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Modeling Multivariate Data Revisions

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  • 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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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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  1. Dungey, Mardi & Jacobs, Jan & Tian, Jing & van Norden, Simon, 2012. "On the correspondence between data revision and trend-cycle decomposition," Working Papers 12975, University of Tasmania, School of Economics and Finance, revised 01 Mar 2012.
  2. 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.
  3. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, September.
  4. Jan P.A.M. Jacobs & Sturm Jan-Egbert, 2008. "The information content of KOF indicators on Swiss current account data revisions," KOF Working papers 08-202, KOF Swiss Economic Institute, ETH Zurich.
  5. 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.
  6. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
  7. repec:taf:jnlbes:v:30:y:2012:i:2:p:181-190 is not listed on IDEAS
  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.
  9. de Jong, Piet, 1987. "Rational Economic Data Revisions," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 539-48, October.
  10. 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.
  11. 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.
  12. Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
  13. repec:taf:jnlbes:v:30:y:2012:i:2:p:173-180 is not listed on IDEAS
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