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Estimating social effects in a multilayered Linear-in-Means model with network data

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  • Manta, Alexandra
  • Ho, Anson T.Y.
  • Huynh, Kim P.
  • Jacho-Chávez, David T.

Abstract

This paper studies the identification and estimation of social parameters in a general version of the Linear-in-Means model commonly fitted in the Social Sciences with multilayered network data. A Monte Carlo exercise showcases its good small-sample properties while an empirical application to Canadian consumers’ credit usage demonstrates its applicability. Our estimates show that one’s credit-card balance increases by $0.31 for an extra $1 owed by surrounding neighbors.

Suggested Citation

  • Manta, Alexandra & Ho, Anson T.Y. & Huynh, Kim P. & Jacho-Chávez, David T., 2022. "Estimating social effects in a multilayered Linear-in-Means model with network data," Statistics & Probability Letters, Elsevier, vol. 183(C).
    • Handle: RePEc:eee:stapro:v:183:y:2022:i:c:s0167715221002832
    DOI: 10.1016/j.spl.2021.109331
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