Taylor & Francis Group
Browse
ubes_a_1668795_sm6072.zip (6.42 kB)

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

Download (6.42 kB)
Version 3 2021-09-29, 15:53
Version 2 2019-10-25, 19:00
Version 1 2019-09-19, 15:02
dataset
posted on 2021-09-29, 15:53 authored by Martin Huber, Andreas Steinmayr

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.

Funding

Financial support by Deutsche Forschungsgemeinschaft through CRC TRR 190 (project number 280092119) is gratefully acknowledged.

History