Income Distribution and Poverty in CGE Models: the Third Generation of Models for Developing Economies

Since the publication of the pathbreaking book by Irma Adelman and Sherman Robinson on the Republic of Korea in 1979, the literature on applied general equilibrium modelling has exploded. It is not relevant to review all of them. In this section our focus is narrowly on the strand of literature dealing with income distribution and poverty. The seminal contribution by Adelman and Robinson already had used an implicit SAM to capture both factorial and household income distribution in a disaggregated manner. At about the same time the work of Lysy and Taylor (1980) focused on Brazil and made distributional aspects a part of the overall analysis. Dervis, De Melo and Robinson (1982) also addressed distributional issues in the general equilibrium modelling context. However, real concern with distribution and poverty analysis started towards the end of 1980s, after a decade of structural adjustment policies. Under the aegis of the OECD, Thorbecke (1991) for Indonesia, de Janvry, Sadoulet and Fargeix (1991) for Ecuador, Morrison (1991) for Morocco and Chia, Wahba and Whalley for the Ivory Coast are some modelling examples from this “second generation” of CGE models for developing countries that addressed income distribution and welfare issues in greater detail than before. A number of papers by Bourguignon and others also contributed to this stream.²¹

We can summarize the main analytical developments in modelling distribution upto this point by noting that these first and second generation models relied on a representative household assumption and fixed distributional coefficients for the household income distribution. Therefore, the analysis of poor households was necessarily coarse. No information about intra representative household income distribution and poverty was sought or used. The multiplier decomposition models of Thorbecke and Jung (1996) for poverty analysis in Indonesia and Khan (1999) for South Africa also share this weakness.

However, by utilizing the information in household income and expenditure surveys, it is now possible to generate intrahousehold groups income distribution and poverty profiles. It is also possible to use these profiles as part of the initial calibrating exercise in CGE models. A set of recent modelling efforts have been directed in precisely this direction.²² Here, the paper by Decaluwé, Bernard, A. Patry, Luc Savard, and Erik Thorbecke (1999) is a pioneering piece. Another paper by Decaluwé, Dumont and Savard (1999) tests the relevance of intrahousehold distributional information for poverty analysis. Based on an archetypal economy with four areas of activity (agriculture, industry, marketable and nonmarketable services), three factors of production (capital, skilled and unskilled labor) and four types of agents (rest of the world, government, firms and households), their approach is to isolate the contribution of average income variations, poverty line changes, and income distributional changes and then to look at the effect of these variations on various poverty indicators. Their results are unambiguous. They clearly highlight the relevance and significance of intrahousehold group information. Of the three influences they discuss, the changes in poverty line in a price-endogenous model accounts for most of the changes in poverty. Therefore, both intra-household group information and price endogeneity that allows us to compute a new nominal poverty line after each policy change are important. Azis (2002) is an example of the use of this approach for analyzing poverty after the Asian financial crisis.²³ Another set of papers exemplified by Cogneau and Robillard (2000) and Cororaton (2003) utilizes the household expenditure survey results to carry out microsimulations. Here each household is treated effectively as an individual economic agent and its decisions are modeled directly.

Since one of the purposes of this paper is to see if there are” generic” models of poverty analysis within the CGE family of models, I now turn to a detailed discussion and evaluation of a generic model by Stifel and Thorbecke (2003) to draw out some relevant methodological and policy lessons.

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