Limit of the optimal weight in least squares model averaging with non-nested models

Fang Fang and Minhan Liu

Economics Letters, 2020, vol. 196, issue C

Abstract: Recently, there has been increasing interest in the asymptotic limits of the optimal weight and the model averaging estimator within frequentist paradigm. Most existing literatures assume the candidate models are nested in such studies and the extension to non-nested models are not trivial. In the paper, we derive the asymptotic limit of the optimal weight in least squares model averaging when the candidate models are non-nested and could be all under-fitted. This result provides more insights into least squares model averaging and a new technique for future studies.

Keywords: Asymptotic limit; Frequentist model averaging; Linear models; Mallows model averaging; Non-nested models (search for similar items in EconPapers)
JEL-codes: C1 C5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:196:y:2020:i:c:s0165176520303530

DOI: 10.1016/j.econlet.2020.109586

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