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Analysis of revisions to quarterly GDP - a real-time database

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Author Info

  • Cath Sleeman

    (Reserve Bank of New Zealand)

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    Abstract

    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.

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    File URL: http://www.rbnz.govt.nz/research_and_publications/reserve_bank_bulletin/2006/2006mar69_1sleeman.pdf
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    Bibliographic Info

    Article provided by Reserve Bank of New Zealand in its journal Reserve Bank of New Zealand Bulletin.

    Volume (Year): 69 (2006)
    Issue (Month): (March)
    Pages: 44p.

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    Handle: RePEc:nzb:nzbbul:march2006:4

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    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.:
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    1. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    2. 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.
    3. Shaun Vahey & Tony Garratt, 2005. "UK Real-time Macro Data Characteristics," Computing in Economics and Finance 2005 253, Society for Computational Economics.
    4. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    5. Carol S. Carson & Lucie Laliberté, 2002. "Assessing Accuracy and Reliability: A Note Based on Approaches Used in National Accounts and Balance of Payments Statistics," IMF Working Papers 02/24, International Monetary Fund.
    6. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-19, June.
    7. 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.
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    Cited by:
    1. Michael Pedersen, 2013. "Extracting GDP signals from the monthly indicator of economic activity: Evidence from Chilean real-time data," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2013(1), pages 1-16.
    2. Troy Matheson & James Mitchell & Brian Silverstone, 2007. "Nowcasting and predicting data revisions in real time using qualitative panel survey data," Reserve Bank of New Zealand Discussion Paper Series DP2007/02, Reserve Bank of New Zealand.
    3. Leo Krippner & Leif Anders Thorsrud, 2009. "Forecasting New Zealand's economic growth using yield curve information," Reserve Bank of New Zealand Discussion Paper Series DP2009/18, Reserve Bank of New Zealand.

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