2 citations · 2 across the 3 of their papers we have counts for
4 papers
Impulse Response Inference for Matrix Autoregressions
Alain Hecq, Ivan Ricardo, Ines Wilms
Matrix autoregressive (MAR) models offer a parsimonious framework for modeling matrix-valued time series, yet tools for estimation and inference for their impulse response function…
Decomposing Co-Movements in Matrix-Valued Time Series: A Pseudo-Structural Reduced-Rank Approach
Alain Hecq, Ivan Ricardo, Ines Wilms
A pseudo-structural framework is proposed for analyzing contemporaneous co-movements in stationary reduced-rank matrix autoregressive (RRMAR) models. Unlike conventional vector aut…
Detecting Cointegrating Relations in Non-stationary Matrix-Valued Time Series
Alain Hecq, Ivan Ricardo, Ines Wilms
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 row…
Reduced-Rank Matrix Autoregressive Models: A Medium Approach
Alain Hecq, Ivan Ricardo, Ines Wilms
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 ser…