Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference Author(s) James G. MacKinnon Morten Ø. Nielsen Matthew D. Webb Read more about Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference
Better Off or More Apart? Empirically Testing Welfare and Inequality Dominance Criteria Author(s) Charles Beach Read more about Better Off or More Apart? Empirically Testing Welfare and Inequality Dominance Criteria
Leverage, Influence, and the Jackknife in Clustered Regression Models: Reliable Inference Using summclust Author(s) James G. MacKinnon Morten Ø. Nielsen Matthew D. Webb Read more about Leverage, Influence, and the Jackknife in Clustered Regression Models: Reliable Inference Using summclust
Using Large Samples in Econometrics Author(s) James G. MacKinnon Read more about Using Large Samples in Econometrics
A Nifty Fix for Published Distribution Statistics: Simplified Distribution-Free Statistical Inference Author(s) Charles Beach Read more about A Nifty Fix for Published Distribution Statistics: Simplified Distribution-Free Statistical Inference
A Useful Empirical Tool Box for Distributional Analysis Author(s) Charles Beach Read more about A Useful Empirical Tool Box for Distributional Analysis
Fast cluster bootstrap methods for linear regression models Author(s) James G. MacKinnon Read more about Fast cluster bootstrap methods for linear regression models
Cluster-Robust Inference: A Guide to Empirical Practice Author(s) James G. MacKinnon Morten Ø. Nielsen Matthew D. Webb Read more about Cluster-Robust Inference: A Guide to Empirical Practice
Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order Author(s) Samuel Brien Michael Jansson Morten Ø. Nielsen Read more about Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order
Wild Bootstrap Randomization Inference For Few Treated Clusters Author(s) James G. MacKinnon Matthew D. Webb Read more about Wild Bootstrap Randomization Inference For Few Treated Clusters