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Approximate Solutions to Stochastic Dynamic Programs

Author

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  • Stern, Steven
Abstract
This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified.

Suggested Citation

  • Stern, Steven, 1997. "Approximate Solutions to Stochastic Dynamic Programs," Econometric Theory, Cambridge University Press, vol. 13(3), pages 392-405, June.
    • Handle: RePEc:cup:etheor:v:13:y:1997:i:03:p:392-405_00
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    Citations

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    Cited by:

    1. Monika Bütler & Olivia Huguenin & Federica Teppa, 2005. "Why Forcing People to Save Retirement May Backfire," Cahiers de Recherches Economiques du Département d'économie 05.05, Université de Lausanne, Faculté des HEC, Département d’économie.
    2. Shawn Ni & Michael Podgursky, 2016. "How Teachers Respond to Pension System Incentives: New Estimates and Policy Applications," Journal of Labor Economics, University of Chicago Press, vol. 34(4), pages 1075-1104.
    3. Monika Bütler & Olivia Huguenin & Federica Teppa, 2005. "Why Forcing People to Save for Retirement May Backfire," University of St. Gallen Department of Economics working paper series 2005 2005-09, Department of Economics, University of St. Gallen.
    4. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin & Kopasker, Daniel & Vittal Katikireddi, Srinivasa, 2023. "SimPaths: an open-source microsimulation model for life course analysis," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    5. Arvid Raknerud & Rolf Golombek, 2000. "Exit Dynamics with Rational Expectations," Discussion Papers 291, Statistics Norway, Research Department.
    6. Erik Hernoes & Marte Sollie & Steinar Strøm, 2000. "Early Retirement and Economic Incentives," Scandinavian Journal of Economics, Wiley Blackwell, vol. 102(3), pages 481-502, September.
    7. Luca Spataro, 2002. "New Tools in Micromodeling Retirement Decisions: Overview and Applications to the Italian Case," Computing in Economics and Finance 2002 109, Society for Computational Economics.
    8. van de Ven, Justin, 2011. "A structural dynamic microsimulation model of household savings and labour supply," Economic Modelling, Elsevier, vol. 28(4), pages 2054-2070, July.
    9. Bingley, Paul & Lanot, Gauthier, 2004. "Employer pay policies, public transfers and the retirement decisions of men and women in Denmark," European Economic Review, Elsevier, vol. 48(1), pages 181-200, February.
    10. repec:ijm:journl:v109:y:2017:i:1:p:135-166 is not listed on IDEAS
    11. Bütler, Monika & Huguenin, Olivia & Teppa, Federica, 2004. "What Triggers Early Retirement? Results from Swiss Pension Funds," CEPR Discussion Papers 4394, C.E.P.R. Discussion Papers.
    12. Justin W. van de Ven, 2017. "Parameterising a detailed dynamic programming model of savings and labour supply using cross-sectional data," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 135-166.

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