It is heavily discussed whether trade liberalization is good or bad for the poor in a given (developing) country. The answer depends on a wide variety of factors, such as the type of trade barrier removed, the economic and institutional environment in the country, and the characteristics of the poor in that country (Winters 2002; Winters et al. 2004). In addition, the results can also be driven by the specific method used to measure the impact of the trade-policy reform on poverty. For an informed discussion, it is, therefore, important to understand the corresponding empirical methods at hand. Most generally, empirical studies on trade impacts can be divided into ex-post and ex-ante analyses. Whereas ex-post studies focus on the effects of trade policies that have already been implemented, ex-ante analyses simulate the effects of potential future (and actual) trade policies (Piermartini and Teh 2005). In other words, ex-post studies have both pre- and post-reform data at their disposal, while ex-ante studies rely exclusively on pre-liberalization data. Ex-post analyses have the advantage of being grounded on real-world observations; however, their difficulty lies in applying appropriate statistical methods to separate the impact of a given trade-policy reform from any other shock affecting the economy in the observation period (Hertel and Reimer 2005; Piermartini and Teh 2005). This identification problem is absent in ex-ante studies, conducting counterfactual analyses, as they allow to explicitly and exclusively simulate the trade-policy shock (Hertel and Reimer 2005). However, simulation studies encounter yet other challenges, namely to verify the assumptions concerning the model specification (e.g., parameters and functional forms) and, thus, to ensure the quality of the results (Piermartini and Teh 2005; Winters et al. 2004). Their strength, in turn, is to reveal possible orders of magnitude of a policy impact, to identify relative winners and losers, and to give insights into the quantitative importance of the mechanisms behind the effects of a given trade-policy reform on poverty (Winters 2003; Winters et al. 2004; Bourguignon et al. 1991). While examples of ex-post methods to analyze the effects of trade liberalization on poverty can be found in Winters et al. (2004), this Roundup gives an overview of some basic ex-ante methods available to quantify and evaluate the impact of a trade-policy reform - or, more generally, a macro-economic shock - on the distribution of household income for poverty (and inequality) analysis, i.e. on the micro-economic level. The methods considered here center all around so-called computable general equilibrium (CGE) models. On the one hand, they include the standard CGE approach with (one or) several representative households; on the other hand, they cover macro-micro simulations, subdivided into the top-down approach, the top-down/bottom-up approach, and the integrated approach. For each method, the Roundup provides a brief description, some applications, and a critical assessment.
