Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors

Zhen Peng and Chaohua Dong

Finance Research Letters, 2022, vol. 47, issue PB

Abstract: This paper proposes a class of augmented cointegrating linear (ACL) models that accommodate both stationary and nonstationary variables in a single equation, where regressors may be strongly correlated defined below. Moreover, the limit theory of estimators proposed is established via joint convergence of the sample variance and covariance that eschews some existing drawback in the literature; to facilitate inference, a self-normalized central limit theorem is given as well. Furthermore, numerical simulations confirm the theoretical results, and for the US’s GDP series we show that ACL model outperforms some competing models.

Keywords: Augmented cointegrating linear regression; Joint convergence; Strongly correlated regressors; Unit root process (search for similar items in EconPapers)
JEL-codes: C12 C22 C32 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:47:y:2022:i:pb:s1544612322000885

DOI: 10.1016/j.frl.2022.102775

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