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Composite Leading Indicators der amerikanischen Wirtschaft - Prognosegüte des Conference Board und des OECD Ansatzes im Vergleich

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  • Berneburg, Marian

Abstract

The Paper analyses both the Conference Board as well as the OECD Leading Indicators concerning their forecasting properties of overall economic activity. For this purpose the two indicators are introduced separately and several in-sample and out-of-sample tests are being conducted. The main focus, apart from other methods, is being laid on coherence tests as well as the Diebold/Mariano test. In contrast to many other analyses dealing with this topic, the chosen reference series is not industrial production, but rather the coincident index, as reported by the conference board. It seems as if both indicators show some sign of correlation to overall economic activity, but at the same time fail to improve on the forecasts of a simple time series model.

Suggested Citation

  • Berneburg, Marian, 2003. "Composite Leading Indicators der amerikanischen Wirtschaft - Prognosegüte des Conference Board und des OECD Ansatzes im Vergleich," IWH Discussion Papers 172/2003, Halle Institute for Economic Research (IWH).
    • Handle: RePEc:zbw:iwhdps:iwh-172
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    References listed on IDEAS

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    1. John E. Maher, 1957. "Forecasting Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 65(2), pages 158-158.
    2. Davis, E Philip & Fagan, Gabriel, 1997. "Are Financial Spreads Useful Indicators of Future Inflation and Output Growth in EU Countries?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(6), pages 701-714, Nov.-Dec..
    3. Auerbach, Alan J, 1982. "The Index of Leading Indicators: "Measurement without Theory," Thirty-Five Years Later," The Review of Economics and Statistics, MIT Press, vol. 64(4), pages 589-595, November.
    4. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    5. Geoffrey H. Moore & Julius Shiskin, 1967. "Indicators of Business Expansions and Contractions," NBER Books, National Bureau of Economic Research, Inc, number moor67-2.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Gary Gorton, 1982. "Forecasting with the Index of Leading Indicators," Business Review, Federal Reserve Bank of Philadelphia, issue Nov/Dec, pages 15-27.
    8. Wesley Clair Mitchell & Arthur F. Burns, 1938. "Statistical Indicators of Cyclical Revivals," NBER Books, National Bureau of Economic Research, Inc, number mitc38-1.
    9. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    10. Koch, Paul D & Rasche, Robert H, 1988. "An Examination of the Commerce Department Leading-Indicator Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 167-187, April.
    11. Saul H. Hymans, 1973. "On the Use of Leading Indicators to Predict Cyclical Turning Points," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 4(2), pages 339-384.
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