance its impact, including on poverty. This also means that poor policies and institutions, weak human capital and limited financial development, have not only a direct negative effect on countries’ welfare, they also prevent the poor in developing countries from benefiting from the gains of trade liberalization.