Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments
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.
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Document Object Identifier (DOI): 10.3386/w20622
Published: 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. citation courtesy of
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