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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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  • 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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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
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Handle: RePEc:boe:boeewp:0450

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

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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 201230, University of Pretoria, Department of Economics.
  2. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
  3. Michael Wickens, 2014. "How Useful are DSGE Macroeconomic Models for Forecasting?," Open Economies Review, Springer, vol. 25(1), pages 171-193, February.

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