Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach

Fuente: arXiv
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Autores principales: Hecq, Alain, Ricardo, Ivan, Wilms, Ines
Formato: Preprint
Publicado: 2024
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author Hecq, Alain
Ricardo, Ivan
Wilms, Ines
author_facet Hecq, Alain
Ricardo, Ivan
Wilms, Ines
contents Reduced-rank regressions are powerful tools used to identify co-movements within economic time series. However, this task becomes challenging when we observe matrix-valued time series, where each dimension may have a different co-movement structure. We propose reduced-rank regressions with a tensor structure for the coefficient matrix to provide new insights into co-movements within and between the dimensions of matrix-valued time series. Moreover, we relate the co-movement structures to two commonly used reduced-rank models, namely the serial correlation common feature and the index model. Two empirical applications involving U.S.\ states and economic indicators for the Eurozone and North American countries illustrate how our new tools identify co-movements.
format Preprint
id arxiv_https___arxiv_org_abs_2407_07973
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach
Hecq, Alain
Ricardo, Ivan
Wilms, Ines
Econometrics
Methodology
Reduced-rank regressions are powerful tools used to identify co-movements within economic time series. However, this task becomes challenging when we observe matrix-valued time series, where each dimension may have a different co-movement structure. We propose reduced-rank regressions with a tensor structure for the coefficient matrix to provide new insights into co-movements within and between the dimensions of matrix-valued time series. Moreover, we relate the co-movement structures to two commonly used reduced-rank models, namely the serial correlation common feature and the index model. Two empirical applications involving U.S.\ states and economic indicators for the Eurozone and North American countries illustrate how our new tools identify co-movements.
title Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach
topic Econometrics
Methodology
url https://arxiv.org/abs/2407.07973