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Forecasting with Unobserved Heterogeneity

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  • Matteo G. Richiardi

Abstract

Forecasting based on random intercepts models requires imputation of the individual permanent effects to the simulated individuals. When these individuals enter the simulation with a history of past outcomes this involves sampling from conditional distributions, which might be unfeasible. I present a method for drawing individual permanent effects from a conditional distribution which only requires to invert the corresponding estimated unconditional distribution. While the algorithms currently available in the literature require polynomial time, the proposed method only requires matching two ranks and works therefore in N lnN time.

Suggested Citation

  • Matteo G. Richiardi, 2012. "Forecasting with Unobserved Heterogeneity," LABORatorio R. Revelli Working Papers Series 123, LABORatorio R. Revelli, Centre for Employment Studies.
    • Handle: RePEc:cca:wplabo:123
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    File URL: http://www.laboratoriorevelli.it/_pdf/wp123.pdf
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    References listed on IDEAS

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    1. Constantijn W.A. Panis, 2003. "Microsimulations in the Presence of Heterogeneity," Working Papers wp048, University of Michigan, Michigan Retirement Research Center.
    2. Li, Jinjing & O'Donoghue, Cathal, 2012. "A methodological survey of dynamic microsimulation models," MERIT Working Papers 2012-002, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
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    Cited by:

    1. Jinjing Li & Denisa Maria Sologon, 2014. "A Continuous Labour Supply Model in Microsimulation: A Life-Cycle Modelling Approach with Heterogeneity and Uncertainty Extension," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-15, November.
    2. Richiardi Matteo & Poggi Ambra, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201213, University of Turin.
    3. Ross Richardson & Lia Pacelli & Ambra Poggi & Matteo Richiardi, 2018. "Female Labour Force Projections Using Microsimulation for Six EU Countries," International Journal of Microsimulation, International Microsimulation Association, vol. 11(2), pages 5-51.
    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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    More about this item

    Keywords

    forecasting; microsimulation; random intercept models; unobserved heterogeneity;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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