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A more general Pandora rule?

Author

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  • Olszewski, Wojciech
  • Weber, Richard

Abstract

In a model introduced by Weitzman an agent called Pandora opens boxes sequentially, in whatever order she likes, discovers prizes within, and optimally stops. Her aim is to maximize the expected value of the greatest discovered prize, minus the costs of opening the boxes. The solution, using the so-called Pandora rule, is attractive and has many applications. However, it does not address applications in which the payoff depends on all discovered prizes, rather than just the best of them, nor is it easy to say whether or not some generalized Pandora rule might do so. Here, we establish a sense in which it cannot. We discover that if a generalized Pandora rule is to be optimal for some more general utility, and all model parameters, then the problem can be solved via a second problem having Weitzman's form of utility.

Suggested Citation

  • Olszewski, Wojciech & Weber, Richard, 2015. "A more general Pandora rule?," Journal of Economic Theory, Elsevier, vol. 160(C), pages 429-437.
  • Handle: RePEc:eee:jetheo:v:160:y:2015:i:c:p:429-437
    DOI: 10.1016/j.jet.2015.10.009
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    Citations

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    Cited by:

    1. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    2. Can Urgun & Leeat Yariv, 2021. "Retrospective Search: Exploration and Ambition on Uncharted Terrain," Working Papers 2021-33, Princeton University. Economics Department..
    3. Yizhaq Minchuk & Aner Sela, 2018. "Asymmetric sequential search under incomplete information," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(2), pages 315-325, June.
    4. Doval, Laura, 2018. "Whether or not to open Pandora's box," Journal of Economic Theory, Elsevier, vol. 175(C), pages 127-158.
    5. Pak Hung Au & Mark Whitmeyer, 2018. "Attraction versus Persuasion: Information Provision in Search Markets," Papers 1802.09396, arXiv.org, revised May 2022.
    6. Robert Kleinberg & Bo Waggoner & E. Glen Weyl, 2016. "Descending Price Optimally Coordinates Search," Papers 1603.07682, arXiv.org, revised Dec 2016.
    7. Murali Agastya & Oleksii Birulin, 2023. "Optimal Task Scheduling under Adverse Selection and Hidden Actions," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 660-698, May.
    8. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Other publications TiSEM ac47e6ff-42a4-4d70-addd-6, Tilburg University, School of Economics and Management.
    9. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    10. Pavan, Alessandro & Fershtman, Daniel, 2020. "Sequential Learning with Endogenous Consideration Sets," CEPR Discussion Papers 15018, C.E.P.R. Discussion Papers.
    11. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Discussion Paper 2019-034, Tilburg University, Center for Economic Research.
    12. Christoph Carnehl & Johannes Schneider, 2021. "On Risk and Time Pressure: When to Think and When to Do," Papers 2111.07451, arXiv.org, revised Mar 2022.
    13. Yariv, Leeat & Urgun, Can, 2020. "Retrospective Search: Exploration and Ambition on Uncharted Terrain," CEPR Discussion Papers 15534, C.E.P.R. Discussion Papers.
    14. Rafael P. Greminger, 2019. "Optimal Search and Discovery," Papers 1911.07773, arXiv.org, revised Feb 2022.
    15. Dellis, Arnaud, 2023. "Legislative informational lobbying," Journal of Economic Theory, Elsevier, vol. 208(C).

    More about this item

    Keywords

    Optimal scheduling and stopping; Weitzman's Pandora rule;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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