# **Box 2. Estimating Poverty Impacts in the Focus Countries**

The unifying theme of our results is that different households are affected differently by trade reforms. Thus how we derive and treat differences among households is central to the analysis. The most consistent approach embeds household behavior fully within the national CGE model, but this is computationally burdensome (Rutherford, Tarr and Shepotylo, 2006) and would add significant complexity to an already complex global analysis. A popular simplification involves solving a national CGE model and combining the resulting changes in commodity prices, factor prices and possibly quantities and employments with household data on earnings and expenditures to estimate a (first-order) approximation of the welfare effects on households. Chen and Ravallion (2004) apply this to 80,000 households to estimate the poverty effects of Chinese accession to the WTO. Hertel and Winters (2006) is conceptually similar in its estimates of the poverty implications of the Doha Round, but with up to three levels of modeling: a global multi-country CGE model to calculate the effects of the Round on each country’s prices of imports and export demand; more detailed national CGE models for twelve country case studies to estimate the effects of these on local prices etc, and, in the cases where the national models do not embed households directly, household modules to calculate the first order welfare approximations by household.

A further simplification is again to solve a CGE model with a single representative consumer, but now to consider the effects of a shock only on a few summary statistics such as average incomes, unskilled wages and food prices. Then, applying ‘poverty elasticities’ to these statistics allows one to estimate the implied change in poverty. (The poverty elasticity relates the proportionate change in poverty to the proportionate change in _per capita_ GDP – see, for example, Ravallion (1997)). This is the approach in Cline (2004), and Anderson et al. (2006) among others. These studies differ _inter alia_ in the base poverty levels to which they apply the elasticities.

For purposes of this paper, we adopt a hybrid of the alternatives. For a global model of the size we have used to explore the DDA, it is not computationally feasible to embed households or even many representative household groups into the CGE model. And neither do we have the requisite data on factor earnings by household for the majority of developing countries. However, we believe that the impact of trade reform on individual households will vary widely depending on their primary sector of employment, their endowments, as well as their consumption patterns. Therefore we reject the single poverty elasticity approach. Instead we utilize the factor earnings and income distribution data for our 15 target developing countries, where this has been obtained and processed in a uniform manner, and we estimate country-stratum-factor price-poverty line specific poverty elasticities. These elasticities embody information about the shape of the income distribution as well as the composition of household earnings in the neighborhood of the poverty line for key subgroups (strata) of the population.

The specifics of our approach are as follows: For each of our 15 countries we have household surveys that identify sources of income. As described in the Annex, we first adjust the earnings data in order to ensure that the composition of factor incomes in agriculture match those reported in the National Accounts. (A comprehensive reconciliation of these two, mutually inconsistent, sources of income would be a monumental, so we focus on the sector most central to our analysis, which also happens to be the easiest to reconcile.) We then divide households into seven strata, or groups of households, according to their predominant source of income and location: for five the criterion is that 95% or more of income comes from the named source—agricultural self-employment, non-agricultural selfemployment, urban wages, rural wages, and transfers; for the remaining two we distinguish urban diversified and rural diversified. Each stratum is then ordered by total income and divided into twenty vigntiles to create a total of 140 classes of households in each of the 15 focus countries.

For each stratum we calculate poverty elasticities with respect to each source of income, where the shares of income come from the vigntiles in which the poverty line falls, and the density of households around the poverty line from the overall distribution. The density determines the change in headcount poverty resulting from a given change in stratum income, while the earnings shares determine how a change in (e.g.) unskilled wages change stratum income in the neighborhood of the poverty line. Once the CGE model has been solved for a new set of factor prices, we can use these poverty elasticities to determine the change in stratum poverty – and, given the relative importance of stratum poverty in national poverty – the change in the latter may also be obtained.

Of course, a rise in factor earnings is only meaningful from a poverty perspective if commodity prices do not also rise by the same amount. Therefore we must deflate the factor price changes by the change in the real cost of living at the poverty line. This is obtained by solving the AIDADS demand system for the expenditure necessary to achieve the poverty level of utility at the post-reform prices.

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