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Unifying Design-based Inference: On Bounding and Estimating the Variance of any Linear Estimator in any Experimental Design

Joel A. Middleton

arXiv 19 Sep 2021 · Statistics — Methodology · 1 citations (OpenAlex)

arXiv:2109.09220 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper provides a design-based framework for variance (bound) estimation in experimental analysis. Results are applicable to virtually any combination of experimental design, linear estimator (e.g., difference-in-means, OLS, WLS) and variance bound, allowing for unified treatment and a basis for systematic study and comparison of designs using matrix spectral analysis. A proposed variance estimator reproduces Eicker-Huber-White (aka. "robust", "heteroskedastic consistent", "sandwich", "White", "Huber-White", "HC", etc.) standard errors and "cluster-robust" standard errors as special cases. While past work has shown algebraic equivalences between design-based and the so-called "robust" standard errors under some designs, this paper motivates them for a wide array of design-estimator-bound triplets. In so doing, it provides a clearer and more general motivation for variance estimators.

Citation extraction

33
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distinct cited
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appendix boundary found by appendix_titled_section at “Supplementary Proofs” · 100% 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
1Holland, P.W (1986) Statistics and Causal Inference0.64422100%
Aronow and Samiiunmatched citation key Aronow and Samii0.51121100%
Freedmanunmatched citation key Freedman0.51121100%
Middletonunmatched citation key Middleton0.51121100%
Arceneaux and Nickersonunmatched citation key Arceneaux and Nickerson0.40511100%
Aronow and Middletonunmatched citation key Aronow and Middleton0.40511100%
Athey and Imbensunmatched citation key Athey and Imbens0.40511100%
Basse and Fellerunmatched citation key Basse and Feller0.40511100%
Bloniarz et al.unmatched citation key Bloniarz et al.0.40511100%
Campbell and Meyerunmatched citation key Campbell and Meyer0.40511100%

Showing the top 10 of 35 scored citations. 9 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

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

Citing paperIntensityMentionsSections
1Design-based Estimation Theory for Complex Experiments0.874112