Spillover Gridlock: Revisiting Interference in Difference-indifferences

Daniel Lasso-Jaramillo
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Daniel Lasso-Jaramillo: Universidad de los Andes

No 2026-26, Documentos CEDE from Universidad de los Andes, Facultad de Economía, CEDE

Abstract: I decompose the canonical Difference-in-differences (DiD) estimator in presence of spillovers into a weighted average of 2×2 estimators that compare treated and untreated units across different levels of exposure to treatment. Identifying the ATT requires strong homogeneity conditions: that spillover magnitudes and exposure probabilities are both identical across treatment status, conditions unlikely to hold in observational studies. While a common response is to control for researcher-proposed interference structures, such estimators induce a selection bias if misspecified, a serious concern given the complex and unknown nature of interference. I propose instead spill-imputation, which identifies individual treatment and spillover effects under a unit-level parallel trends assumption —weaker than correct specification of the interference structure— and recovers spillover heterogeneity ex-post, in a data-driven way. Monte Carlo simulations show deviations of up to 31.2% for the parametric DiD against at most 0.25% for spill-imputation, with standard errors 42% smaller, reflecting greater estimation efficiency. An application to road paving in Mexico finds positive spillover effects of 19.5% on nearby unpaved plots’ property values, and no heterogeneous effects along the distance to the paved street.

Keywords: Difference-in-differences; Spillovers; Heterogeneity; Semi-parametric estimation; Individual Treatment Effects (search for similar items in EconPapers)
JEL-codes: C01 C13 C14 C33 (search for similar items in EconPapers)
Pages: 48
Date: 2026-05
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Published in Documentos CEDE - Universidad de los Andes

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Persistent link: https://EconPapers.repec.org/RePEc:col:000089:022570

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