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The Fragility of Sparsity

Michal Kolesár, Ulrich K. Müller, Sebastian T. Roelsgaard

arXiv 4 Nov 2023 · Econometrics

arXiv:2311.02299 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We show, using three empirical applications, that linear regression estimates which rely on the assumption of sparsity are fragile in two ways. First, we document that different choices of the regressor matrix that do not impact ordinary least squares (OLS) estimates, such as the choice of baseline category with categorical controls, can move sparsity-based estimates by two standard errors or more. Second, we develop two tests of the sparsity assumption based on comparing sparsity-based estimators with OLS. The tests tend to reject the sparsity assumption in all three applications. Unless the number of regressors is comparable to or exceeds the sample size, OLS yields more robust inference at little efficiency cost.

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41
references
100
in-text mentions
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distinct cited
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11,585
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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
1Belloni, Alexandre, Chernozhukov, Victor, Hansen, Christian B (2014) Inference on Treatment Effects after Selection among High-Dimensional Controls1.000105100%
2Ferrara, Andreas (2022) World War II and Black Economic Progress0.92815580%
3Cattaneo, Matias D., Jansson, Michael, Newey, Whitney K (2018) Inference in Linear Regression Models with Many Covariates and Heteroscedasticity0.92843100%
4Enke, Benjamin (2020) Moral Values and Voting0.87412467%
5Javanmard, Adel, Montanari, Andrea (2014) Confidence Intervals and Hypothesis Testing for High-Dimensional Regression0.84333100%
6Zhang, Cun-Hui, Zhang, Stephanie S (2014) Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models0.84333100%
7Geer, Sara, Bühlmann, Peter, Ritov, Ya'acov, Dezeure, Ruben (2014) On Asymptotically Optimal Confidence Regions and Tests for High-Dimensional Models0.84333100%
8Bondell, Howard D., Reich, Brian J (2009) Simultaneous Factor Selection and Collapsing Levels in ANOVA0.64422100%
9Dobriban, Edgar, Su, Weijie J., Yang, Yachong, Zhang, Zhixiang (2024) Robust Inference Under Heteroskedasticity via the Hadamard Estimator0.64422100%
10Gertheiss, Jan, Tutz, Gerhard (2010) Sparse Modeling of Categorial Explanatory Variables0.64422100%

Showing the top 10 of 41 scored citations.