Autori: Richiardi, Matteo, Poggi, Ambra
Titolo: Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method
Periodico: Università degli studi di Torino. Dip. Di Economia e Statistica Cognetti de Martiis. Working paper series
Anno: 2012 - Volume: 9 - Fascicolo: 13 - Pagina iniziale: 1 - Pagina finale: 36

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 estimat ed unconditional distributions lead to biased forecasts, which are often worse than those obtained neglect ing 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.




Testo completo: http://www.est.unito.it/do/home.pl/Download?doc=/allegati/wp2012dip/13_wp_richiardi_poggi.pdf

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