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Two Dynamic Discrete Choice Estimation Problems and Simulation Method Solutions

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  • Stern, Steven

Abstract

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results. Copyright 1994 by MIT Press.

Suggested Citation

  • Stern, Steven, 1994. "Two Dynamic Discrete Choice Estimation Problems and Simulation Method Solutions," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 695-702, November.
  • Handle: RePEc:tpr:restat:v:76:y:1994:i:4:p:695-702
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    Cited by:

    1. Quitterie Roquebert & Roméo Fontaine & Agnès Gramain, 2016. "L'aide à un parent âgé, seul et dépendant : déterminants structurels et interactions," Documents de travail du Centre d'Economie de la Sorbonne 16030, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Jose M. Fernandez, 2013. "An Empirical Model Of Learning Under Ambiguity: The Case Of Clinical Trials," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 549-573, May.
    3. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    4. Liliana E. Pezzin & Robert A. Pollak & Barbara S. Schone, 2007. "Efficiency in Family Bargaining: Living Arrangements and Caregiving Decisions of Adult Children and Disabled Elderly Parents," CESifo Economic Studies, CESifo Group, vol. 53(1), pages 69-96, March.
    5. Good, D. & Nadiri, M.I. & Sickles, R., 1996. "Index Number and Factor Demand Approaches to the Estimarion of Productivity," Working Papers 96-34, C.V. Starr Center for Applied Economics, New York University.
    6. Edward C. Norton & Courtney Harold Van Houtven, 2006. "Inter‐vivos Transfers and Exchange," Southern Economic Journal, John Wiley & Sons, vol. 73(1), pages 157-172, July.
    7. Tennille J. Checkovich & Steven Stern, 2002. "Shared Caregiving Responsibilities of Adult Siblings with Elderly Parents," Journal of Human Resources, University of Wisconsin Press, vol. 37(3), pages 441-478.
    8. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    9. Hiedemann, Bridget & Stern, Steven, 1999. "Strategic play among family members when making long-term care decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 40(1), pages 29-57, September.
    10. Fernandez, Jose & Cataiefe, Guido, 2009. "Model of the 2000 Presidential Election: Instrumenting for Ideology," MPRA Paper 16264, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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