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A More Timely and Useful Index of Leading Indicators

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Listed:
  • Robert H. McGuckin

    (The Conference Board)

  • Ataman Ozyildirim

    (The Conference Board)

  • Victor Zarnowitz

    (The Conference Board)

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.

Suggested Citation

  • Robert H. McGuckin & Ataman Ozyildirim & Victor Zarnowitz, 2003. "A More Timely and Useful Index of Leading Indicators," Economics Program Working Papers 03-01, The Conference Board, Economics Program.
  • Handle: RePEc:cnf:wpaper:0301
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    File URL: http://www.conference-board.org/economics/workingpapers.cfm?pdf=E-0010-03-WP
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    References listed on IDEAS

    as
    1. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, June.
    2. 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, June.
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    Cited by:

    1. Ataman Ozyildirim & Brian Schaitkin & Victor Zarnowitz, 2010. "Business cycles in the euro area defined with coincident economic indicators and predicted with leading economic indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 6-28.
    2. 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.
    3. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    4. 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.
    5. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
    6. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2011. "Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 784-792.
    8. Thomas Gilbert & Shimon Kogan & Lars Lochstoer & Ataman Ozyildirim, 2012. "Investor Inattention and the Market Impact of Summary Statistics," Management Science, INFORMS, vol. 58(2), pages 336-350, February.
    9. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    10. 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, Centre for International Research on Economic Tendency Surveys, vol. 2004(2), pages 171-191.
    11. 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.
    12. Philip Gray, 2008. "Economic significance of predictability in Australian equities," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(5), pages 783-805, December.
    13. 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.
    14. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    15. 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.
    16. Jamie Alcock & Philip Gray, 2005. "Forecasting Stock Returns Using Model‐Selection Criteria," The Economic Record, The Economic Society of Australia, vol. 81(253), pages 135-151, June.
    17. Michael Donadelli & Antonio Paradiso & Max Riedel, 2019. "A Quasi Real‐Time Leading Indicator for the EU Industrial Production," Manchester School, University of Manchester, vol. 87(4), pages 510-542, July.
    18. Lleo, Sebastien & Ziemba, William T., 2014. "Does the bond-stock earning yield differential model predict equity market corrections better than high P/E models?," LSE Research Online Documents on Economics 59290, London School of Economics and Political Science, LSE Library.
    19. Blagica Petreski & Marjan Petreski, 2014. "Leading composite index produced by Finance Think: Forecasting power reassessed," Finance Think Policy Studies 2014-12/2, Finance Think - Economic Research and Policy Institute.
    20. Giuseppe Munda, 2015. "Beyond Gdp: An Overview Of Measurement Issues In Redefining ‘Wealth’," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 403-422, July.
    21. Marjan Petreski & Blagica Petreski, 2014. "Leading composite index produced by Finance Think: Forecasting power reassessed," Finance Think Policy Studies 2014-12, Finance Think - Economic Research and Policy Institute.
    22. Levanon, Gad & Manini, Jean-Claude & Ozyildirim, Ataman & Schaitkin, Brian & Tanchua, Jennelyn, 2015. "Using financial indicators to predict turning points in the business cycle: The case of the leading economic index for the United States," International Journal of Forecasting, Elsevier, vol. 31(2), pages 426-445.
    23. Petreski, Marjan, 2013. "Assessing the forecasting power of the leading composite index in Macedonia," MPRA Paper 49433, University Library of Munich, Germany.

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