Distributional analysis using microsimulations in Stata

Ex-ante evaluation of the distributional effects of a macroeconomic shock is a difficult task. One approach relies on microsimulation models often combined with a macroeconomic model (e.g., a CGE model). This approach typically follows a top-down sequence where the microsimulation model takes the outputs from the macroeconomic model as given and then uses a household survey to generate changes in the data that mimic the resulting macroeconomic aggregates. For example, this approach could be used to model how changes in the level of employment and wages by industry derived from a given macroeconomic scenario (e.g., a set of climate change policies) impact poverty and inequality. This presentation compares two methods (reweighting versus modeling occupational choices) for analyzing changes in the labor market in the context of a top-down macro–micro model. I use two surveys that are more than 10 years apart to explore how these two different ways of modeling changes in the labor market using the older survey can predict what we observe in the newer survey.