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Sequential Search with Adaptive Intensity

Lee, J. and Li, D. (2021) 'Sequential Search with Adaptive Intensity.', International Economic Review .

Abstract

This paper 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 inter-temporal 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 identify the connection between search with full and no recall to quantify the value of recall

Item Type:Article
Full text:Publisher-imposed embargo until 25 October 2023.
(AM) Accepted Manuscript
File format - PDF
(370Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1111/iere.12551
Date accepted:10 September 2021
Date deposited:14 September 2021
Date of first online publication:25 October 2021
Date first made open access:25 October 2023

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