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Nonparametric identification of behavioral responses to counterfactual policy interventions in dynamic discrete decision processes

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  • Aguirregabiria, Victor

Abstract

This paper deals with identification in Markov dynamic discrete decision processes. It shows the nonparametric identification of the behavioral responses to counterfactual policy interventions that modify the one- period utility function.
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  • Aguirregabiria, Victor, 2005. "Nonparametric identification of behavioral responses to counterfactual policy interventions in dynamic discrete decision processes," Economics Letters, Elsevier, vol. 87(3), pages 393-398, June.
    • Handle: RePEc:eee:ecolet:v:87:y:2005:i:3:p:393-398
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    1. 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.
    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," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 497-529.
    4. J. Rust & J. F. Traub & H. Wozniakowski, 2002. "Is There a Curse of Dimensionality for Contraction Fixed Points in the Worst Case?," Econometrica, Econometric Society, vol. 70(1), pages 285-329, January.
    5. Matzkin, Rosa L., 1993. "Nonparametric identification and estimation of polychotomous choice models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 137-168, July.
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    Citations

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    Cited by:

    1. Victor Aguirregabiria, 2006. "Another Look at the Identification of Dynamic Discrete Decision Processes: With an Application to Retirement Behavior," 2006 Meeting Papers 169, Society for Economic Dynamics.
    2. Le-Yu Chen, 2009. "Identification of structural dynamic discrete choice models," CeMMAP working papers CWP08/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. George-Levi Gayle & Limor Golan, "undated". "Estimating a Dynamic Adverse Selection Model: Labor Force Experience and the Changing Gender Earnings Gap 1968-93," GSIA Working Papers 2006-E40, Carnegie Mellon University, Tepper School of Business.
    4. 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.
    5. Xun Tang, 2009. "Rationalizable Counterfactual Choice Probabilities in Dynamic Binary Choice Processes," PIER Working Paper Archive 09-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. A. Norets & X. Tang, 2014. "Semiparametric Inference in Dynamic Binary Choice Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1229-1262.
    7. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    8. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
    9. Victor Aguirregabiria, 2005. "Another Look at the Identification of Dynamic Discrete Decision Processes," Econometrics 0504006, University Library of Munich, Germany.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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