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Real-Time Tests of the Leading Economic Index: Do Changes in the Index Composition Matter?

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  • Robert H. McGuckin
  • Ataman Ozyildirim

Abstract

In an important paper, Diebold and Rudebusch (1991) find that, despite good performance for post revision historical versions, the U.S. Index of Leading Economic Indicators (LEI) fails to improve forecasts in real time out-of-sample tests. This paper revisits the issue of real-time performance of the LEI using growth rate forecast specifications. We contrast real-time out-of-sample tests of LEI forecasts using „composition-changing” or „as-published” versions of the LEI with those based on „composition-constant” indexes. The goal is ...

Suggested Citation

  • 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.
    • Handle: RePEc:oec:stdkaa:5lmqcr2jcpd8
    DOI: 10.1787/jbcma-v2004-art11-en
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    References listed on IDEAS

    as
    1. Maximo Camacho & Gabriel Perez-Quiros, 2002. "This is what the leading indicators lead," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 61-80.
    2. Geoffrey H. Moore, 1950. "Statistical Indicators of Cyclical Revivals and Recessions," NBER Books, National Bureau of Economic Research, Inc, number moor50-1.
    3. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1.
    4. repec:ucp:bknber:9780226978901 is not listed on IDEAS
    5. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
    6. McGuckin, Robert H. & Ozyildirim, Ataman & Zarnowitz, Victor, 2007. "A More Timely and Useful Index of Leading Indicators," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 110-120, January.
    7. Geoffrey H. Moore & Julius Shiskin, 1967. "Indicators of Business Expansions and Contractions," NBER Books, National Bureau of Economic Research, Inc, number moor67-2.
    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. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Rua, Antonio & Nunes, Luis C., 2005. "Coincident and leading indicators for the euro area: A frequency band approach," International Journal of Forecasting, Elsevier, vol. 21(3), pages 503-523.
    2. Loría, Eduardo & Brito, L., 2004. "Is the Consumer Confidence Index a Sound Predictor of the Private Demand in the United States?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 22, pages 1-15, Diciembre.
    3. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    4. 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.

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    More about this item

    Keywords

    Business cycle; Indicators; Leading index; Times series; Forecasting;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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