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Real-time Data for Norway: Challenges for Monetary Policy

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  • Bernhardsen, Tom
  • Eitrheim, Øyvind
  • Jore, Anne Sofie
  • Røisland, Øistein

Abstract

National accounts data are always revised. Not only recent data, but also figures dating many years back can be revised substantially. This means that there is a danger that an important part of the central bank's information set is flawed for a long period of time. In this paper we present a data base consisting of various vintages of real-time data from 1993Q1 to 2003Q4. We describe the nature of the data revisions, the causes of the revisions, and investigate whether the revisions are true martingale differences, or whether they can be forecasted. In the spirit of Orphanides and van Norden (2002), we analyze how data revisions and model uncertainty affect the reliability of output gap estimates. We also compare Taylor type interest rate rules based on real-time data versus final data and assess the consequences for monetary policy if policy was conducted using this type of interest rate rules. Finally, we analyze the implications of output gap uncertainty for monetary policy using a small New Keynesian macroeconomic model.

Suggested Citation

  • Bernhardsen, Tom & Eitrheim, Øyvind & Jore, Anne Sofie & Røisland, Øistein, 2004. "Real-time Data for Norway: Challenges for Monetary Policy," Discussion Paper Series 1: Economic Studies 2004,26, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdp1:2292
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    Cited by:

    1. Chiu, Adrian & Wieladek, Tomasz, 2012. "Did output gap measurement improve over time?," Discussion Papers 36, Monetary Policy Committee Unit, Bank of England.
    2. George Kapetanios & Tony Yates, 2010. "Estimating time variation in measurement error from data revisions: an application to backcasting and forecasting in dynamic models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 869-893.
    3. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    4. Ince, Onur & Papell, David H., 2013. "The (un)reliability of real-time output gap estimates with revised data," Economic Modelling, Elsevier, vol. 33(C), pages 713-721.
    5. Adriana Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization and Monetary Policy Institute Working Paper 96, Federal Reserve Bank of Dallas.
    6. Felipe Morandé & Mauricio Tejada, 2009. "Sources of Uncertainty in Conducting Monetary Policy in Chile," Central Banking, Analysis, and Economic Policies Book Series,in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.), Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 12, pages 451-509 Central Bank of Chile.
    7. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    8. Muhammad Mahmud & Gobind M. Herani & Prof. A. W. Rajar, 2009. "Economic Factors Influencing Corporate Capital Structure in Three Asian Countries: Evidence from Japan, Malaysia and Pakistan," Indus Journal of Management & Social Science (IJMSS), Department of Business Administration, vol. 3(1), pages 9-17, June.
    9. Rochelle M. Edge & Jeremy B. Rudd, 2016. "Real-Time Properties of the Federal Reserve's Output Gap," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 785-791, October.
    10. Hilde Bjørnland & Leif Brubakk & Anne Jore, 2008. "Forecasting inflation with an uncertain output gap," Empirical Economics, Springer, vol. 35(3), pages 413-436, November.
    11. Tom Bernhardsen & ØYvind Eitrheim, 2005. "Real-time data for Norway: Output gap revisions and challenges for monetary policy," Computing in Economics and Finance 2005 274, Society for Computational Economics.
    12. Julien Champagne & Guillaume Poulin-Bellisle & Rodrigo Sekkel, 2016. "The Real-Time Properties of the Bank of Canada’s Staff Output Gap Estimates," Staff Working Papers 16-28, Bank of Canada.
    13. Christopher Adam & David Cobham, 2009. "Using Real-Time Output Gaps To Examine Past And Future Policy Choices," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 98-110, October.
    14. Bernhardsen, Tom & Eitrheim, Oyvind & Jore, Anne Sofie & Roisland, Oistein, 2005. "Real-time data for Norway: Challenges for monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 333-349, December.
    15. Gerberding, Christina & Seitz, Franz & Worms, Andreas, 2007. "Money-based interest rate rules: lessons from German data," Discussion Paper Series 1: Economic Studies 2007,06, Deutsche Bundesbank.
    16. Felipe Morandé & Mauricio Tejada, 2008. "Sources of Uncertainty for Conducting Monetary Policy in Chile," Working Papers Central Bank of Chile 492, Central Bank of Chile.
    17. Rafael Cusinato & André Minella & Sabino Silva Pôrto Júnior, 2013. "Output gap in Brazil: a real-time data analysis," Empirical Economics, Springer, vol. 44(3), pages 1113-1127, June.

    More about this item

    Keywords

    Monetary policy; output gap; real-time data; interest rate rules;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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