Estimation of peer effects in endogenous social networks: Control function approach

Ida Johnsson; Hyungsik Roger Moon

doi:10.1162/rest_a_00870

Estimation of peer effects in endogenous social networks: Control function approach

Ida Johnsson, Hyungsik Roger Moon

Department of Economics

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

We propose methods of estimating the linear-in-means model of peer effects in which the peer group, defined by a social network, is endogenous in the outcome equation for peer effects. Endogeneity is due to unobservable individual characteristics that influence both link formation in the network and the outcome of interest. We propose two estimators of the peer effect equation that control for the endogeneity of the social connections using a control function approach. We leave the functional form of the control function unspecified, estimate the model using a sieve semiparametric approach and establish asymptotics of the semiparametric estimator.

Original language	English
Pages (from-to)	328-345
Number of pages	18
Journal	Review of Economics and Statistics
Volume	103
Issue number	2
DOIs	https://doi.org/10.1162/rest_a_00870
Publication status	Published - 2021 May 14

Bibliographical note

Funding Information:
We thank Bryan Graham and three referees for their helpful and valuable comments and suggestions. We are particularly grateful to one of the referees for suggesting the idea that is presented in section V.B. of the paper. We also appreciate the comments and discussions of the participants at the 2015 USC Dornsife INET Conference on Networks, the 2016 North American Summer Meeting of the Econometric Society, the 2016 California Econometrics Conference, the 2017 Asian Meeting of Econometric Society, the 2017 IAAE conference, the 2018 UCLA-USC Mini Conference, and the econometrics seminars at University of British Columbia and Ohio State University. The first draft of the paper was written while I.J. was a graduate fellow of USC Dornsife INET and H.R.M. was the associate director of USC Dornsife INET. H.R.M. acknowledges that this work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5A2A01023679).

Publisher Copyright:
© 2019 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

All Science Journal Classification (ASJC) codes

Social Sciences (miscellaneous)
Economics and Econometrics

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abstract = "We propose methods of estimating the linear-in-means model of peer effects in which the peer group, defined by a social network, is endogenous in the outcome equation for peer effects. Endogeneity is due to unobservable individual characteristics that influence both link formation in the network and the outcome of interest. We propose two estimators of the peer effect equation that control for the endogeneity of the social connections using a control function approach. We leave the functional form of the control function unspecified, estimate the model using a sieve semiparametric approach and establish asymptotics of the semiparametric estimator.",

author = "Ida Johnsson and Moon, {Hyungsik Roger}",

note = "Funding Information: We thank Bryan Graham and three referees for their helpful and valuable comments and suggestions. We are particularly grateful to one of the referees for suggesting the idea that is presented in section V.B. of the paper. We also appreciate the comments and discussions of the participants at the 2015 USC Dornsife INET Conference on Networks, the 2016 North American Summer Meeting of the Econometric Society, the 2016 California Econometrics Conference, the 2017 Asian Meeting of Econometric Society, the 2017 IAAE conference, the 2018 UCLA-USC Mini Conference, and the econometrics seminars at University of British Columbia and Ohio State University. The first draft of the paper was written while I.J. was a graduate fellow of USC Dornsife INET and H.R.M. was the associate director of USC Dornsife INET. H.R.M. acknowledges that this work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5A2A01023679). Publisher Copyright: {\textcopyright} 2019 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.",

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Estimation of peer effects in endogenous social networks: Control function approach

Abstract

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