Sequential Search with Adaptive Intensity

Lee, J.; Li, D.

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

Citation

Lee, J., & Li, D. (2022). Sequential Search with Adaptive Intensity. International Economic Review, 63(2), 803-829. https://doi.org/10.1111/iere.12551

• Journal Article Type: Article
• Acceptance Date: Sep 10, 2021
• Online Publication Date: Oct 25, 2021
• Publication Date: 2022-05
• Deposit Date: Sep 13, 2021
• Publicly Available Date: Oct 26, 2023
• Journal: International Economic Review
• Print ISSN: 0020-6598
• Electronic ISSN: 1468-2354
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 63
• Issue: 2
• Pages: 803-829
• DOI: https://doi.org/10.1111/iere.12551
• Public URL: https://durham-repository.worktribe.com/output/1240802