Identification of treatment response with social interactions

Charles F. Manski*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

79 Scopus citations

Abstract

This paper studies identification of potential outcome distributions when treatment response may have social interactions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when non-parametric shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response is a polar case within the broad class of constant treatment response (CTR) assumptions, the other pole being unrestricted interactions. Important non-polar cases are interactions within reference groups and anonymous interactions. I first study identification under Assumption CTR alone. I then strengthen this Assumption to semi-monotone response. I next discuss derivation of these assumptions from models of endogenous interactions. Finally, I combine Assumption CTR with statistical independence of potential outcomes from realized effective treatments. The findings both extend and delimit the classical analysis of randomized experiments.

Original languageEnglish (US)
Pages (from-to)S1-S23
JournalEconometrics Journal
Volume16
Issue number1
DOIs
StatePublished - Feb 1 2013

Keywords

  • Analysis of treatment response
  • Partial identification
  • social networks

ASJC Scopus subject areas

  • Economics and Econometrics

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