Many economic variables are characterized by changes in their conditional mean and
volatility, and time-varying Vector Autoregressive Models are often used to handle such
complexity. Unfortunately, as the number of series grows, they present increasing estimation
and interpretation issues. This paper tries to address this problem by proposing a
Multivariate Autoregressive Index model that features time-varying mean and volatility.
Technically, we develop a new estimation methodology that mixes switching algorithms with …