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Linear estimation of global average treatment effects

Stefan Faridani, Paul Niehaus

arXiv 28 Sep 2022 · Econometrics · 1 citations (OpenAlex)

arXiv:2209.14181 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study the problem of estimating the average causal effect of treating every member of a population, as opposed to none, using an experiment that treats only some. We consider settings where spillovers have global support and decay slowly with (a generalized notion of) distance. We derive the minimax rate over both estimators and designs, and show that it increases with the spatial rate of spillover decay. Estimators based on OLS regressions like those used to analyze recent large-scale experiments are consistent (though only after de-weighting), achieve the minimax rate when the DGP is linear, and converge faster than IPW-based alternatives when treatment clusters are small, providing one justification for OLS's ubiquity. When the DGP is nonlinear they remain consistent but converge slowly. We further address inference and bandwidth selection. Applied to the cash transfer experiment studied by Egger et al. (2022) these methods yield a 20% larger estimated effect on consumption.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Peter M. Aronow and Cyrus Samii (2017) Estimating average causal effects under general interference, with application to a social network experiment1.00094100%
2Miguel, Edward and Kremer, Michael (2004) Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities1.00063100%
3Michael P. Leung (2025) Cluster-Randomized Trials with Cross-Cluster Interference0.95917688%
4Egger, Dennis and Haushofer, Johannes and Miguel, Edward and Niehaus… (2022) General Equilibrium Effects of Cash Transfers: Experimental Evidence From Kenya self0.9507586%
5Leung, Michael P (2022) Rate-optimal cluster-randomized designs for spatial interference0.93823883%
6Leung, Michael P (2022) Causal Inference Under Approximate Neighborhood Interference0.92843100%
7Sussman, Daniel L. and Airoldi, Edoardo M (2017) Elements of estimation theory for causal effects in the presence of network interference0.84333100%
8Karthik Muralidharan and Paul Niehaus (2017) Experimentation at Scale self0.81142100%
9Muralidharan, Karthik and Niehaus, Paul and Sukhtankar, Sandip (2023) General Equilibrium Effects of (Improving) Public Employment Programs: Experimental Evidence From India self0.81142100%
10Nazgul Jenish and Ingmar R. Prucha (2012) On spatial processes and asymptotic inference under near-epoch dependence0.73732100%

Showing the top 10 of 42 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Evaluating Policy Effects under Network Interference without Network Information: A Transfer Learning Approach0.73732
2Causal inference in network experiments: regression-based analysis and design-based properties0.40511
3Regression Discontinuity Design with Spillovers0.40511
4A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances0.40511
5Decomposition of Spillover Effects Under Misspecification: Pseudo-True Estimands and a Local-Global Extension0.40511
6A Design-Based Approach to Testing and Inference in (Quasi-)Experiments with Spillovers0.40511