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Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters

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Author Info

  • Barnett, Alina

    () (Bank of England)

  • Mumtaz, Haroon

    () (Bank of England)

  • Theodoridis, Konstantinos

    () (Bank of England)

Abstract

Evidence from a large and growing empirical literature strongly suggests that there have been changes in inflation and output dynamics in the United Kingdom. This is largely based on a class of econometric models that allow for time-variation in coefficients and volatilities of shocks. While these have been used extensively to study evolving dynamics and for structural analysis, there is little evidence on their usefulness in forecasting UK output growth, inflation and the short-term interest rate. This paper attempts to fill this gap by comparing the performance of a wide variety of time-varying parameter models in forecasting output growth, inflation and a short rate. We find that allowing for time-varying parameters can lead to large and statistically significant gains in forecast accuracy.

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Bibliographic Info

Paper provided by Bank of England in its series Bank of England working papers with number 450.

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Length: 56 pages
Date of creation: 18 May 2012
Date of revision:
Handle: RePEc:boe:boeewp:0450

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Keywords: Time-varying parameters; stochastic volatility; VAR; FAVAR; forecasting; Bayesian estimation;

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References

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  1. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
  2. Jana Eklund & George Kapetanios & Simon Price, 2011. "Forecasting in the presence of recent structural change," CAMA Working Papers 2011-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Groen, Jan J J & Mumtaz, Haroon, 2008. "Investigating the structural stability of the Phillips curve relationship," Bank of England working papers 350, Bank of England.
  4. Kristie M. Engemann & Michael T. Owyang, 2007. "Whatever happened to the business cycle? a Bayesian analysis of jobless recoveries," Working Papers 2007-013, Federal Reserve Bank of St. Louis.
  5. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
  6. 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.
  7. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
  8. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
  9. Christiane Baumeister & Luca Benati, 2010. "Unconventional monetary policy and the great recession - Estimating the impact of a compression in the yield spread at the zero lower bound," Working Paper Series 1258, European Central Bank.
  10. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2010. "Changes in the transmission of monetary policy: evidence from a time-varying factor-augmented VAR," Bank of England working papers 401, Bank of England.
  11. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
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Cited by:
  1. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.

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