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A state space approach to extracting the signal from uncertain data

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  • Alastair Cunningham
  • Jana Eklund
  • Christopher Jeffery
  • George Kapetanios
  • Vincent Labhard

Abstract

Most macroeconomic data are uncertain - they are estimates rather than perfect measures. Use of these uncertain data to form an assessment of current activity can be viewed as a problem of signal extraction. 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 to extracting the signal from uncertain data that takes the experience of past revisions as representative of the uncertainties surrounding the latest published estimates. Specifically, it describes a two-step estimation procedure in which the history of past revisions (real-time data) are first used to estimate the parameters of a measurement equation describing the official published estimates; and these parameters are then imposed in a maximum likelihood estimation of a state space representation of the 'true' profile of the macroeconomic variable.

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Bibliographic Info

Paper provided by Bank of England in its series Bank of England working papers with number 336.

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Date of creation: Nov 2007
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Handle: RePEc:boe:boeewp:336

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  1. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  2. Anthony Garratt & Shaun P Vahey, 2006. "UK Real-Time Macro Data Characteristics," Economic Journal, Royal Economic Society, vol. 116(509), pages F119-F135, 02.
  3. Richard Harrison & George Kapetanios & Tony Yates, 2004. "Forecasting with Measurement Errors in Dynamic Models," Working Papers 521, Queen Mary, University of London, School of Economics and Finance.
  4. 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.
  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. 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.
  7. 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.
  8. 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.
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Cited by:
  1. 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.
  2. 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.
  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. Jan P. A. M. Jacobs & Samad Sarferaz & Jan-Egbert Sturm & Simon van Norden, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
  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. 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.
  8. 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.

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