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
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
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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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