Identification in Search Models with Social Information
43 Pages Posted: 7 Dec 2022 Last revised: 12 Dec 2022
Date Written: December 11, 2022
We theoretically study how social information affects agents' search behavior and the resulting observable outcomes that identify search models. We generalize canonical empirical search models by allowing a share of agents in the population to observe some peers' choices. Social information changes optimal search. First, we show that neglecting social information leads to non-identification of search cost distributions under various standard datasets. Whether search costs are under or overestimated depends on the dataset. Next, we propose remedies---such as data requirements, offline estimation techniques, exogenous variations, and partial identification approaches---that restore identification and consistent estimation.
Keywords: Search and Learning, Social Information, Identification, Networks, Robustness.
JEL Classification: C1, C5, C8, D1, D6, D8.
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