Factor augmented VAR revisited - A sparse dynamic factor model approach

Simon Beyeler and Sylvia Kaufmann

No 16.08R, Working Papers from Swiss National Bank, Study Center Gerzensee

Abstract: We combine the factor augmented VAR framework with recently developed estimation and identification procedures for sparse dynamic factor models. Working with a sparse hierarchical prior distribution allows us to discriminate between zero and non-zero factor loadings. The non-zero loadings identify the unobserved factors and provide a meaningful economic interpretation for them. Applying our methodology to US macroeconomic data reveals indeed a high degree of sparsity in the data. We use the estimated FAVAR to study the effect of a monetary policy shock and a shock to the term premium. Factors and specific variables show sensible responses to the identified shocks.

Pages: 55 pages
Date: 2019-03
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Related works:
Working Paper: Factor augmented VAR revisited - A sparse dynamic factor model approach (2018)
Working Paper: Factor augmented VAR revisited - A sparse dynamic factor model approach (2016)
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