Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy

Matteo Richiardi and Ambra Poggi ()
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Ambra Poggi: University of Milan-Bicocca LABORatorio R. Revelli

International Journal of Microsimulation, 2014, vol. 7, issue 2, 3-39

Abstract: Dynamic microsimulation modelling involves two stages: estimation and forecasting. Unobserved heterogeneity is often considered in estimation, but not in forecasting, beyond trivial cases. Non-trivial cases involve individuals that enter the simulation with a history of previous outcomes. We show that the simple solutions of attributing to these individuals a null effect or a random draw from the estimated unconditional distributions lead to biased forecasts, which are often worse than those obtained neglecting unobserved heterogeneity altogether. We then present a first implementation of the Rank method, a new algorithm for assigning individual effects to the simulation sample. Out-of-sample validation of our model shows that use of the Rank method significantly improves the quality of the forecasts.

Keywords: Dynamic microsimulation; Unobserved heterogeneity; Validation; Rank method; Assignment algorithms; Female labour force participation; Italy (search for similar items in EconPapers)
JEL-codes: C18 C23 C25 C53 J11 J12 J21 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:ijm:journl:v:7:y:2014:i:2:p:3-39

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