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A Framework for Separating Individual-Level Treatment Effects From Spillover Effects

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  • Martin Huber
  • Andreas Steinmayr

Abstract

This article suggests a causal framework for separating individual-level treatment effects and spillover effects such as general equilibrium, interference, or interaction effects related to treatment distribution. We relax the stable unit treatment value assumption assuming away treatment-dependent interaction between study participants and permit spillover effects within aggregates, for example, regions. Based on our framework, we systematically categorize the individual-level and spillover effects considered in the previous literature and clarify the assumptions required for identification under different designs, for instance, based on randomization or selection on observables. Furthermore, we propose a novel difference-in-differences approach and apply it to a policy intervention extending unemployment benefit durations in selected regions of Austria that arguably affected ineligibles in treated regions through general equilibrium effects in local labor markets.

Suggested Citation

  • Martin Huber & Andreas Steinmayr, 2021. "A Framework for Separating Individual-Level Treatment Effects From Spillover Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 422-436, March.
  • Handle: RePEc:taf:jnlbes:v:39:y:2021:i:2:p:422-436
    DOI: 10.1080/07350015.2019.1668795
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