The Modeling of Macroeconomic Shocks and Policies

The importance of distributional issues in policymaking creates a need for empirical tools that can help assess the impact of economic shocks and policies, such as terms-of-trade shocks, fiscal adjustment, monetary policy, and trade liberalization, on the living standards of relevant individuals.   B. Essama-Nssah reviews some of the modeling approaches that are currently available for the analysis of the impact of macroeconomic shocks and policies on poverty and income distribution. These approaches provide a framework that links a macroeconomic model to a model of the distribution of economic welfare at the individual or household level.

The approaches or specific models described in this note vary in the ways they specify the macroeconomy, the distribution of welfare, and macro-micro linkages. A first series of models focuses only on income distribution, while the macromodel remains implicit. These models can be used in conjunction with assumptions about the response of the macroeconomy to shocks and policies. The models in this family include POVCAL and SimSIP, which are purely statistical, and PovStat, the maximum value or envelope model, and the household income and occupational choice model.

A second series involves embedding distributional mechanisms within a general equilibrium framework. While the standard representative household approach limits the analysis of the distributional impact of shocks and policies to their effects on representative socioeconomic groups, the extended representative household approach considers various socioeconomic groups as representative households. Within a general equilibrium framework, it is possible to account for various market and household behavioral adjustments induced by shocks or policies.

The third series adopts a modular approach in linking poverty and distributional outcomes to macroeconomic shocks and policies. These models have been influenced by an emerging approach known as Top-Down/Bottom-Up; they try to account for the feedback effects from the microlevel to the macrolevel and back until convergence is achieved. Within this class, the author focuses on the 123PRSP model (one country, two sectors, and three commodities); the poverty analysis macroeconomic simulator; a macro-micro simulation model that uses the investment savings–liquidity money framework for macroeconomic analysis; and the integrated macroeconomic model for poverty analysis framework, which links a dynamic computable general equilibrium model to unit record data.

The best approach to adopt depends on the problem at hand, the data, and other resource constraints.

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