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Modeling Multivariate Data Revisions

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Author Info

  • Jan P. A. M. Jacobs

    ()

  • Samad Sarferaz
  • Jan-Egbert Sturm
  • Simon van Norden

    ()

Abstract

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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Bibliographic Info

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

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Date of creation: 01 Nov 2013
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Handle: RePEc:cir:cirwor:2013s-44

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Keywords: data revisions; state space form; linear constraints; correlated shocks; Bayesian econometrics; current account statistics; Switzerland;

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References

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  1. Jan Jacobs & Jan-Egbert Sturm, 2008. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2008(2), pages 161-181.
  2. 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.
  3. 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.
  4. de Jong, Piet, 1987. "Rational Economic Data Revisions," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 539-48, October.
  5. Dean Croushore, 2008. "Frontiers of real-time data analysis," Working Papers 08-4, Federal Reserve Bank of Philadelphia.
  6. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal from Uncertain Data," Working Papers 637, Queen Mary, University of London, School of Economics and Finance.
  7. 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.
  8. Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
  9. repec:taf:jnlbes:v:30:y:2012:i:2:p:173-180 is not listed on IDEAS
  10. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  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:181-190 is not listed on IDEAS
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