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Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method

Matteo Richiardi and Ambra Poggi

No 267, Carlo Alberto Notebooks from Collegio Carlo Alberto

Abstract: Dynamic microsimulation modeling 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 attributing the individual effects to the simulation sample which greatly simplifies those already known in the literature. Out-of-sample validation of our model shows that correctly imputing unobserved heterogeneity significantly improves the quality of the forecasts.

Keywords: Dynamic microsimulation; Unobserved heterogeneity; Validation; Rank method; Assignment algorithms; Female labor force participation; Italy (search for similar items in EconPapers)
JEL-codes: C18 C23 C25 C53 J11 J12 J21 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2012
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Imputing Individual Effects in Dynamic Microsimulation Models.An application of the Rank Method (2012) Downloads
Working Paper: Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method (2012) Downloads
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