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Improving the Predictive Power of Spreads for Economic Activity: A Wavelet Method

Author

Listed:
  • Chang Min LEE

    (Financial Market Analysis Division, Financial Services Commission, Korea.)

  • Hahn Shik LEE

    (Corresponding author. Department of Economics, Sogang University, Korea)

Abstract

In this paper, we examine whether and to what extent the predictive power of credit spread for real economic activity can be enhanced by using additional information via wavelet approach. In doing so, we first apply the wavelet analysis to the Korean real GDP data, and present evidence that the business-cycle component of wavelet-filtered series closely resembles the series obtained from an approximate band-pass filter. Given the recent empirical findings that the credit spread has a useful explanatory power for future economic fluctuations, we also suggest that the business-cycle component of the credit spread can better predict the probability of a recession than the usual time- domain analysis. The wavelet methodology used in this paper can naturally be applied to any sets of economic and financial time series to unveil their structures and hence to enhance their predictive contents.

Suggested Citation

  • Chang Min LEE & Hahn Shik LEE, 2016. "Improving the Predictive Power of Spreads for Economic Activity: A Wavelet Method," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 65-78, December.
    • Handle: RePEc:rjr:romjef:v::y:2016:i:4:p:65-78
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    References listed on IDEAS

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    1. Sunju Hwang & Hahn Shik Lee, 2016. "Predictability of Term Spread for Economic Activity with Liquidity Premium Theory," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(7), pages 1528-1541, July.
    2. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
    3. Michael Dotsey, 1998. "The predictive content of the interest rate term spread for future economic growth," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 31-51.
    4. Benjamin M. Friedman & Kenneth Kuttner, 1993. "Why Does the Paper-Bill Spread Predict Real Economic Activity?," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 213-254, National Bureau of Economic Research, Inc.
    5. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
    6. Gertler, Mark & Lown, Cara S, 1999. "The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 15(3), pages 132-150, Autumn.
    7. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    8. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    9. 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.
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    Cited by:

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    3. Jasmina Ðuraškovic & Slavica Manic & Dejan Živkov, 2019. "Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(2), pages 211-235, April.
    4. Jovan Njegic & Milica Stankovic & Dejan Živkov, 2019. "What Wavelet-Based Quantiles Can Suggest about the Stocks-Bond Interaction in the Emerging East Asian Economies?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(1), pages 95-119, February.
    5. Yonghong JIANG & Juan MENG & He NIE, 2018. "Visiting the Economic Policy Uncertainty Shocks - Economic Growth Relationship: Wavelet-based Granger-Causality in Quantiles Approac," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 80-94, December.
    6. Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.

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    More about this item

    Keywords

    credit spread; business cycle; wavelet decomposition;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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