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A More Timely and Useful Index of Leading Indicators

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Author Info

  • McGuckin, Robert H.
  • Ozyildirim, Ataman
  • Zarnowitz, Victor

Abstract

Effectively predicting cyclical movements in the economy is a major challenge. While there are other approaches to forecasting, the U.S. leading index has long been used to analyze and predict economic fluctuations. We describe and test a new procedure for making the index more timely. The new index significantly outperforms its less timely counterpart and offers substantial gains in real-time out-of-sample forecasts of changes in aggregate economic activity and industrial production. It provides timely and accurate ex-ante information for predicting, not only the business cycle turning points, but the monthly changes in the economy.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 25 (2007)
Issue (Month): (January)
Pages: 110-120

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Handle: RePEc:bes:jnlbes:v:25:y:2007:p:110-120

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References

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  1. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
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Citations

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Cited by:
  1. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2005. "Forecasting with real-time macroeconomic data: the ragged-edge problem and revisions," CCSO Working Papers 200505, University of Groningen, CCSO Centre for Economic Research.
  2. Chiara Scotti & S.Boragan Aruoba & Francis X. Diebold & University of Maryland, 2006. "Real-Time Measurement of Business Conditions," Computing in Economics and Finance 2006 387, Society for Computational Economics.
  3. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481.
  4. Heij, C. & van Dijk, D.J.C. & Groenen, P.J.F., 2009. "Macroeconomic forecasting with real-time data: an empirical comparison," Econometric Institute Research Papers EI 2009-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  5. Paap, Richard & Segers, Rene & van Dijk, Dick, 2009. "Do Leading Indicators Lead Peaks More Than Troughs?," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 528-543.
  6. Robert H. McGuckin & Ataman Ozyildirim, 2004. "Real-Time Tests of the Leading Economic Index: Do Changes in the Index Composition Matter?," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2004(2), pages 171-191.
  7. Henk Kranendonk & Jan Bonenkamp & Johan Verbruggen, 2004. "A leading indicator for the Dutch economy; methodological and empirical revision of the CPB system," CPB Discussion Paper 32, CPB Netherlands Bureau for Economic Policy Analysis.
  8. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Ravazzolo, F., 2007. "Evaluating real-time forecasts in real-time," Econometric Institute Research Papers EI 2007-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  9. Petreski, Marjan, 2013. "Assessing the forecasting power of the leading composite index in Macedonia," MPRA Paper 49433, University Library of Munich, Germany.
  10. Henk C. Kranendonk & Jan Bonenkamp & Johan P. Verbruggen, 2004. "A Leading Indicator for the Dutch Economy – Methodological and Empirical Revision of the CPB System," CESifo Working Paper Series 1200, CESifo Group Munich.
  11. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.

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