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The Information Content of KOF Indicators on Swiss Current Account Data Revisions


  • Jan Jacobs
  • Jan-Egbert Sturm


This paper analyses revisions of Swiss current account data, taking into account the actual data revision process and the implied types of revisions. In addition we investigate whether the first release of current account data can be improved upon by the use of survey results as gathered by the KOF Swiss Economic Institute, ETH Zurich. An answer in the affirmative indicates that it is possible to improve first releases and thereby enhance the current assessment of the Swiss economy.

Suggested Citation

  • Jan Jacobs & Jan-Egbert Sturm, 2008. "The Information Content of KOF Indicators on Swiss Current Account Data Revisions," CESifo Working Paper Series 2370, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_2370

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    References listed on IDEAS

    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. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    3. Pierre Siklos, 2006. "What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation: Some US Evidence," Working Papers eg0049, Wilfrid Laurier University, Department of Economics, revised 2006.
    4. Richard Etter & Michael Graff, 2004. "Coincident and Leading Indicators of Manufacturing Industry," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 109-131.
    5. Jan Jacobs & Jan-Egbert Sturm, 2004. "Do Ifo Indicators Help Explain Revisions in German Industrial Production?," CESifo Working Paper Series 1205, CESifo Group Munich.
    6. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    7. Swanson, Norman R. & van Dijk, Dick, 2006. "Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 24-42, January.
    8. Lee, Kevin & Shields, Kalvinder, 2000. " Expectations Formation and Business Cycle Fluctuations: An Empirical Analysis of Actual and Expected Output in UK Manufacturing, 1975-1996," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 463-490, September.
    9. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank.
    10. 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.
    11. Richard McKenzie, 2006. "Undertaking Revisions and Real-Time Data Analysis using the OECD Main Economic Indicators Original Release Data and Revisions Database," OECD Statistics Working Papers 2006/2, OECD Publishing.
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    Cited by:

    1. repec:taf:apeclt:v:23:y:2016:i:15:p:1062-1064 is not listed on IDEAS
    2. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, Hamburg University, Department Wirtschaft und Politik.
    3. Pascal Bührig & Klaus Wohlrabe, 2016. "Forecasting revisions of German industrial production," Applied Economics Letters, Taylor & Francis Journals, vol. 23(15), pages 1062-1064, October.
    4. Boriss Siliverstovs, 2010. "Assessing Predictive Content of the KOF Barometer in Real Time," KOF Working papers 10-249, KOF Swiss Economic Institute, ETH Zurich.
    5. Jan P. A. M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.

    More about this item


    current account statistics; real-time analysis; data revisions;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access


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