Cotrending: Testing for common deterministic trends in varying means model

Dueker MC, Pipiras V, Sundararajan R (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Journal of Multivariate Analysis Elsevier

Book Volume: 187

Article Number: 104825

DOI: 10.1016/j.jmva.2021.104825

Abstract

In a varying means model, the temporary evolution of a p-vector system is determined by p deterministic nonparametric functions superimposed by error terms, possibly dependent cross sectionally. The basic interest is in linear combinations across the p dimensions that make the deterministic functions constant over time. The number of such linearly independent linear combinations is referred to as a cotrending dimension, and their spanned space as a cotrending space. This work puts forward a framework to test statistically for cotrending dimension and space. Connections to principal component analysis and cointegration are also considered. Finally, a simulation study to assess the finite-sample performance of the proposed tests, and applications to several real data sets are also provided.

Involved external institutions

Ruhr-Universität Bochum (RUB) DE Germany (DE) University of North Carolina at Chapel Hill US United States (USA) (US) Southern Methodist University (SMU) US United States (USA) (US)

How to cite

APA:

Dueker, M.-C., Pipiras, V., & Sundararajan, R. (2022). Cotrending: Testing for common deterministic trends in varying means model. Journal of Multivariate Analysis, 187. https://dx.doi.org/10.1016/j.jmva.2021.104825

MLA:

Dueker, Marie-Christine, Vladas Pipiras, and Raanju Sundararajan. "Cotrending: Testing for common deterministic trends in varying means model." Journal of Multivariate Analysis 187 (2022).

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