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The limits of statistical information: How important are GDP revisions in Italy?

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Author Info
Lupi, Claudio ()
Peracchi, Franco

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Abstract

The use of Gross Domestic Product (GDP) as a summary measure of the level of economic activity is pervasive in empirical economics, policy analysis and forecasting. This pervasive role of GDP and its nature of "public good" raises obvious problems of timeliness and accuracy of the data. A striking feature of GDP data (and, more generally, of all national accounts figures) is the presence of "data vintages". That is, the GDP estimate for a specific year or quarter is subject to several revisions after its first release. As a result, both the level and the profile of GDP over a given period may change, sometimes substantially, through time. This paper presents some evidence on the extent of GDP revisions in Italy, with particular emphasis on revisions of the quarterly national accounts series, and compares the Italian evidence with the available evidence from other countries. After discussing some areas in which data revisions can have potentially important consequences, the paper concludes with some policy recommendations.

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Publisher Info
Paper provided by University of Molise, Dept. SEGeS in its series Economics & Statistics Discussion Papers with number esdp03005.

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Length: 61 pages
Date of creation: 06 Jun 2003
Date of revision:
Handle: RePEc:mol:ecsdps:esdp03005

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Related research
Keywords: Data revisions; National accounts; Real-time datasets.;

Find related papers by JEL classification:
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November. [Downloadable!] (restricted)
  2. Cainelli, Giulio & Lupi, Claudio, 1999. "The Choice of the Aggregation Level in the Estimation of Quarterly National Accounts," Review of Income and Wealth, Blackwell Publishing, vol. 45(4), pages 483-92, December.
  3. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
  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. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November. [Downloadable!] (restricted)
    Other versions:
  6. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September. [Downloadable!] (restricted)
    Other versions:
  7. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research Department. [Downloadable!]
  8. Bordignon, Silvano & Trivellato, Ugo, 1989. "The Optimal Use of Provisional Data in Forecasting with Dynamic Model s," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(2), pages 275-86, April.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  2. Martin Schneider & Christian Ragacs, 2009. "Why did we fail to predict GDP during the last cycle? A breakdown of forecast errors for Austria," Working Papers 151, Oesterreichische Nationalbank (Austrian Central Bank). [Downloadable!]
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