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A Statistical Analysis of Revisions of Swedish National Accounts Data

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Abstract

In this paper, we study revisions of Swedish national accounts data. Three aspects of the revisions are considered: volatility, unbiasedness and forecast efficiency. Our results indicate that the properties of the revisions are more problematic for the production side than for the expenditure side. The high volatility of the revisions on the production side indicates that it, based on the initial data release, generally is difficult to make clear cut statements concerning production in different industries within the business sector; it is also likely to make forecasting more difficult. Concerning unbiasedness, there appears to be shortcomings for a number of variables, including GDP; this finding implies that it could be possible to improve the production of the Swedish national accounts data.

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  • Flodberg, Caroline & Österholm, Pär, 2015. "A Statistical Analysis of Revisions of Swedish National Accounts Data," Working Papers 136, National Institute of Economic Research.
  • Handle: RePEc:hhs:nierwp:0136
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    1. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    2. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    3. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    4. Boriss Siliverstovs, 2012. "Are GDP Revisions Predictable? Evidence for Switzerland," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 58(4), pages 299-326.
    5. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    6. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    7. Jens Richard Clausen & Carsten-Patrick Meier, 2005. "Did the Bundesbank Follow a Taylor Rule? An Analysis Based on Real-Time Data," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 141(II), pages 213-246, June.
    8. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    9. 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 403-419, June.
    10. Lars-Erik Öller & Karl-Gustav Hansson, 2005. "Revision of National Accounts: Swedish Expenditure Accounts and GDP," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(3), pages 363-385.
    11. Jacopo Cimadomo, 2012. "Fiscal Policy in Real Time," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(2), pages 440-465, June.
    12. repec:bla:revinw:v:15:y:1969:i:3:p:229-45 is not listed on IDEAS
    13. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
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    More about this item

    Keywords

    Real-time data; Volatility; Unbiasedness; Forecast efficiency;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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