Identification of Peer Effects using Panel Data

Marisa Miraldo, Carol Propper and Christiern Rose

No 639, Discussion Papers Series from University of Queensland, School of Economics

Abstract: This paper provides new identification results for panel data models with contextual and endogenous peer effects. Contextual effects operate through individuals’ time-invariant unobserved heterogeneity. Identification hinges on a conditional mean restriction requiring exogenous mobility of individuals between groups over time. Some networks governing peer interactions preclude identification. For these cases we propose additional conditional variance restrictions. We conduct a Monte-Carlo experiment to evaluate the performance of our method and apply it to surgeon-hospital-year data to study take-up of minimally invasive surgery. A standard deviation increase in the average time-invariant unobserved heterogeneity of other surgeons in the same hospital leads to a 0.12 standard deviation increase in take-up. The effect is equally due to endogenous and contextual effects.

Keywords: Peer effects; panel data; networks; identification; innovation; healthcare (search for similar items in EconPapers)
Date: 2020-12-03
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-eff, nep-hea, nep-net and nep-ure
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Working Paper: Identification of Peer Effects using Panel Data (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:qld:uq2004:639

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