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Unrequited friendship? How reciprocity mediates adolescent peer effects

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  • Lin, Xu
  • Weinberg, Bruce A.

Abstract

Researchers using directed network data to estimate peer effects must somehow handle unreciprocated nominations. To better understand how peer effects operate and how best to estimate their effects, this paper investigates how the reciprocation of friendship mediates peer effects. We begin by characterizing how reciprocated and unreciprocated friendships compare in terms of the amount of interaction and social distance. We then use a higher order spatial autoregressive (SAR) model to investigate the differential effects of reciprocated friends, unreciprocated friends, and unchosen friends (i.e. an incoming friendship nomination that is not reciprocated) on adolescents' behaviors and outcomes using data from the Add Health study. We find that adolescents experience heterogenous influences from friends, with the greatest effect from reciprocated friends, intermediate effects from unreciprocated friends, and the smallest, but positive effects from unchosen friends. Our results indicate that it is misleading to assign equal weight to all friends or to impose symmetry on unreciprocated friendship nominations, as is often done.

Suggested Citation

  • Lin, Xu & Weinberg, Bruce A., 2014. "Unrequited friendship? How reciprocity mediates adolescent peer effects," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 144-153.
    • Handle: RePEc:eee:regeco:v:48:y:2014:i:c:p:144-153
    DOI: 10.1016/j.regsciurbeco.2014.06.001
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    Cited by:

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    3. Francesca Gioia, 2017. "Peer effects on risk behaviour: the importance of group identity," Experimental Economics, Springer;Economic Science Association, vol. 20(1), pages 100-129, March.
    4. Xu, Dafeng, 2017. "Acculturational homophily," Economics of Education Review, Elsevier, vol. 59(C), pages 29-42.
    5. Presler, Jonathan L., 2022. "You are who you eat with: Academic peer effects from school lunch lines," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 43-58.
    6. Chih‐Sheng Hsieh & Hans van Kippersluis, 2018. "Smoking initiation: Peers and personality," Quantitative Economics, Econometric Society, vol. 9(2), pages 825-863, July.
    7. Tizheng Li & Xiaojuan Kang, 2022. "Variable selection of higher-order partially linear spatial autoregressive model with a diverging number of parameters," Statistical Papers, Springer, vol. 63(1), pages 243-285, February.
    8. Bofei Xiao & Bo Lei & Wei Lan & Bin Guo, 2022. "A blockwise network autoregressive model with application for fraud detection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1043-1065, December.
    9. Han, Xiaoyi & Hsieh, Chih-Sheng & Lee, Lung-fei, 2017. "Estimation and model selection of higher-order spatial autoregressive model: An efficient Bayesian approach," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 97-120.

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    More about this item

    Keywords

    Peer effect; Networks; Spatial autoregressive model; Reciprocity;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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