Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5097129 | Journal of Econometrics | 2017 | 24 Pages |
Abstract
I consider the asymptotic properties of a commonly advocated covariance matrix estimator for panel data. Under asymptotics where the cross-section dimension, n, grows large with the time dimension, T, fixed, the estimator is consistent while allowing essentially arbitrary correlation within each individual. However, many panel data sets have a non-negligible time dimension. I extend the usual analysis to cases where n and T go to infinity jointly and where Tââ with n fixed. I provide conditions under which t and F statistics based on the covariance matrix estimator provide valid inference and illustrate the properties of the estimator in a simulation study.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Christian B. Hansen,