Detecting Cointegrating Relations in Non-stationary Matrix-Valued Time Series

Alain Hecq, Ivan Ricardo*, Ines Wilms

*Corresponding author for this work

Research output: Working paper / PreprintPreprint

Abstract

This paper proposes a Matrix Error Correction Model to identify cointegration relations in matrix-valued time series. We hereby allow separate cointegrating relations along the rows and columns of the matrix-valued time series and use information criteria to select the cointegration ranks. Through Monte Carlo simulations and a macroeconomic application, we demonstrate that our approach provides a reliable estimation of the number of cointegrating relationships.
Original languageEnglish
PublisherCornell University - arXiv
Number of pages10
DOIs
Publication statusPublished - 2024

Publication series

SeriesarXiv.org
Number2411.05601
ISSN2331-8422

Keywords

  • matrix-valued time series
  • cointegration rank
  • error correction model
  • information criteria

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