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PPML estimation of dynamic discrete choice models with aggregate shocks

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  • Artuc, Erhan

Abstract

This paper introduces a computationally efficient method for estimating structural parameters of dynamic discrete choice models with large choice sets. The method is based on Poisson pseudo maximum likelihood (PPML) regression, which is widely used in the international trade and migration literature to estimate the gravity equation. Unlike most of the existing methods in the literature, it does not require strong parametric assumptions on agents'expectations, thus it can accommodate macroeconomic and policy shocks. The regression requires count data as opposed to choice probabilities; therefore it can handle sparse decision transition matrices caused by small sample sizes. As an example application, the paper estimates sectoral worker mobility in the United States.

Suggested Citation

  • Artuc, Erhan, 2013. "PPML estimation of dynamic discrete choice models with aggregate shocks," Policy Research Working Paper Series 6480, The World Bank.
  • Handle: RePEc:wbk:wbrwps:6480
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    References listed on IDEAS

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    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Thierry Magnac & David Thesmar, 2002. "Identifying Dynamic Discrete Decision Processes," Econometrica, Econometric Society, vol. 70(2), pages 801-816, March.
    3. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 497-529.
    4. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    5. Erhan Artuç & Shubham Chaudhuri & John McLaren, 2010. "Trade Shocks and Labor Adjustment: A Structural Empirical Approach," American Economic Review, American Economic Association, vol. 100(3), pages 1008-1045, June.
    6. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    7. Artuç, Erhan & McLaren, John, 2015. "Trade policy and wage inequality: A structural analysis with occupational and sectoral mobility," Journal of International Economics, Elsevier, vol. 97(2), pages 278-294.
    8. J. M. C. Santos Silva & Silvana Tenreyro, 2006. "The Log of Gravity," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 641-658, November.
    9. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
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    Cited by:

    1. Artuc, Erhan, 2012. "Workers'age and the impact of trade shocks," Policy Research Working Paper Series 6035, The World Bank.
    2. Brücker, Herbert & Bertoli, Simone & Fernández-Huertas Moraga, Jesús, 2013. "The European Crisis and Migration to Germany: Expectations and the Diversion of Migration Flows," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79693, Verein für Socialpolitik / German Economic Association.
    3. Artuc, Erhan & Docquier, Frédéric & Özden, Çaglar & Parsons, Christopher, 2015. "A Global Assessment of Human Capital Mobility: The Role of Non-OECD Destinations," World Development, Elsevier, vol. 65(C), pages 6-26.
    4. Arias, Javier & Artuc, Erhan & Lederman, Daniel & Rojas, Diego, 2013. "Trade, informal employment and labor adjustment costs," Policy Research Working Paper Series 6614, The World Bank.

    More about this item

    Keywords

    Economic Theory&Research; Science Education; Scientific Research&Science Parks; Statistical&Mathematical Sciences; Econometrics;

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