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PPML estimation of dynamic discrete choice models with aggregate shocks, Volume 1
Author:Artuc, Erhan; Country:United States; World;
Date Stored:2013/06/12Document Date:2013/06/01
Document Type:Policy Research Working PaperSubTopics:Scientific Research & Science Parks; Econometrics; Economic Theory & Research; Science Education; Statistical & Mathematical Sciences
Language:EnglishMajor Sector:Industry and trade
Rel. Proj ID:1W-Trade And Poverty -- -- P111069;Region:The World Region; Rest Of The World
Report Number:WPS6480Sub Sectors:Other domestic and international trade
Collection Title:Policy Research working paper ; no. WPS 6480Volume No:1

Summary: This paper introduces a computationally efficient method for estimating structural parameters of dynamic discrete choice models with large choice sets. The method is based on Poisson pseudo maximum likelihood (PPML) regression, which is widely used in the international trade and migration literature to estimate the gravity equation. Unlike most of the existing methods in the literature, it does not require strong parametric assumptions on agents' expectations, thus it can accommodate macroeconomic and policy shocks. The regression requires count data as opposed to choice probabilities; therefore it can handle sparse decision transition matrices caused by small sample sizes. As an example application, the paper estimates sectoral worker mobility in the United States.

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