How to treat benchmark revisions? The case of German production and orders statistics
Abstract
Elements of an econometric examination of benchmark revisions in real-time data are suggested. Structural break tests may be applied to detect heterogeneities within vintages. Systems cointegration tests are helpful to reveal inconsistencies across vintages. Differencing and rebasing, often used to adjust for benchmark revisions, are generally not sufficient to ensure consistent real-time macroeconomic data. Vintage transformation functions estimated by cointegrating regressions are more flexible. Inappropriate conversion may cause observed revision statistics to be affected by nuisance parameters. In German industrial production and orders statistics, remaining revisions are generally biased and serially correlated. --Download Info
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Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2006,38.Length:
Date of creation: 2006
Date of revision:
Handle: RePEc:zbw:bubdp1:5155
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Related research
Keywords: real-time data; benchmark revisions; industrial production; orders;Find related papers by JEL classification:
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-01-14 (All new papers)
- NEP-ECM-2007-01-14 (Econometrics)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Konstantin A. Kholodilin & Boriss Siliverstovs, 2009.
"Do Forecasters Inform or Reassure?: Evaluation of the German Real-Time Data,"
Discussion Papers of DIW Berlin
858, DIW Berlin, German Institute for Economic Research.
- Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do Forecasters Inform or Reassure? Evaluation of the German Real-Time Data," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(4), pages 269-294.
- Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure? Evaluation of the German real-time data," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
- Jan P.A.M. 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.
- 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.
- 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.
- Joachim Möller, 2012. "From a Bulwark of Eurosclerosis to a Flexibility Champion? Why Did the German Economy and the Labour Market Do So Well During and After the Recession?," CESifo DICE Report, Ifo Institute for Economic Research at the University of Munich, vol. 10(2), pages 14-19, 08.
- Jens Boysen-Hogrefe & Stefan Neuwirth, 2012. "The Impact of Seasonal and Price Adjustments on the Predictability of German GDP Revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy.
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