EconBase
← All papers

Inference in Difference-in-Differences with Few Treated Units and Spatial Correlation

Luis Alvarez, Bruno Ferman

arXiv 30 Jun 2020 · Econometrics · 3 citations (OpenAlex)

arXiv:2006.16997 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We consider the problem of inference in Difference-in-Differences (DID) when there are few treated units and errors are spatially correlated. We first show that, when there is a single treated unit, some existing inference methods designed for settings with few treated and many control units remain asymptotically valid when errors are weakly dependent. However, these methods may be invalid with more than one treated unit. We propose alternatives that are asymptotically valid in this setting, even when the relevant distance metric across units is unavailable.

Citation extraction

56
references
91
in-text mentions
56
distinct cited
7
self-citations
10,586
main-text words

appendix boundary found by appendix_command · 67% of the source is main text. Read the extracted text to check this.

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
1Sommers, B. D., Long, S. K., and Baicker, K (2014) Changes in mortality after Massachusetts health care reform0.92810480%
2Benjamini, Y. and Hochberg, Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing0.8746467%
3Ferman, B (2023) Inference in difference-in-differences: How much should we trust in independent clusters? self0.7373367%
4Conley, T. G. and Taber, C. R (2011) Inference with Difference in Differences with a Small Number of Policy Changes0.73732100%
5Ferman, B. and Pinto, C (2019) Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity self0.73732100%
6Chernozhukov, V., Wüthrich, K., and Zhu, Y (2021) An exact and robust conformal inference method for counterfactual and synthetic controls0.64422100%
7Canay, I. A., Romano, J. P., and Shaikh, A. M (2017) Randomization tests under an approximate symmetry assumption0.64422100%
8MacKinnon, J. G. and Webb, M. D (2020) Randomization inference for difference-in-differences with few treated clusters0.64422100%
9Alvarez, L. and Ferman, B (2023) Extensions for inference in difference-in-differences with few treated clusters self0.64422100%
10de Chaisemartin, C. and D'Haultfoeuille, X (2020) Two-way fixed effects estimators with heterogeneous treatment effects0.5113233%

Showing the top 10 of 56 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
1On the relationship between prediction intervals, tests of sharp nulls and inference on realized treatment effects in settings with few treated units0.81142
2ASSESSING INFERENCE METHODS0.40511
3Inference with few treated units0.40511
4Cluster-robust inference with a single treated cluster using the t-test0.40511