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Generalized Indirect Inference for Discrete Choice Models

Listed author(s):
  • Marianne Bruins

    ()

    (Nuffield College and Dept of Economics, Univesity of Oxford)

  • James A. Duffy

    ()

    (Nuffield College, Dept of Economics and Institute for New Economic Thinking at the Oxford Martin School, Univesity of Oxford)

  • Michael P. Keane

    ()

    (Nuffield College and Dept of Economics, Univesity of Oxford)

  • Anthony A. Smith, Jr

    (Yale University)

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. The main difficulty in implementing indirect inference in discrete choice models is that the objective surface is a step function, rendering gradientbased optimization methods useless. To overcome this obstacle, this paper shows how to smooth the objective surface. The key idea is to use a smoothed 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. We establish conditions on the smoothing such that our estimator enjoys the same limiting distribution as the indirect inference estimator, while at the same time ensuring that the smoothing facilitates the convergence of gradient-based optimization methods. 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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File URL: https://www.nuffield.ox.ac.uk/economics/papers/2015/GII_July_22_2015.pdf
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2015-W08.

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Length: 56 pages
Date of creation: 15 Jul 2015
Handle: RePEc:nuf:econwp:1508
Contact details of provider: Web page: https://www.nuffield.ox.ac.uk/economics/

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  1. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
  2. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
  3. Fermanian, Jean-David & Salani , Bernard, 2004. "A Nonparametric Simulated Maximum Likelihood Estimation Method," Econometric Theory, Cambridge University Press, vol. 20(04), pages 701-734, August.
  4. Meghan M. Skira, 2015. "Dynamic Wage And Employment Effects Of Elder Parent Care," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 63-93, February.
  5. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
  6. Cristina Lopez-Mayan, 2014. "Microeconometric Analysis of Residential Water Demand," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 137-166, September.
  7. Magnac, Thierry & Robin, Jean-Marc & Visser, Michael, 1995. "Analysing Incomplete Individual Employment Histories Using Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(S), pages 153-169, Suppl. De.
  8. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
  9. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(01), pages 105-157, February.
  10. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
  11. Lopez Garcia, Italo, 2015. "Human Capital and Labor Informality in Chile: A Life-Cycle Approach," Working Papers 1087, RAND Corporation.
  12. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
  13. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
  14. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
  15. Tong Li & Bingyu Zhang, 2015. "Affiliation and Entry in First-Price Auctions with Heterogeneous Bidders: An Analysis of Merger Effects," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 188-214, May.
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