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Retrospective Search: Exploration and Ambition on Uncharted Terrain

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  • Yariv, Leeat
  • Urgun, Can

Abstract

We study a model of retrospective search in which an agent—a researcher, an online shopper, or a politician—tracks the value of a product. Discoveries beget discoveries and their observations are correlated over time, which we model using a Brownian motion. The agent decides both how ambitiously, or broadly, to search, and for how long. We fully characterize the optimal search policy and show that it entails constant scope of search and a simple stopping boundary. We also show the special features that emerge from contracting with a retrospective searcher.

Suggested Citation

  • Yariv, Leeat & Urgun, Can, 2020. "Retrospective Search: Exploration and Ambition on Uncharted Terrain," CEPR Discussion Papers 15534, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:15534
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    References listed on IDEAS

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    More about this item

    Keywords

    Retrospective search; Drawdown stopping boundary; Contracting;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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