households and governments in multiple product markets and across several countries and regions of the world. The model incorporates well-developed dynamic features such as accumulation of capital through changes in savings and investment.

It is also worth noting some of the key limitations of the model, including the lack of positive dynamic feedback loops concerning the accumulation of knowledge and the absorption of foreign technology through PTAs-facilitated FDI. It also does not allow for modeling of extensive margins in exports. Therefore, the gains captured here may underestimate the eventual impact and represent the lower bound of potential benefits. In contrast, PTA-driven productivity increases in member countries could undermine the competitiveness of non-member countries and exacerbate the detrimental effects on non-member countries.<sup>4</sup>

# **2.2. Micro-simulation model**

The impact of PTAs is differentiated across different types of households and workers. Such heterogeneity is key in determining the poverty and distributional impacts of any trade agreement. We use the GIDD modeling framework in order to model these distributional consequences of the macro-economic results of the PTAs.<sup>5</sup> The GIDD is a top-down macro-micro simulation framework, which distributes the macroeconomic results of the CGE model to households using SUSENAS 2014 as the source of data. The microeconomic model distributes the effects while keeping consistency with the aggregate behavior observed in the macro model. The two models operate mainly through changes in labor supply, skill formation, and real earnings, as a result, they are linked through key specific variables that reflect these changes (see Annexes 1 and 2 for details).

The micro simulation framework is performed in 5 steps. Steps 1 to 4 change the distribution of benefits across individuals, keeping the national average intact; while step 5 applies a distributional-neutral growth for all individuals. Briefly explained, step 1 changes the demographic structure of the household survey according to exogenous population and education projections. The second step allows for the migration of labor from shrinking to expanding sectors in the economy while changes in skill and sectoral wage premia are modeled in step 3. Step 4 adjusts for

> 4 Another limitation of the model is that it does not incorporate the intended harmonization of labor and environmental standards within the CPTPP. While such harmonization has social and environmental benefits, it may also reduce competitiveness of firms that currently do not meet such standards, reducing the potential economic gains.

> 5 GIDD was developed by the World Bank’s Development Prospects Group and was inspired by previous efforts involving top-down simulation exercises. See Bourguignon, F.,  Bussolo, M., and Pereira da Silva, L. A. (2008); Davies (2009). Earlier versions of the GIDD can be found in Bourguignon and Bussolo (2013); and Bussolo, De Hoyos, and Medvedev (2010a, b). Recent modeling applications include distributional assessments of the effects of demographic change (Ahmed et al., 2014); Africa’s resilience to climate, violence, and global economic stagnation (Devarajan et al., 2015), deeper regional trade integration in Eastern Africa (Balistreti et al., 2016), or the poverty and shared prosperity effects of China’s economic slowdown and rebalancing (Lakatos et al., 2016).

6