VAR Models with an Index Structure: A Survey with New Results

Gianluca Cubadda

Econometrics, 2025, vol. 13, issue 4, 1-17

Abstract: The main aim of this paper is to review recent advances in the multivariate autoregressive index model [MAI] and their applications to economic and financial time series. MAI has recently gained momentum because it can be seen as a link between two popular but distinct multivariate time series approaches: vector autoregressive modeling [VAR] and the dynamic factor model [DFM]. Indeed, on the one hand, MAI is a VAR model with a peculiar reduced-rank structure that can lead to a significant dimension reduction; on the other hand, it allows for the identification of common components and common shocks in a similar way as the DFM. Our focus is on recent developments of the MAI, which include extending the original model with individual autoregressive structures, stochastic volatility, time-varying parameters, high-dimensionality, and co-integration. In addition, some gaps in the literature are filled by providing new results on the representation theory underlying previous contributions, and a novel model is provided.

Keywords: multivariate autoregressive index models; vector autoregressive models; dynamic factor models; reduced-rank regression (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2025
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Related works:
Working Paper: VAR models with an index structure: A survey with new results (2025)
Working Paper: VAR Models With An Index Structure: A Survey With New Results (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:13:y:2025:i:4:p:40-:d:1777016

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