Introduction

The debate about the impact of globalization on the well-being of people has already generated a large literature.¹ Here I focus on one particular aspect of globalization, namely, trade liberalization. I also focus on the well-being of one particular group, namely, the poor.² Understanding the impacts of trade liberalization on income (and wealth) distribution and poverty is important because of the vulnerability of the poor as a group in developing economies. The literature on trade liberalization emphasizes the elimination of distortions leading to both gains from trade and an increase in domestic economic activities leading to sustained growth. To the extent that the poor are also beneficiaries of these outcomes, poverty is expected to decline.

However establishing the link between this type of trade liberalization or trade reform in general associated, for example, with WTO entry and poverty reduction requires more than just a description or projection of trade patterns. A counterfactual "no-change" scenario must be compared with an estimated scenario after liberalization. An appealing way of addressing this is to formulate and use an appropriate computable general equilibrium (CGE) model that compares the non-liberalized case with scenarios based on trade liberalization. For example, Roland-Holst (2002) and (2003) applies a version of the well-known GTAP model to assess the impact of reform on trade and income for some regions of Asia and PRC. His model is aggregated and covers 16 countries and 18 sectors with CES production functions.³ Recent work on trade and development has also emphasized the importance of considering the response of the informal sector to trade liberalization and the importance of modeling specific institutional aspects of particular labor markets.⁴ The complexity of the links between trade and poverty have been analyzed by Alan Winters and his coauthors in particular (Winters 2000, 2002 and the references therein).

This paper has two related goals. The first and the main aim is to present a "generic", stylized CGE model for South Asia within which certain policy experiments about trade liberalization can be carried out. The second, related objective is to use 'real world' country data from South Asia to carry out some experiments with respect to the progressive removal of tariff barriers. I use largely data from India with some exceptions. However the results should be indicative of what can be expected for other South Asian economies with large populations and large numbers of poor people in both the urban and rural areas.

The emphasis on poverty reduction at the national and international levels as embodied for example, in the Millennium Development Goals, calls for a careful methodological approach to the estimation of the poverty reduction impacts of changes in macroeconomic, trade and other policy variables. A recent report produced at the Asian Development Bank sorts out many of the complex issues involved at the macro-, meso- and micro-economic levels and pinpoints the need for further conceptual and modelling work at the appropriate levels of (dis)aggregation(Bolt et.al.2003).The identification of the three different levels and treating the meso-economic level as the (institutional) link between the other two levels are encouraging in terms of understanding the complex causal relations that are involved in understanding and reducing poverty.

There are at least two aspects of any poverty impact analysis for a particular policy. These are: i) the impact on economic growth; ii) the impact on income and asset distribution. The growth effect on poverty reduction is then given by some estimated growth-poverty elasticity. In the second case, a more (less) favorable income/asset distribution for the poor may reduce (increase) poverty. A distributional neutrality assumption in a model simply allows one to look at the growth aspect by itself. Here, too, different sectoral growth rates and different sectors themselves may affect poverty differently. (Quibria 2002; Khan 1999; Thorbecke and Jung 1996). Thus the dynamic and disaggregated growth impacts of trade liberalization may ultimately be the key intervening variables. From this overall perspective, the present endeavor may be seen as a first step to capture the poverty impact of trade liberalization through a comparative statics experiment in a generic CGE model.

The structure of the paper is as follows. In the following section I discuss the general macroeconomic policy issues arising out of program lending and their relevance to the poverty reduction strategy in the "post-Washington consensus" policy environment and trade liberalization. This raises some pertinent questions regarding the measurement of poverty and the nature of macroeconomic environment in the developing economies. Consequently, in the two sections following immediately, I discuss these issues in the context of developing economies. In section 3, I deal with some fundamental issues for the measurement of poverty. This is followed up in section 4 by a discussion of some issues regarding the general structure of macro-models as they may relate to the salient characteristics related to the dualistic nature of some South Asian economies. Section 5 then takes up the specific issue of recent history of reforms in South Asia via a discussion of the Indian case from 1991 to 2004. Section 6 explores specifically the questions related to income distribution and poverty in CGE models for developing economies in general and for South Asia in particular. In the penultimate section (section 7), I discuss the structure of what has been termed the "dual-dual" class of models and offer a modified version of the Stifel-Thorbecke dual-dual model for analyzing the poverty impacts of trade liberalization in South Asia. The model is implemented empirically by using largely data from India In the concluding section I raise the question of how applicable the model is for other regions, e.g., some middle income Asian economies with large pockets of poverty. I end with some tentative suggestions regarding poverty analysis in an "extended dual-dual" framework for a middle income Asian economy such as Thailand and People's Republic of China as well as some other modifications including a more micro poverty analysis.

At the outset it is fair to mention that even the poverty 'incidence analysis' at the micro level is not as straightforward as it seems. For example, even cash transfers may modify behavior. Such modifications can lead to general equilibrium effects in an economy wide set of repercussions. Typically, of course, most transfers are made indirectly--- through public spending and indirect taxation. The allocation rules are not always transparent and implementation is incomplete or distorted (Bourguignon et. al. 2002). More relevant to our purpose here, often macroeconomic and structural adjustment instruments and outcomes are also involved. The declared purpose of such reforms is to enhance economic activity and long-term rate of growth. In the short-run, however, the effects may even run in the opposite direction. A careful specification of the macro-models and the macro-micro linkage is thus a prerequisite for any meaningful and policy-relevant economic analysis.

Essentially there are three levels that such a relatively complete analysis of poverty reduction impacts of macro-policy changes would involve. First level includes the macroeconomic tools and models that will allow us to estimate and evaluate the impact of various exogenous shocks and policies on macro or aggregate variables such as the GDP/capita and its macro-components, the rate of interest, inflation/deflation via changes in the aggregate price level, the exchange rate and so on. The time frame must also be made explicit. At the second level we need to have tools and procedures for disaggregating the values of the variables obtained through our modelling and estimation exercises at the first level. Thus, at the end of our procedures at this level we will have at our disposal a disaggregated picture of the effects of policies on sectoral activities, and returns to factors and households at the appropriate levels of disaggregation. The last, bottom layer usually consists of a micro-module where an 'incidence analysis' can be carried out through the manipulation of household micro data with the help of relevant theories of distribution, household income generation and consumption.

Our earlier review of the CGE models (Khan2004a) revealed that for developing economies the useful CGE models can be conveniently categorized in three "generational" classes.⁵ The first generation, starting with the pioneering works of Taylor and Lysy (1980) and Adelman and Robinson (1979) in the late 70s and the 80s focused increasingly on trade policy issues. The second generation in the late 80s and 90s made income distribution in the context of structural adjustment policies as the main focus, although it must be added that the pioneering works in both the Lysy and Taylor volume, and the Adelman-Robinson volume did not neglect distribution. The main difference is the explicit reckoning with Structural Adjustment Programs (SAPs). In the late 90s, explicit attention began to be paid to the poverty impact of SAPs within a CGE modelling context. In this context, with the Work of Decaluwe et. al. (1999), we seem to be in the third generation of CGE models where poverty impact has been modeled explicitly. The present work may be said to belong to this "third generation" of models for poverty analysis under globalization in a general equilibrium setting for Asian Developing Economies (ADEs).⁶

Download this Discussion Paper [ PDF 431.2KB| 61 pages ].

Comment(s)

There are [0] comment(s) for this entry. Post a comment.