Model averaging based on leave-subject-out cross-validation

Yan Gao, Xinyu Zhang, Shouyang Wang and Guohua Zou

Journal of Econometrics, 2016, vol. 192, issue 1, 139-151

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.

Keywords: Asymptotic optimality; Leave-subject-out cross-validation; Longitudinal data; Model averaging; Time series (search for similar items in EconPapers)
JEL-codes: C51 C52 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:192:y:2016:i:1:p:139-151

DOI: 10.1016/j.jeconom.2015.07.006

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