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- W3122936966 abstract "The cluster robust variance estimator (CRVE) relies on the of clusters being sufficiently large. Monte Carlo evidence suggests that the rule of 42 is not true for unbalanced clusters. Rejection frequencies are higher for datasets with 50 clusters proportional to U.S. state populations than with 50 balanced clusters. Using critical values based on the wild cluster bootstrap performs much better. However, this procedure fails when a small of clusters is treated. We explain why CRVE t statistics and the wild bootstrap fail in this case, study the effective number of clusters, and simulate placebo laws with dummy variable regressors." @default.
- W3122936966 created "2021-02-01" @default.
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- W3122936966 date "2015-12-01" @default.
- W3122936966 modified "2023-09-27" @default.
- W3122936966 title "Wild Bootstrap Inference For Wildly Different Cluster Sizes" @default.
- W3122936966 hasPublicationYear "2015" @default.
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