Identification of Peer Effects using Panel Data

Marisa Miraldo, Carol Propper and Christiern Rose

Papers from arXiv.org

Abstract: We provide new identification results for panel data models with peer effects operating through unobserved individual heterogeneity. The results apply for general network structures governing peer interactions and allow for correlated effects. Identification hinges on a conditional mean restriction requiring exogenous mobility of individuals between groups over time. We apply our method to surgeon-hospital-year data to study take-up of keyhole surgery for cancer, finding a positive effect of the average individual heterogeneity of other surgeons practicing in the same hospital

Date: 2021-08, Revised 2021-09
New Economics Papers: this item is included in nep-isf, nep-net and nep-ure
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http://arxiv.org/pdf/2108.11545 Latest version (application/pdf)

Related works:
Working Paper: Identification of Peer Effects using Panel Data (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2108.11545

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