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Assessing the transmission of monetary policy using dynamic factor models

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  • Korobilis, Dimitris

Abstract

This paper extends the current literature which questions the stability of the monetary transmission mechanism, by proposing a factor-augmented vector autoregressive (VAR) model with time-varying coefficients and stochastic volatility. The VAR coefficients and error covariances may change gradually in every period or be subject to abrupt breaks. The model is applied to 143 post-World War II quarterly variables fully describing the US economy. I show that both endogenous and exogenous shocks to the US economy resulted in the high inflation volatility during the 1970s and early 1980s. The time-varying factor augmented VAR produces impulse responses of inflation which significantly reduce the price puzzle. Impulse responses of other indicators of the economy show that the most notable changes in the transmission of unanticipated monetary policy shocks occurred for GDP, investment, exchange rates and money.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 27593.

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Date of creation: May 2009
Date of revision: Nov 2010
Handle: RePEc:pra:mprapa:27593

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Keywords: Structural FAVAR; time varying parameter model; monetary policy;

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Citations

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Cited by:
  1. Kemal Bagzibagli, 2012. "Monetary Transmission Mechanism and Time Variation in the Euro Area," Discussion Papers, Department of Economics, University of Birmingham 12-12, Department of Economics, University of Birmingham.
  2. Eickmeier, Sandra & Lemke, Wolfgang & Marcellino, Massimiliano, 2011. "Classical time-varying FAVAR models - estimation, forecasting and structural analysis," Discussion Paper Series 1: Economic Studies 2011,04, Deutsche Bundesbank, Research Centre.
  3. Koop, Gary & Korobilis, Dimitris, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," MPRA Paper 20125, University Library of Munich, Germany.
  4. Miguel Belmonte & Gary Koop, 2013. "Model Switching and Model Averaging in Time-Varying Parameter Regression Models," Working Papers, University of Strathclyde Business School, Department of Economics 1302, University of Strathclyde Business School, Department of Economics.
  5. Christiane Baumeister & Philip Liu & Haroon Mumtaz, 2012. "Changes in the Effects of Monetary Policy on Disaggregate Price Dynamics," Working Papers, Bank of Canada 12-13, Bank of Canada.
  6. Korobilis, Dimitris & Gilmartin, Michelle, 2010. "The dynamic effects of U.S. monetary policy on state unemployment," MPRA Paper 27596, University Library of Munich, Germany.
  7. Marcellino, Massimiliano & Porqueddu, Mario & Venditti, Fabrizio, 2013. "Short-term GDP forecasting with a mixed frequency dynamic factor model with stochastic volatility," CEPR Discussion Papers, C.E.P.R. Discussion Papers 9334, C.E.P.R. Discussion Papers.
  8. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics, Australian National University, College of Business and Economics, School of Economics 2013-604, Australian National University, College of Business and Economics, School of Economics.
  9. Huang, Y-F., 2012. "Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach," MPRA Paper 41933, University Library of Munich, Germany.
  10. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," IMES Discussion Paper Series 11-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
  11. Andrew Stuart Duncan & Alain Kabundi, 2011. "Global Financial Crises and Time-varying Volatility Comovement in World Equity Markets," Working Papers 253, Economic Research Southern Africa.

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