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Forecasting inflation with gradual regime shifts and exogenous information


  • Hubrich, Kirstin
  • González, Andrés
  • Teräsvirta, Timo


We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary component and dynamic short-run fluctuations around it. An important feature of our model is that it provides a way of combining the information in the sample and exogenous information about the quantity to be forecast. This makes it possible to form a single model-based inflation forecast that also incorporates the exogenous information. We demonstrate, both theoretically and by simulations, how this is done by using the penalised likelihood for estimating the model parameters. In forecasting inflation, the central bank inflation target, if it exists, is a natural example of such exogenous information. We illustrate the application of our method by an out-of-sample forecasting experiment for euro area and UK inflation. We find that for euro area inflation taking the exogenous information into account improves the forecasting accuracy compared to that of a number of relevant benchmark models but this is not so for the UK. Explanations to these outcomes are discussed. JEL Classification: C22, C52, C53, E31, E47

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  • Hubrich, Kirstin & González, Andrés & Teräsvirta, Timo, 2011. "Forecasting inflation with gradual regime shifts and exogenous information," Working Paper Series 1363, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20111363

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    References listed on IDEAS

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    Cited by:

    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
    2. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    3. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, Elsevier.
    4. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    5. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    6. Tamer Kulaksizoglu, 2016. "Measuring the Turkish core inflation with a shifting mean model," Empirical Economics, Springer, vol. 51(1), pages 57-70, August.
    7. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    8. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    9. Kulaksizoglu, Tamer, 2015. "Measuring the Core Inflation in Turkey with the SM-AR Model," MPRA Paper 62653, University Library of Munich, Germany.

    More about this item


    Nonlinear forecast; nonlinear model; nonlinear trend; penalised likelihood; structural shift; time-varying parameter;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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