3 papers
econ.EM2026
Jackknife inference with two-way clustering
James G. MacKinnon, Morten Ãrregaard Nielsen, Matthew D. Webb
For linear regression models with cross-section or panel data, it is natural to assume that the disturbances are clustered in two dimensions. However, the finite-sample properties…
econ.EM2026
Improved Inference for CSDID Using the Cluster Jackknife
Sunny R. Karim, Morten Ãrregaard Nielsen, James G. MacKinnon +1
Obtaining reliable inferences with traditional difference-in-differences (DiD) methods can be difficult. Problems can arise when both outcomes and errors are serially correlated, w…
econ.EM2025
Cluster-robust jackknife and bootstrap inference for logistic regression models
James G. MacKinnon, Morten Ãrregaard Nielsen, Matthew D. Webb
We study cluster-robust inference for logistic regression (logit) models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unre…