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Swiss Journal of Economics and Statistics

, Volume 147, Issue 3, pp 353–375 | Cite as

The real-time predictive content of the KOF Economic Barometer

  • Boriss Siliverstovs
Open Access
Article

Summary

We investigate whether the KOF Economic Barometer – a leading indicator released by the KOF Swiss Economic Institute – is useful for short-term prediction of quarterly year-on-year real GDP growth in Switzerland. Using a real-time data set consisting of historical vintages of GDP data and the leading indicator we find that the model augemented with the KOF Barometer produces more accurate forecasts of the Swiss GDP than purely autoregressive models and consensus forecasts.

JEL-Classification

C53 C22 

Keywords

Leading Indicators Forecasting Switzerland 

References

  1. Amato, Jeffrey D., and Norman R. Swanson (2001), “The Real-Time Predictive Content of Money for Output”, Journal of Monetary Economics, 48, pp. 3–24.CrossRefGoogle Scholar
  2. Ashley, Richard, Clive W. J. Granger, and Richard Schmalensee (1980), “Advertising and Aggregate Consumption: An Analysis of Causality”, Econometrica, 48, pp. 1149–1167.CrossRefGoogle Scholar
  3. Clark, Todd E., and Kenneth D. West (2007), “Approximately Normal Tests for Equal Predictive Accuracy in Nested Models”, Journal of Econometrics, 138, pp. 291–311.CrossRefGoogle Scholar
  4. Croushore, Dean (2005), “Do Consumer-Confidence Indexes Help Forecast Consumer Spending in Real Time?”, The North American Journal of Economics and Finance, 16, pp.435–450.CrossRefGoogle Scholar
  5. Cuche-Curti, Nicolas, Pamela Hall, and Attilio Zanetti (2008), “Swiss GDP Revisions: A Monetary Policy Perspective”, Journal of Business Cycle Measurement and Analysis, 4, pp. 183–214.Google Scholar
  6. Diebold, Francis X. and Robert S. Mariano (1995), “Comparing Predictive Accuracy”, Journal of Business & Economic Statistics, 13, pp. 253–63.Google Scholar
  7. Diebold, Francis X. and Glenn D. Rudebusch (1991), “Forecasting Output with the Composite Leading Index: A Real-Time Analysis”, Journal of the American Statistical Association, 86, pp. 603–610.CrossRefGoogle Scholar
  8. Doornik, Jurgen A. (2007), Object-Oriented Matrix Programming Using Ox. London.Google Scholar
  9. Graff, Michael (2006), „Ein multisektoraler Sammelindikator für die Schweizer Konjunktur“, Schweizerische Zeitschrift für Volkswirtschaft und Statistik, 142, pp. 529–577.Google Scholar
  10. Graff, Michael (2010), “Does a Multi-Sectoral Design Improve Indicator-Based Forecasts of the GDP Growth Rate? Evidence for Switzerland”, Applied Economics, 42, pp. 2579–2781.CrossRefGoogle Scholar
  11. Granger, Clive W. J., Maxwell L. King, and Hall White (1995), “Comments on Testing Economic Theories and the Use of Model Selection Criteria”, Journal of Econometrics, 67, pp. 173–187.CrossRefGoogle Scholar
  12. Harvey, David I., Stephen J. Leybourne, and Paul Newbold (1997), “Testing the Equality of Prediction Mean Squared Errors”, International Journal of Forecasting, 13, pp. 281–291.CrossRefGoogle Scholar
  13. Harvey, David I., Stephen J. Leybourne, and Paul Newbold (1998), “Tests for Forecast Encompassing”, Journal of Business & Economic Statistics, 16, pp. 254–259.Google Scholar
  14. Marcellino, Massimiliano, James H. Stock, and Mark W. Watson (2006), “A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series”, Journal of Econometrics, 135, pp. 499–526.CrossRefGoogle Scholar

Copyright information

© Swiss Society of Economics and Statistics 2011

Authors and Affiliations

  1. 1.ETH ZurichKOF Swiss Economic InstituteZurichSwitzerland

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