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Time-varying structural vector autoregressions and monetary policy: a corrigendum

  • Marco Del Negro
  • Giorgio E. Primiceri

This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and proposes a new algorithm that correctly applies the procedure proposed by Kim, Shephard, and Chib (1998) to the estimation of VAR or DSGE models with stochastic volatility. Relative to Primiceri (2005), the correct algorithm involves a different ordering of the various Markov Chain Monte Carlo steps.

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Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 619.

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Date of creation: 2013
Date of revision:
Handle: RePEc:fip:fednsr:619
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  1. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
  2. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-89, October.
  3. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, 01.
  4. Vasco Cúrdia & Marco Del Negro & Daniel L. Greenwald, 2013. "Rare shocks, Great Recessions," Working Paper Series 2013-01, Federal Reserve Bank of San Francisco.
  5. Fabio Canova & Luca Gambetti, 2003. "Structural changes in the US economy: is there a role for monetary policy?," Economics Working Papers 918, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2008.
  6. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-17, October.
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