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

  • Lupi, Claudio

    ()

  • Peracchi, Franco

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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Paper provided by University of Molise, Dept. EGSeI 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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  1. 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 and International Relations Area.
  2. Cainelli, Giulio & Lupi, Claudio, 1999. "The Choice of the Aggregation Level in the Estimation of Quarterly National Accounts," Review of Income and Wealth, International Association for Research in Income and Wealth, 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. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  5. G. Cainelli & C. Lupi, 1998. "Aggregazione contemporanea e specificazione econometrica nella stima trimestrale dei conti economici nazionali," Working Papers 319, Dipartimento Scienze Economiche, Universita' di Bologna.
  6. 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.
  7. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  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.
  9. de Jong, Piet, 1987. "Rational Economic Data Revisions," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 539-48, October.
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