Cluster-robust inference: a guide to empirical practice
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Publication:2682950
DOI10.1016/j.jeconom.2022.04.001OpenAlexW3156042878MaRDI QIDQ2682950
Morten Ørregaard Nielsen, James G. MacKinnon, Matthew D. Webb
Publication date: 1 February 2023
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2205.03285
clustered datarobust inferencewild cluster bootstrapcluster jackknifecluster-robust variance estimator (CRVE)
Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
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Uses Software
Cites Work
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- The wild bootstrap, tamed at last
- A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
- Asymptotic properties of a robust variance matrix estimator for panel data when \(T\) is large
- Inference with dependent data using cluster covariance estimators
- Random group effects and the precision of regression estimates
- Influential observations, high leverage points, and outliers in linear regression
- Asymptotic theory for clustered samples
- Simple and trustworthy cluster-robust GMM inference
- Empirical process results for exchangeable arrays
- Randomization inference for difference-in-differences with few treated clusters
- Difference-in-differences with multiple time periods
- Inference with difference-in-differences revisited
- Asymptotic theory and wild bootstrap inference with clustered errors
- Placebo inference on treatment effects when the number of clusters is small
- t-Statistic Based Correlation and Heterogeneity Robust Inference
- Simulation-Based Tests that Can Use Any Number of Simulations
- Handbook of Spatial Statistics
- Characterizations of an Empirical Influence Function for Detecting Influential Cases in Regression
- Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods
- How Much Should We Trust Differences-In-Differences Estimates?
- Bootstrap tests: how many bootstraps?
- Randomization Tests Under an Approximate Symmetry Assumption
- Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis
- Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results*
- The wild bootstrap for few (treated) clusters
- Causal Inference for Statistics, Social, and Biomedical Sciences
- Robust Inference With Multiway Clustering
- Testing Statistical Hypotheses
- MODEL SELECTION AND INFERENCE: FACTS AND FICTION
- The bootstrap and Edgeworth expansion
- Bootstrap With Cluster‐Dependence in Two or More Dimensions
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