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Erik Brynjolfsson. Rock, Daniel Ian Sloan School of Management. Sloan School of Management 2016-10-25T19:52:40Z 2016-10-25T19:52:40Z 2016 2016 http://hdl.handle.net/1721.1/105074 960700336 Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 20-22). After product adoption, consumers make decisions about continued use. These choices can be influenced by peer decisions in networks, but identifying causal peer influence effects is challenging. Correlations in peer behavior may be driven by correlated effects, exogenous consumer and peer characteristics, or endogenous peer effects of behavior (Manski 1993). Extending the work of Bramoullé et al. (2009), we apply proofs of peer effect identification in networks under a set of exogeneity assumptions to the panel data case. With engagement data for Yahoo Go, a mobile application, we use the network topology of application users in an instrumental variables setup to estimate usage peer effects, comparing the performance of a variety of regression models. We find analyses of this type may be especially useful for ruling out endogenous peer effects as a driver of behavior. Omitted variables (especially ones related to network homophily) and violation of the exogeneity assumptions can bias regression coefficients toward finding statistically significant peer effects. by Daniel Ian Rock. S.M. in Management Research 23 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Sloan School of Management. Estimating peer effects in networked panel data Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ac429f71-e7d5-45fa-87a0-b02ec51063ff"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Estimating peer effects in networked panel data</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <Authors> <Author> <DisplayName>Rock, Daniel Ian</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Sloan School of Management.</Keyword> <Abstract>After product adoption, consumers make decisions about continued use. These choices can be influenced by peer decisions in networks, but identifying causal peer influence effects is challenging. Correlations in peer behavior may be driven by correlated effects, exogenous consumer and peer characteristics, or endogenous peer effects of behavior (Manski 1993). Extending the work of Bramoullé et al. (2009), we apply proofs of peer effect identification in networks under a set of exogeneity assumptions to the panel data case. With engagement data for Yahoo Go, a mobile application, we use the network topology of application users in an instrumental variables setup to estimate usage peer effects, comparing the performance of a variety of regression models. We find analyses of this type may be especially useful for ruling out endogenous peer effects as a driver of behavior. Omitted variables (especially ones related to network homophily) and violation of the exogeneity assumptions can bias regression coefficients toward finding statistically significant peer effects.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>