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Forecasting inflation with an uncertain output gap

Author

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  • Hilde C. Bjørnland

    (University of Oslo and Norges Bank (Central Bank of Norway))

  • Leif Brubakk

    (Norges Bank (Central Bank of Norway))

  • Anne Sofie Jore

    (Norges Bank (Central Bank of Norway))

Abstract

The output gap (measuring the deviation of output from its potential) is a crucial concept in the monetary policy framework, indicating demand pressure that generates inflation. The output gap is also an important variable in itself, as a measure of economic fluctuations. However, its definition and estimation raise a number of theoretical and empirical questions. This paper evaluates a series of univariate and multivariate methods for extracting the output gap, and compares their value added in predicting inflation. The multivariate measures of the output gap have by far the best predictive power. This is in particular interesting, as they use information from data that are not revised in real time. We therefore compare the predictive power of alternative indicators that are less revised in real time, such as the unemployment rate and other business cycle indicators. Some of the alternative indicators do as well, or better, than the multivariate output gaps in predicting inflation. As uncertainties are particularly pronounced at the end of the calculation periods, assessment of pressures in the economy based on the uncertain output gap could benefit from being supplemented with alternative indicators that are less revised in real time.

Suggested Citation

  • Hilde C. Bjørnland & Leif Brubakk & Anne Sofie Jore, 2006. "Forecasting inflation with an uncertain output gap," Working Paper 2006/02, Norges Bank.
  • Handle: RePEc:bno:worpap:2006_02
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    3. Samir Ben Ali, 2013. "Estimating The New Keynesian Phillips Curve For Tunisia: Empirical Issues," Middle East Development Journal (MEDJ), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 1-17.
    4. Mahmood-ul-Hasan Khan, 2008. "Short Run Effects of an Unanticipated Change in Monetary Policy: Interpreting Macroeconomic Dynamics in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 4, pages 1-30.
    5. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2023. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability, Cyclical Sensitivity and Hysteresis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 238-267, February.
    6. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    7. Houda Ben Hadj Boubaker, 2011. "Inflation Forecast-Based Rule for Inflation Targeting: Case of Some Selected MENA Countries," Working Papers 628, Economic Research Forum, revised 09 Jan 2011.
    8. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2020. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability and Cyclical Sensitivity," Working Paper 2020/7, Norges Bank.
    9. Gian Luigi Mazzi & Frédéric Reynès & Matthieu Lemoine & Paola Veroni, 2008. "Real Time Estimation of Potential Output and Output Gap for the Euro-Area : Comparing Production Function with Unobserved Components and SVAR Approaches," SciencePo Working papers Main hal-01027422, HAL.
    10. S. Adnan H. A. S. Bukhari & Safdar Ullah Khan, 2008. "Estimating Output Gap for Pakistan Economy: Structural and Statistical Approaches," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 4, pages 31-60.
    11. Mamdouh Abdelmoula M. ABDELSALAM, 2017. "Improving Phillips Curve’s Inflation Forecasts under Misspecification," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 54-76, September.
    12. Ben Ali, Samir, 2010. "A New Keynesian Phillips curve for Tunisia : Estimation and analysis of sensitivity," MPRA Paper 29624, University Library of Munich, Germany.
    13. Ashima Goyal & Sanchit Arora, 2012. "Deriving India's Potential growth from theory and structure," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-018, Indira Gandhi Institute of Development Research, Mumbai, India.
    14. Carlos Hamilton Vasconcelos Araujo & Osmani Teixeira de Carvalho Guillén, 2008. "Previsão de inflação com incerteza do hiato do produto no Brasil," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211138520, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
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    More about this item

    Keywords

    Output gap; real time indicators; forecasting; Phillips curve;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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