Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments
James Heckman and
No 20622, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: C13 C15 C35 I21 (search for similar items in EconPapers)
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Published as Philipp Eisenhauer & James J. Heckman & Stefano Mosso, 2015. "Estimation Of Dynamic Discrete Choice Models By Maximum Likelihood And The Simulated Method Of Moments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 331-357, 05.
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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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