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Joint analysis of the discount factor and payoff parameters in dynamic discrete choice models

Author

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  • Tatiana Komarova
  • Fabio Sanches
  • Daniel Silva Junior
  • Sorawoot Srisuma

Abstract

Most empirical and theoretical econometric studies of dynamic discrete choice models assume the discount factor to be known. We show the knowledge of the discount factor is not necessary to identify parts, or even all, of the payoff function. We show the discount factor can be generically identified jointly with the payoff parameters. On the other hand, it is known the payoff function cannot be nonparametrically identified without any a priori restrictions. Our identification of the discount factor is robust to any normalization choice on the payoff parameters. In IO applications, normalizations are usually made on switching costs, such as entry costs and scrap values. We also show that switching costs can be nonparametrically identified, in closed‐form, independently of the discount factor and other parts of the payoff function. Our identification strategies are constructive. They lead to easy to compute estimands that are global solutions. We illustrate with a Monte Carlo study and the dataset used in Ryan ().

Suggested Citation

  • Tatiana Komarova & Fabio Sanches & Daniel Silva Junior & Sorawoot Srisuma, 2018. "Joint analysis of the discount factor and payoff parameters in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 9(3), pages 1153-1194, November.
  • Handle: RePEc:wly:quante:v:9:y:2018:i:3:p:1153-1194
    DOI: 10.3982/QE675
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    Cited by:

    1. Raphael Corbi & Fabio Miessi Sanches, 2022. "Church Competition, Religious Subsidies and the Rise of Evangelicalism: a Dynamic Structural Analysis," Working Papers, Department of Economics 2022_09, University of São Paulo (FEA-USP).
    2. Mateusz Mysliwski & Fabio M. Sanches & Daniel Silva Junior & Sorawoot Srisuma, 2020. "The Welfare Effects of Promotional Fees," CeMMAP working papers CWP35/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    4. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," NBER Working Papers 29291, National Bureau of Economic Research, Inc.
    5. Jaap H. Abbring & Øystein Daljord, 2020. "Identifying the discount factor in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 11(2), pages 471-501, May.
    6. Joachim Freyberger, 2021. "Normalizations and misspecification in skill formation models," Papers 2104.00473, arXiv.org, revised Jul 2022.

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