Retrospective Search: Exploration and Ambition on Uncharted Terrain

Can Urgun and Leeat Yariv
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Can Urgun: Princeton University
Leeat Yariv: Princeton University, CEPR, NBER

Working Papers from Princeton University. Economics Department.

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, a standard exponential discounter, decides the breadth and length of search. We fully characterize the optimal search policy. The optimal search scope is U-shaped, with the agent searching most ambitiously when approaching a breakthrough or when nearing search termination. A drawdown stopping boundary is optimal, where the agent ceases search whenever current observations fall a constant amount below the maximal achieved alternative. We also show special features that emerge from contracting with a retrospective searcher.

Keywords: Retrospective Search; Drawdown Stopping Boundary; Contracting (search for similar items in EconPapers)
JEL-codes: C61 C73 D25 D83 (search for similar items in EconPapers)
Date: 2021-07
New Economics Papers: this item is included in nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pri:econom:2021-33

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