Principal component analysis for a mix of stationary and nonstationary variables

Journal of Econometrics 2026 Open access

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Authors: James D. Hamilton, Xinwei Ma, Jin Xi
DOI: 10.1016/j.jeconom.2026.106317
Cited by: 0
References: 27

Abstract

This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which variables are nonstationary or the nature of the nonstationarity. An application to the FRED-MD macroeconomic dataset demonstrates that the approach offers similar benefits to those of traditional principal component analysis with some added advantages.

Fields of Study & Subjects

Monetary Policy and Economic Impact Statistical Methods and Applications Statistical and numerical algorithms

Publication details

Journal / source
Journal of Econometrics
Publisher
Elsevier BV
Volume
258
Pages
106317–106317
Publication date
4 September 2026
Language
EN