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A State Space Approach to Extracting the Signal from Uncertain Data

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  • Alastair Cunningham

    (Bank of England)

  • Jana Eklund

    (Bank of England)

  • Chris Jeffery

    (Bank of England)

  • George Kapetanios

    ()
    (Queen Mary, University of London and Bank of England)

  • Vincent Labhard

    (European Central Bank)

Abstract

Most macroeconomic data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the macroeconomic variable.

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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 637.

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Date of creation: Feb 2009
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Handle: RePEc:qmw:qmwecw:wp637

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Keywords: Real-time data analysis; State space models; Data uncertainty; Data revisions;

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References

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  1. Kevin Lee & Emi Mise & Kalvinder Shields & Tony Garratt, 2005. "Real time Representations of the Output Gap," Money Macro and Finance (MMF) Research Group Conference 2005 26, Money Macro and Finance Research Group.
  2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  3. Richard Harrison & George Kapetanios & Tony Yates, 2004. "Forecasting with measurement errors in dynamic models," Bank of England working papers 237, Bank of England.
  4. Anthony Garratt & Shaun P Vahey, 2005. "UK Real-Time Macro Data Characteristics," Birkbeck Working Papers in Economics and Finance 0502, Birkbeck, Department of Economics, Mathematics & Statistics.
  5. 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.
  6. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
  7. Jan Jacobs & Jan-Egbert Sturm, 2007. "A real-time analysis of the Swiss trade account," Money Macro and Finance (MMF) Research Group Conference 2006 167, Money Macro and Finance Research Group.
  8. George Kapetanios & Tony Yates, 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.
  9. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
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Citations

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Cited by:
  1. 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.
  2. Dean Croushore, 2009. "Commentary on Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 371-382.
  3. Norden, Simon van & Tian, Jing & Jacobs, Jan & Dungey, Mardi, 2012. "On trend-cycle decomposition and data revision," Research Report 12009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  4. Michael P. Clements & Ana Beatriz Galv�o, 2011. "Improving Real-time Estimates of Output Gaps and Inflation Trends with Multiple-vintage Models," Working Papers 678, Queen Mary, University of London, School of Economics and Finance.
  5. Richard G. Anderson & Charles S. Gascon, 2009. "Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 349-370.
  6. Hara, Naoko & Ichiue, Hibiki, 2011. "Real-time analysis on Japan's labor productivity," Journal of the Japanese and International Economies, Elsevier, vol. 25(2), pages 107-130, June.
  7. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
  8. Jan P. A. M. Jacobs & Samad Sarferaz & Jan-Egbert Sturm & Simon van Norden, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.

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