Estimation of Non-Gaussian SVAR Using Tensor Singular Value Decomposition

Alain Guay and Dalibor Stevanovic
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Alain Guay: University of Quebec in Montreal

No 25-03, Working Papers from Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management

Abstract: This paper introduces a tensor singular value decomposition (TSVD) approach for estimating non-Gaussian Structural Vector Autoregressive (SVAR) models. The proposed methodology applies to both complete and partial identification of structural shocks. The estimation procedure relies on third and/or fourth-order cumulants. We establish the asymptotic distribution of the estimator and conduct a simulation study to evaluate its finite-sample performance. The results demonstrate that the estimator is highly competitive in small samples compared to alternative methods under complete identification. In cases of partial identification, the estimator also exhibits very good performance in small samples. To illustrate the practical relevance of the procedure under partial identification, two empirical applications are presented.

Keywords: Non-Gaussian SVAR; tensor decomposition; cumulants (search for similar items in EconPapers)
JEL-codes: C12 C32 C51 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2025-02, Revised 2025-02
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Persistent link: https://EconPapers.repec.org/RePEc:bbh:wpaper:25-03

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