Identification and estimation of spillover effects in randomized experiments

Gonzalo Vazquez-Bare

Journal of Econometrics, 2023, vol. 237, issue 1

Abstract: I study identification, estimation and inference for spillover effects in experiments where units’ outcomes may depend on the treatment assignments of other units within a group. I show that the commonly-used reduced-form linear-in-means regression identifies a weighted sum of spillover effects with some negative weights, and that the difference in means between treated and controls identifies a combination of direct and spillover effects entering with different signs. I propose nonparametric estimators for average direct and spillover effects that overcome these issues and are consistent and asymptotically normal under a precise relationship between the number of parameters of interest, the total sample size and the treatment assignment mechanism. These findings are illustrated using data from a conditional cash transfer program and with simulations. The empirical results reveal the potential pitfalls of failing to flexibly account for spillover effects in policy evaluation: the estimated difference in means and the reduced-form linear-in-means coefficients are all close to zero and statistically insignificant, whereas the nonparametric estimators I propose reveal large, nonlinear and significant spillover effects.

Keywords: Spillover effects; Treatment effects; Causal inference; Interference (search for similar items in EconPapers)
JEL-codes: C10 C13 C14 C90 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:237:y:2023:i:1:s0304407621003067

DOI: 10.1016/j.jeconom.2021.10.014

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