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Classical time-varying FAVAR models - Estimation, forecasting and structural analysis

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  • Eickmeier, Sandra
  • Lemke, Wolfgang
  • Marcellino, Massimiliano

Abstract

We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of US variables from 1972 to 2007, the results indicate some changes in the factor dynamics, and more marked variation in the factors' shock volatility and their loading parameters. Forecasts from the time-varying FAVAR are more accurate than those from a constant parameter FAVAR for most variables and horizons when computed in-sample, and for some variables in pseudo real time, mostly financial and credit variables. Finally, we use the time-varying FAVAR to assess how monetary transmission to the economy has changed. We find substantial time variation in the volatility of monetary policy shocks, and we observe that the reaction of GDP, the GDP deflator, inflation expectations and long-term interest rates to a same-sized monetary policy shock has decreased since the early-1980s.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8321.

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Date of creation: Apr 2011
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Handle: RePEc:cpr:ceprdp:8321

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Keywords: FAVAR; forecasting; monetary transmission; time-varying parameters;

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References

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  1. Korobilis, Dimitris, 2009. "Assessing the transmission of monetary policy using dynamic factor models," MPRA Paper 27593, University Library of Munich, Germany, revised Nov 2010.
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  21. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
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Citations

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Cited by:
  1. Eickmeier, Sandra & Lemke, Wolfgang & Marcellino, Massimiliano, 2011. "The changing international transmission of financial shocks: evidence from a classical time-varying FAVAR," Discussion Paper Series 1: Economic Studies 2011,05, Deutsche Bundesbank, Research Centre.
  2. Prieto, Esteban & Eickmeier, Sandra & Marcellino, Massimiliano, 2013. "Time variation in macro-financial linkages," Discussion Papers 13/2013, Deutsche Bundesbank, Research Centre.
  3. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511.
  4. Eickmeier, Sandra & Ng, Tim, 2011. "How Do Credit Supply Shocks Propagate Internationally? A GVAR approach," CEPR Discussion Papers 8720, C.E.P.R. Discussion Papers.
  5. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
  6. Xu Han & Atsushi Inoue, 2011. "Tests for Parameter Instability in Dynamic Factor Models," TERG Discussion Papers 306, Graduate School of Economics and Management, Tohoku University, revised May 2013.
  7. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.

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