Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments

Philipp Eisenhauer (peisenha@uni-bonn.de), James J. Heckman (jjh@uchicago.edu) and Stefano Mosso (smosso@uchicago.edu)
Additional contact information
Philipp Eisenhauer: University of Bonn
James J. Heckman: University of Chicago
Stefano Mosso: University of Chicago

No 8548, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic dataset and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM.

Keywords: dynamic discrete choice; simulation-based estimation; returns to education (search for similar items in EconPapers)
JEL-codes: C13 C15 C35 I21 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2014-10
New Economics Papers: this item is included in nep-dcm and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published - published in: International Economic Review, 2015, 56 (2), 331 - 357

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Related works:
Journal Article: ESTIMATION OF DYNAMIC DISCRETE CHOICE MODELS BY MAXIMUM LIKELIHOOD AND THE SIMULATED METHOD OF MOMENTS (2015)
Working Paper: Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments (2014)
Working Paper: Estimation of dynamic discrete choice models by maximum likelihood and the simulated method of moments (2014)
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