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Microsimulations in the Presence of Heterogeneity


  • Constantijn W.A. Panis



This 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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  • Constantijn W.A. Panis, 2003. "Microsimulations in the Presence of Heterogeneity," Working Papers wp048, University of Michigan, Michigan Retirement Research Center.
  • Handle: RePEc:mrr:papers:wp048

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    References listed on IDEAS

    1. Richard Blundell & Alan Duncan & Julian McCrae & Costas Meghir, 2000. "The labour market impact of the working families’ tax credit," Fiscal Studies, Institute for Fiscal Studies, vol. 21(1), pages 75-103, March.
    2. Tjalling C. Koopmans & Martin J. Beckmann, 1955. "Assignment Problems and the Location of Economic Activities," Cowles Foundation Discussion Papers 4, Cowles Foundation for Research in Economics, Yale University.
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    Cited by:

    1. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    2. Munch, Jakob Roland & Rosholm, Michael & Svarer, Michael, 2008. "Home ownership, job duration, and wages," Journal of Urban Economics, Elsevier, vol. 63(1), pages 130-145, January.
    3. Matteo G. Richiardi, 2012. "Forecasting with Unobserved Heterogeneity," LABORatorio R. Revelli Working Papers Series 123, LABORatorio R. Revelli, Centre for Employment Studies.
    4. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.

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