Microsimulations in the Presence of Heterogeneity
AbstractThis paper develops a method that improves researchers’ ability to account for behavioral responses to policy change in microsimulation models. Current microsimulation models are relatively simple, in part because of the technical difficulty of accounting for unobserved heterogeneity. This is all the more problematic because data constraints typically force researchers to limit their forecasting models to relatively few, mostly time-invariant explanatory covariates, so that much of the variation across individuals is unobserved. Furthermore, failure to account for unobservables often leads to biased estimates of structural parameters, which are critically important for measuring behavioral responses. This paper develops a theoretical approach to incorporate (univariate and multivariate) unobserved heterogeneity into microsimulation models; illustrates computer algorithms to efficiently implement heterogeneity in continuous and limited dependent models; and evaluates the importance of unobserved heterogeneity by conducting Monte Carlo simulations.
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Bibliographic InfoPaper provided by University of Michigan, Michigan Retirement Research Center in its series Working Papers with number wp048.
Length: 17 pages
Date of creation: May 2003
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-02-13 (All new papers)
- NEP-CBE-2005-02-13 (Cognitive & Behavioural Economics)
- NEP-CMP-2005-02-13 (Computational Economics)
- NEP-ECM-2005-02-13 (Econometrics)
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