IDEAS home Printed from https://ideas.repec.org/p/qmw/qmwecw/520.html
   My bibliography  Save this paper

Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Forecasting in Dynamic Models

Author

Listed:
  • George Kapetanios

    (Queen Mary, University of London
    Bank of England)

Abstract

Over time, economic statistics are refined. This means that newer data is typically less well measured than old data. Time variation in measurement error like this influences how forecasts should be made. We show how modelling the behaviour of the statistics agency generates both an estimate of this time variation and an estimate of the absolute amount of uncertainty in the data. We apply the method to UK aggregate expenditure data, and illustrate the gains in forecasting from exploiting our model estimates of measurement error.

Suggested Citation

  • George Kapetanios, 2004. "Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Forecasting in Dynamic Models," Working Papers 520, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:520
    as

    Download full text from publisher

    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2004/items/wp520.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nelson, Edward & Nikolov, Kalin, 2003. "UK inflation in the 1970s and 1980s: the role of output gap mismeasurement," Journal of Economics and Business, Elsevier, vol. 55(4), pages 353-370.
    2. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    3. Swanson, Eric T., 2004. "Signal Extraction And Non-Certainty-Equivalence In Optimal Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 8(1), pages 27-50, February.
    4. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    5. Coenen, Gunter & Levin, Andrew & Wieland, Volker, 2005. "Data uncertainty and the role of money as an information variable for monetary policy," European Economic Review, Elsevier, vol. 49(4), pages 975-1006, May.
    6. Aoki, Kosuke, 2003. "On the optimal monetary policy response to noisy indicators," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 501-523, April.
    7. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    8. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    9. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research and International Relations Area.
    10. Egginton, Don M. & Pick, Andreas & Vahey, Shaun P., 2002. "'Keep it real!': a real-time UK macro data set," Economics Letters, Elsevier, vol. 77(1), pages 15-20, September.
    11. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    12. Clark, Todd E, 1996. "Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 367-373, July.
    13. Kamada, Koichiro, 2005. "Real-time estimation of the output gap in Japan and its usefulness for inflation forecasting and policymaking," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 309-332, December.
    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. Howrey, E Philip, 1978. "The Use of Preliminary Data in Econometric Forecasting," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 193-200, May.
    16. Gerberding, Christina & Worms, Andreas & Seitz, Franz, 2004. "How the Bundesbank really conducted monetary policy: An analysis based on real-time data," Discussion Paper Series 1: Economic Studies 2004,25, Deutsche Bundesbank.
    17. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    18. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-287, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal From Uncertain Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 173-180, March.
    2. Alastair Cunningham & Chris Jeffery & George Kapetanios & Vincent Labhard, 2007. "A State Space Approach To The Policymaker's Data Uncertainty Problem," Money Macro and Finance (MMF) Research Group Conference 2006 168, Money Macro and Finance Research Group.
    3. Paul Downward & Andrew Mearman, 2005. "Methodological Triangulation at the Bank of England:An Investigation," Working Papers 0505, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    4. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    5. Lavan Mahadeva & Alex Muscatelli, 2005. "National Accounts Revisions and Output Gap Estimates in a Model of Monetary Policy with Data Uncertainty," Discussion Papers 14, Monetary Policy Committee Unit, Bank of England.
    6. Paul Downward & Andrew Mearman, 2008. "Decision-making at the Bank of England: a critical appraisal," Oxford Economic Papers, Oxford University Press, vol. 60(3), pages 385-409, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. George Kapetanios & Tony Yates, 2004. "Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models," Bank of England working papers 238, 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. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    4. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    5. repec:wrk:wrkemf:11 is not listed on IDEAS
    6. Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
    7. Michael Scharnagl & Christina Gerberding & Franz Seitz, 2010. "Should Monetary Policy Respond to Money Growth? New Results for the Euro Area," International Finance, Wiley Blackwell, vol. 13(3), pages 409-441, December.
    8. Ahsan ul Haq Satti & Wasim Shahid Malik, 2017. "The Unreliability of Output-Gap Estimates in Real Time," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 56(3), pages 193-219.
    9. Xueting Yu & Yuhan Zhu & Guangming Lv, 2020. "Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1251-1274, May.
    10. 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.
    11. 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.
    12. Clements, Michael P. & Beatriz Galvao, Ana, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," Economic Research Papers 270771, University of Warwick - Department of Economics.
    13. 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.
    14. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
    15. Jarkko Jääskelä & Tony Yates, 2005. "Monetary policy and data uncertainty," Bank of England working papers 281, Bank of England.
    16. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    17. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal From Uncertain Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 173-180, March.
    18. Costas Milas & Ruthira Naraidoo, 2009. "Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment," Working Papers 200923, University of Pretoria, Department of Economics.
    19. Givens, Gregory E. & Salemi, Michael K., 2015. "Inferring monetary policy objectives with a partially observed state," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 190-208.
    20. Yu, Xiangrong, 2013. "Measurement error and policy evaluation in the frequency domain," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 307-329.
    21. Hughes Hallett, Andrew & Bernoth, Kerstin & Lewis, John, 2008. "Did Fiscal Policy Makers Know What They Were Doing? Reassessing Fiscal Policy with Real Time Data," CEPR Discussion Papers 6758, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Forecasting; Data revisions;

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qmw:qmwecw:520. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nicholas Owen (email available below). General contact details of provider: https://edirc.repec.org/data/deqmwuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.