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Solving Dynamic Discrete Choice Models: Integrated or Expected Value Function?

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  • Patrick Kofod Mogensen

Abstract

Dynamic Discrete Choice Models (DDCMs) are important in the structural estimation literature. Since the structural errors are practically always continuous and unbounded in nature, researchers often use the expected value function. The idea to solve for the expected value function made solution more practical and estimation feasible. However, as we show in this paper, the expected value function is impractical compared to an alternative: the integrated (ex ante) value function. We provide brief descriptions of the inefficacy of the former, and benchmarks on actual problems with varying cardinality of the state space and number of decisions. Though the two approaches solve the same problem in theory, the benchmarks support the claim that the integrated value function is preferred in practice.

Suggested Citation

  • Patrick Kofod Mogensen, 2018. "Solving Dynamic Discrete Choice Models: Integrated or Expected Value Function?," Papers 1801.03978, arXiv.org.
  • Handle: RePEc:arx:papers:1801.03978
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    References listed on IDEAS

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    1. Andriy Norets, 2010. "Continuity and differentiability of expected value functions in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 1(2), pages 305-322, November.
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    3. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    4. Igal Hendel & Aviv Nevo, 2006. "Sales and consumer inventory," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 543-561, September.
    5. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    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. Che‐Lin Su & Kenneth L. Judd, 2012. "Constrained Optimization Approaches to Estimation of Structural Models," Econometrica, Econometric Society, vol. 80(5), pages 2213-2230, September.
    8. Fedor Iskhakov & Jinhyuk Lee & John Rust & Bertel Schjerning & Kyoungwon Seo, 2016. "Comment on “Constrained Optimization Approaches to Estimation of Structural Models”," Econometrica, Econometric Society, vol. 84, pages 365-370, January.
    9. Igal Hendel & Aviv Nevo, 2006. "Sales and Consumer Inventory," RAND Journal of Economics, The RAND Corporation, vol. 37(3), pages 543-561, Autumn.
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    Cited by:

    1. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.

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