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Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments

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  • Phillipp Eisenhauer
  • James J. Heckman
  • Stefano Mosso

Abstract

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.

Suggested Citation

  • Phillipp Eisenhauer & James J. Heckman & Stefano Mosso, 2014. "Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments," NBER Working Papers 20622, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20622
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    Cited by:

    1. Rania Gihleb & Osnat Lifshitz, . "Dynamic Effects of Educational Assortative Mating on Labor Supply," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics.
    2. Brant Abbott & Giovanni Gallipoli & Costas Meghir & Giovanni L. Violante, 2019. "Education Policy and Intergenerational Transfers in Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2569-2624.
    3. Jérôme Adda & Christian Dustmann & Katrien Stevens, 2017. "The Career Costs of Children," Journal of Political Economy, University of Chicago Press, vol. 125(2), pages 293-337.
    4. Bo Honoré & Thomas Jørgensen & Áureo de Paula, 2020. "The informativeness of estimation moments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 797-813, November.
    5. Jack Britton & Ben Waltmann, 2021. "Revisiting the solution of dynamic discrete choice models: time to bring back Keane and Wolpin (1994)?," IFS Working Papers W21/13, Institute for Fiscal Studies.
    6. Brant Abbott & Giovanni Gallipoli & Costas Meghir & Giovanni L. Violante, 2013. "Education Policy�and Intergenerational Transfers in Equilibrium," Cowles Foundation Discussion Papers 1887, Cowles Foundation for Research in Economics, Yale University.
    7. Franco Peracchi & Claudio Rossetti, 2022. "A nonlinear dynamic factor model of health and medical treatment," Health Economics, John Wiley & Sons, Ltd., vol. 31(6), pages 1046-1066, June.
    8. James J. Heckman & John Eric Humphries & Greg Veramendi & Sergio S. Urzua, 2014. "Education, Health and Wages," NBER Working Papers 19971, National Bureau of Economic Research, Inc.
    9. Manudeep Bhuller & Philipp Eisenhauer & Moritz Mendel, 2022. "Sequential Choices, Option Values, and the Returns to Education," Papers 2205.05444, arXiv.org.
    10. Maibom, Jonas, 2021. "The Welfare Effects of Mandatory Reemployment Programs: Combining a Structural Model and Experimental Data," IZA Discussion Papers 14866, Institute of Labor Economics (IZA).
    11. Chuan, A. & Zhang, W., 2021. "Non-College Occupations, Workplace Routinization, and the Gender Gap in College Enrollment," Cambridge Working Papers in Economics 2177, Faculty of Economics, University of Cambridge.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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