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Modeling Multivariate Data Revisions

  • Jan P. A. M. Jacobs
  • Samad Sarferaz
  • Simon van Norden
  • Jan-Egbert Sturm

Data revisions in macroeconomic time series are typically studied in isolation ignoring the joint behaviour of revisions across different series. This ignores (i) the possibility that early releases of some series may help forecast revisions in other series and (ii) the problems statitical agencies may face in producing estimates consistent with accounting identities. This paper extends the Jacobs and van Norden (2011) modeling framework to multivariate data revisions. We consider systems of variables, where true values and news and noise can be correlated, and which may be linked by one or more identities. We show how to model such systems with standard linear state space models. We motivate and illustrate the multivariate modeling framework with Swiss current account data using Bayesian econometric methods for estimation and inference.

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Paper provided by CIRANO in its series CIRANO Working Papers with number 2013s-44.

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Length: 46 pages
Date of creation: 01 Nov 2013
Date of revision:
Handle: RePEc:cir:cirwor:2013s-44
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  1. Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.
  2. de Jong, Piet, 1987. "Rational Economic Data Revisions," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 539-48, October.
  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. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
  5. Jan Jacobs & Jan-Egbert Sturm, 2008. "The Information Content of KOF Indicators on Swiss Current Account Data Revisions," CESifo Working Paper Series 2370, CESifo Group Munich.
  6. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2013. "Improving GDP measurement: a measurement-error perspective," Working Papers 13-16, Federal Reserve Bank of Philadelphia.
  7. Mardi Dungey & Jan PAM Jacobs & Jing Tian & Simon van Norden, 2012. "On the correspondence between data revision and trend-cycle decomposition," CAMA Working Papers 2012-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  8. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP measurement: a forecast combination perspective," Working Papers 11-41, Federal Reserve Bank of Philadelphia.
  9. Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
  10. Richard Stone & D. G. Champernowne & J. E. Meade, 1942. "The Precision of National Income Estimates," Review of Economic Studies, Oxford University Press, vol. 9(2), pages 111-125.
  11. 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.
  12. repec:taf:jnlbes:v:30:y:2012:i:2:p:173-180 is not listed on IDEAS
  13. Alastair Cunningham & Jana Eklund & Christopher Jeffery & George Kapetanios & Vincent Labhard, 2007. "A state space approach to extracting the signal from uncertain data," Bank of England working papers 336, Bank of England.
  14. 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.
  15. repec:taf:jnlbes:v:30:y:2012:i:2:p:181-190 is not listed on IDEAS
  16. Thomas A. Knetsch & Hans-Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real-Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, 04.
  17. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, December.
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