Analysis of revisions to quarterly GDP - a real-time database
Gross Domestic Product (GDP) is one of the key data series used by the Reserve Bank to inform monetary policy decisions. The measures of GDP, published by Statistics New Zealand (SNZ), are estimates rather than exact figures and may be revised in subsequent releases. Analysis of the most recent measures of GDP should incorporate the extent of uncertainty that surrounds these estimates. To enable a more detailed examination of revision patterns, the Reserve Bank has constructed a real-time database containing each quarterly release of Expenditure GDP (GDP(E)) and its components. The database is available to users on the Reserve Bank's website and will be regularly updated. This article provides an introduction to the database and, by way of example, presents a basic analysis of the revisions made to GDP(E) and its components.
Volume (Year): 69 (2006)
Issue (Month): (March)
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References listed on IDEAS
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99-21, Federal Reserve Bank of Philadelphia.
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Royal Economic Society, vol. 118(530), pages 1128-1144, 07.
- Anthony Garratt & Gary Koop & Shaun P. Vahey, 2006. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0617, Birkbeck, Department of Economics, Mathematics & Statistics.
- Anthony Garratt & Gary Koop & Shaun P. Vahey, 2006. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2006/02, Reserve Bank of New Zealand.
- Carol S Carson & Lucie LalibertÃ©, 2002. "Assessing Accuracy and Reliability; A Note Basedon Approaches Used in National Accounts and Balance of Payments Statistics," IMF Working Papers 02/24, International Monetary Fund.
- David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 3-12.
- Shaun Vahey & Tony Garratt, 2005.
"UK Real-time Macro Data Characteristics,"
Computing in Economics and Finance 2005
253, Society for Computational Economics.
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