Model Averaging of Integer-Valued Autoregressive Model With Covariates

33 Pages Posted: 18 May 2021 Last revised: 5 Jan 2022

See all articles by Jiajing Sun

Jiajing Sun

Chinese Academy of Sciences (CAS) - School of Economics and Management

Yuying Sun

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science (AMSS)

Xinyu Zhang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Sciences

Brendan McCabe

University of Liverpool - Management School (ULMS)

Date Written: May 15, 2021

Abstract

The integer-valued autoregressive (INAR) process is a class of structural models that can be used to model dependent count data in various fields including medicine, statistics, economics, finance and marketing. This paper proposes a K-fold cross-validation model averaging (KCVMA) method to average predictions from INAR models based on maximum likelihood estimation. The KCVMA method is shown to be asymptotically optimal in the sense of achieving the lowest quadratic loss. The KCVMA estimators are consistent, provided at least one candidate model is not underfitted. Monte Carlo simulations and empirical analysis illustrate the merits of the propose method relative to the existing model averaging and model selection methods

Keywords: Asymptotic optimality; K-fold cross-validation; Integer-valued autoregressive models; Maximum likelihood; Model averaging.

Suggested Citation

Sun, Jiajing and Sun, Yuying and Zhang, Xinyu and McCabe, Brendan, Model Averaging of Integer-Valued Autoregressive Model With Covariates (May 15, 2021). Available at SSRN: https://ssrn.com/abstract=3846927 or http://dx.doi.org/10.2139/ssrn.3846927

Jiajing Sun (Contact Author)

Chinese Academy of Sciences (CAS) - School of Economics and Management ( email )

No.80, Zhongguancun East Road, Haidian District
Beijing
China

Yuying Sun

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Science (AMSS) ( email )

Beijing
China

Xinyu Zhang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Sciences ( email )

Zhong-Guan-Cun-Dong-Lu 55, Haidian District
Beijing, 100080, P.R., Beijing 100080
China

Brendan McCabe

University of Liverpool - Management School (ULMS) ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

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