Constrained Optimization Approaches to Estimation of Structural Models
University of Chicago Booth School of Business
Kenneth L. Judd
Stanford University - The Hoover Institution on War, Revolution and Peace; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP); National Bureau of Economic Research (NBER)
December 20, 2011
Estimating structural models is often viewed as computationally difficult, an impression partly due to a focus on the nested fixed-point (NFXP) approach. We propose a new constrained optimization approach for structural estimation. We show that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally, our approach can have speed advantages because we do not repeatedly solve the structural equation at each guess of structural parameters. Monte Carlo experiments on the canonical Zurcher bus-repair model demonstrate that the constrained optimization approach can be significantly faster.
Number of Pages in PDF File: 21
Keywords: structural estimation, constrained optimization, dynamic discrete choice models
JEL Classification: C13, C61
Date posted: February 13, 2008 ; Last revised: January 14, 2012
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