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Generalized Indirect Inference for Discrete Choice Models

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Author Info

  • Anthony A. Smith, Jr.
  • Michael Keane

Abstract

This paper develops and implements a practical simulation-based method for estimating dynamic discrete choice models. The method, which can accommodate lagged dependent variables, serially correlated errors, unobserved variables, and many alternatives, builds on the ideas of indirect inference. In particular, the method uses an auxiliary model---typically a linear probability model---to summarize the statistical properties of the observed and simulated data. The method then chooses the structural parameters so that the coefficients of the auxiliary model in the simulated data match as closely as possible those in the observed data. The main difficulty in implementing indirect inference in discrete choice models is that the objective surface is a step function, rendering useless gradient-based optimization methods. To overcome this obstacle, this paper shows how to smooth the objective surface. The key idea is to use a smooth function of the latent utilities as the dependent variable in the auxiliary model. As the smoothing parameter goes to zero, this function delivers the discrete choice implied by the latent utilities, thereby guaranteeing consistency. A set of Monte Carlo experiments shows that the method is fast, robust, and nearly as efficient as maximum likelihood when the auxiliary model is sufficiently rich

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 512.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nawm04:512

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Related research

Keywords: indirect inference; discrete choice models; simulation estimation;

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Cited by:
  1. Joseph G. Altonji & Anthony Smith & Ivan Vidangos, 2009. "Modeling Earnings Dynamics," NBER Working Papers 14743, National Bureau of Economic Research, Inc.
  2. Shintaro Yamaguchi, 2007. "Job Search, Bargaining, and Wage Dynamics," Department of Economics Working Papers 2007-03, McMaster University.
  3. José Mustre-del-Río, 2011. "The aggregate implications of individual labor supply heterogeneity," Research Working Paper RWP 11-09, Federal Reserve Bank of Kansas City.
  4. Cristina López-Mayán, 2008. "Microeconometric Analysis Of Residential Water Demand," Working Papers wp2008_0803, CEMFI.
  5. Li Gan & Guan Gong, 2007. "Estimating Interdependence Between Health and Education in a Dynamic Model," NBER Working Papers 12830, National Bureau of Economic Research, Inc.
  6. Ivan Vidangos, 2009. "Household welfare, precautionary saving, and social insurance under multiple sources of risk," Finance and Economics Discussion Series 2009-14, Board of Governors of the Federal Reserve System (U.S.).

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