2. Macro-micro methodologies for ex-ante evaluation of the distributional impacts of trade

**The importance of assessing the distributional gains from trade has been long recognized in economic thinking.** The origin of dynamic microsimulation can be traced back to the 1950s seminal work of Orcutt (1957) whose contributions aimed at overcoming the limitations of models available at that time. Orcutt observed that those earlier models could be used to predict the aggregate impact but could not describe the distributional impacts of policy reforms nor the effects on inequality of long-term policy options or shocks. Data availability and modeling have significantly advanced since then, yet dynamic microsimulations remain the main tool to study distributional change and to provide the unique perspective of projecting samples of population forward in time.

**Traditionally, tools for policy analysis concerned with distributional issues tend to be either exclusively micro or macro** . Microsimulation models based on household samples are used for studying reforms of a variety of policy choices, such as tax-benefit systems, impact of delivering public goods like education or health care, or changes in labor market regulations. Macro modeling, on the other hand, is typically used to measure the impact of reforms in tax, trade, finance or monetary policies on the sectoral structure of the economy, its level of employment and wages. From the aggregate information, it is possible to inform which groups in the population will benefit or lose from the reform being analyzed.

**Aggregate outcomes from macro models are insufficient to assess how individual households might be affected by the policy being analyzed** . Likewise, seemingly micro-oriented policies like a reform in cash transfers or in the pension system may have important macro effects through labor supply and savings, in turn, these macro effects of micro-oriented policies will impact wages, employment and returns to wealth affecting the income distribution within a population. Hence, the need to combine macro and micro approaches to policy analysis is obvious.

**Several approaches have been proposed to integrate macro-micro frameworks that allow for the simultaneous study of the distributional and macro impact of policy reforms** (Bourguignon and Bussolo 2013). The usual problem of data availability and quality is, in the case of a macro-micro model, compounded because data from national accounts and from household surveys – the two most common sources of macro and micro data – need to be reconciled, let alone the economic treatment of their respective sources. In this context, the modeling framework used in this paper represents a departure from the static simple top-down approach. It incorporates a macro-micro framework operating in a dynamic setting.

**This paper discusses the CGE-GIDD macro-micro methodology that can be used for the ex-ante assessment of trade policy and shocks.** This paper uses the Global Income Distribution Dynamics (GIDD) microsimulation framework in combination with the global computable general equilibrium (CGE) model called LINKAGE/ENVISAGE. CGE-GIDD is a “top-down” macro-micro simulation framework that exploits heterogeneity observed in household surveys to distribute macroeconomic shocks. CGE-GIDD was developed by the World Bank (Bussolo, De Hoyos, and Medvedev 2010), inspired by previous efforts involving simulation exercises (Bourguignon, Ferreira, and Leite 2008; Bourguignon, Bussolo, and Pereira da Silva 2008; Davies 2009). The full technical documentation of the LINKAGE/ENVISAGE model is provided by van der Mensbrugghe (2013; 2020); the following sub-section briefly describes the main structure of the models.

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