# 2. Methodological framework and scenarios

To provide a quantitative assessment of the policy scenarios, we rely on a soft linkage between the global recursive dynamic CGE model ENVISAGE (van der Mensbrugghe 2019) and the GIDD microsimulation framework (Bussolo et al. 2010). First, the ENVISAGE model is run to provide an assessment of policy scenarios under consideration. Next, selected indicators from this assessment are transferred to the GIDD model. These are further implemented as an external shock relative to the baseline scenario within the GIDD modeling framework to estimate the distributional impacts of the considered set of policies. Such soft-linking approach does not incorporate any backward linkages from the GIDD to ENVISAGE and can be considered as a decomposition of the aggregate ENVISAGE results using the microsimulation framework.

Key data input to the ENVISAGE model for the reference year representation is the Global Trade Analysis Project (GTAP) 10 MRIO Data Base with 2014 as the reference year (Aguiar et al. 2019; Carrico et al. 2020). Relying on the MRIO data, which distinguishes agent-based demand for imports by region of origin, selected manufacturing sectors in the ENVISAGE model are represented using the MRIO specification, while all other sectors use the standard Armington assumption, treating imports as imperfect substitutes with domestically produced commodities—and sourcing is done at the national level. The model is solved as a sequence of comparative static equilibria where the factors of production accumulate over time. Nested constant-elasticity-of-substitution (CES) functions are used to represent production technologies. 141 regions and 65 sectors of the GTAP 10 Data Base have been aggregated to 21 countries/regions and 27 sectors for the current assessment. Annex A reports sectoral and regional mappings, as well as provides identification of the sectors of the model that are represented using the MRIO specification. Annex B provides technical details of the modeling framework.

The GIDD is a top-down macro-micro simulation framework that exploits heterogeneity observed in household surveys to distribute macroeconomic shocks obtained from the CGE model. Transferred shocks are distributed in a predefined set of linkage aggregate variables that communicate between the two models. The GIDD model relies on a collection of 130 nationally representative household surveys with harmonized variables on demographics, education, labor, welfare and consumption. The sample covers more than 10.5 million individuals from countries constituting 83.4% of global GDP and 86.3% of global population. The data is described with more detail in Ahmed et al. (2020). Additional details regarding the GIDD microsimulation framework can be found in Bussolo et al. (2010).

The ENVISAGE-GIDD model linking process is performed in a sequence of steps, where the two models are pre-calibrated to the same demographic and macroeconomic baseline assumptions. ENVISAGE and GIDD models are connected through changes in labor supply, skill formation, and real earnings. In terms of labor supply, the macro and micro models incorporate projections for skilled and unskilled labor over time. The GIDD framework, in addition, reallocates workers across sectors based on aggregate general equilibrium conditions. After reallocation, the GIDD simulates impacts on real earnings, income growth, and changes in relative prices for food and non-food expenditures. The shocks are transmitted through a set of linkage variables that connect the macro and micro models. Figure 1 provides an overview of the general approach. For additional details on the model linkage implementation an interested reader is referred to Chepeliev et al. (2021).

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