Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5095594 | Journal of Econometrics | 2016 | 13 Pages |
Abstract
This paper develops a frequentist model averaging method based on the leave-subject-out cross-validation. This method is applicable not only to averaging longitudinal data models, but also to averaging time series models which can have heteroscedastic errors. The resulting model averaging estimators are proved to be asymptotically optimal in the sense of achieving the lowest possible squared errors. Both simulation study and empirical example show the superiority of the proposed estimators over their competitors.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Yan Gao, Xinyu Zhang, Shouyang Wang, Guohua Zou,