CLT for Largest Eigenvalues and Unit Root Tests for High-Dimensional Nonstationary Time Series

Bo Zhang (), Guangming Pan () and Jiti Gao

No 11/16, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper first considers some testing issues for a vector of high-dimensional time series before it establishes a joint distribution for the largest eigenvalues of the corresponding co-variance matrix associated with the high-dimensional time series for the case where both the dimensionality of the time series and the length of time series go to infinity. As an application, a new unit root test for a vector of high-dimensional time series is proposed and then studied both theoretically and numerically to show that existing unit tests for the fixed-dimensional case are not applicable

Keywords: asymptotic normality; largest eigenvalue; linear process; unit root test (search for similar items in EconPapers)
JEL-codes: C21 C32 (search for similar items in EconPapers)
Pages: 40
Date: 2016
New Economics Papers: this item is included in nep-ecm and nep-ets
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