SEQUENTIAL SEARCH WITH ADAPTIVE INTENSITY

Joosung Lee and Daniel Li

International Economic Review, 2022, vol. 63, issue 2, 803-829

Abstract: This article studies sequential search problems, where a searcher chooses search intensity adaptively in each period. We fully characterize the optimal search rule and value, decomposing the intertemporal change of search intensity into the fall‐back value effect and the deadline effect. We show that the optimal search intensity (value) is submodular (supermodular) in fall‐back value and time. It follows that the fall‐back value effect increases when the deadline approaches, and the deadline effect decreases when a searcher's fall‐back value gets higher. We further investigate the connection between search with full and no recall to quantify the value of recall.

Date: 2022
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