Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum

Marco Del Negro and Giorgio Primiceri

No 619, Staff Reports from Federal Reserve Bank of New York

Abstract: This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and shows how to correctly apply the procedure of Kim, Shephard, and Chib (1998) to the estimation of VAR, DSGE, factor, and unobserved components models with stochastic volatility. Relative to Primiceri (2005), the main difference in the new algorithm is the ordering of the various Markov Chain Monte Carlo steps, with each individual step remaining the same.

Keywords: Bayesian methods; time-varying volatility (search for similar items in EconPapers)
JEL-codes: C11 C15 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2013
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-ore
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Citations: View citations in EconPapers (14)

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Journal Article: Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum (2015)
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