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Title: Refining clustered standard errors with few clusters

Citation Type: Miscellaneous

Publication Year: 2020

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Abstract: We introduce efficient formulas that dramatically decrease the computational time of CR2VE and CR3VE, the cluster-robust estimators of standard errors with few clusters, and of the Imbens and Kolesar (2016) degrees of freedom. We also introduce CR3VE-λ, an estimator that is unbiased under more general conditions than CR3VE as it takes cluster unbalancedness into account. We illustrate these refinements by empirical simulations.

Url: https://pure.rug.nl/ws/portalfiles/portal/112981601/2020002_EEF_def.pdf

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Authors: Niccodemi, Gianmaria; Alessie, Rob; Angelini, VIola; Mierau, Jochen; Wansbeek, Thomas

Publisher: University of Groningen

Data Collections: IPUMS CPS

Topics: Population Data Science

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