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Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set

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  • Herman O. Stekler

    (The George Washington University)

  • Yongchen Zhao

    (Towson University)

Abstract

This paper considers the issue of predicting cyclical turning points using real-time diffusion indexes constructed using a large data set from March 2005 to September 2014. We construct diffusion indexes at the monthly frequency, compare several smoothing and signal extraction methods, and evaluate predictions based on the indexes. Our finding suggest that diffusion indexes are still effective tools in predicting turning points. Using diffusion indexes, along with good judgement, one would have successfully predicted or at least identified the 2008 recession in real time.

Suggested Citation

  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2016-006
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    References listed on IDEAS

    as
    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
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    5. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    6. Herman O Stekler & Raj M Talwar, 2013. "Forecasting the Downturn of the Great Recession," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 48(2), pages 113-120, April.
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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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