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VAR Models With An Index Structure: A Survey With New Results

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Abstract

The main aim of this paper is to review recent advances in the multivariate autoregressive index model [MAI], originally proposed by Reinsel (1983), and their applications to economic and ?nancial 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, the MAI is a VAR model with a peculiar reduced-rank structure; on the other hand, it allows for identi?cation of common components and common shocks in a similar way as the DFM. The 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 cointegration. In addition, new insights on previous contributions and a novel model are also provided.

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  • Gianluca Cubadda, 2025. "VAR Models With An Index Structure: A Survey With New Results," CEIS Research Paper 611, Tor Vergata University, CEIS, revised 22 Sep 2025.
    • Handle: RePEc:rtv:ceisrp:611
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