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Forecasting with the Index of Leading Indicators

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  • Beatrice N. Vaccara
  • Victor Zarnowitz

Abstract

The composite index of leading indicators is found to be a valuable tool for predicting not only the direction but also the size of near- term changes in aggregate economic activity. This conclusion is based on assessments of the leading index as a predictor of (1) business cycle turning points as dated by the National Bureau of Economic Research and (2) quantitative changes in real GNP and the composite index of coincident indicators. Specific smoothing rules are identified which reduce the frequency of false signals but still provide adequate early warning of cyclical turning points. Simple regression models based on first differences in the logarithms produce a comparatively good record of forecasts one and two quarters ahead. The best results are obtained by using predictive chains whereby, e.g., quarterly changes in the lagging index (inverted) for Q[sub t] are used to forecast changes in the leading index in quarter Q which in turn are used to forecast changes in real GNP (or the coincident index) in Q[sub t+2].

Suggested Citation

  • Beatrice N. Vaccara & Victor Zarnowitz, 1978. "Forecasting with the Index of Leading Indicators," NBER Working Papers 0244, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0244
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    Cited by:

    1. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    2. Rafal Kasperowicz, 2010. "Identification Of Industrial Cycle Leading Indicators Using Causality Test," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 5(2), pages 47-59, December.
    3. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    4. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 95-156, National Bureau of Economic Research, Inc.
    5. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, September.
    6. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    7. Werner Hölzl & Michael Klien & Agnes Kügler, 2019. "Konjunktur schwächt sich weiter ab. Ergebnisse der Quartalsbefragung des WIFO-Konjunkturtests vom Oktober 2019," WIFO Monatsberichte (monthly reports), WIFO, vol. 92(11), pages 807-819, November.
    8. Wolfgang Nierhaus & Klaus Abberger, 2014. "Zur Prognose von konjunkturellen Wendepunkten: Dreimal-Regelversus Markov-Switching," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(16), pages 21-25, August.
    9. Vojtech Benda & Lubos Ruzicka, 2007. "Short-term Forecasting Methods Based on the LEI Approach: The Case of the Czech Republic," Research and Policy Notes 2007/01, Czech National Bank.
    10. Victor Zarnowitz, 1986. "The Record and Improvability of Economic Forecasting," NBER Working Papers 2099, National Bureau of Economic Research, Inc.
    11. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.

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