Skip to main content
Log in

The predictive power of yield spread: evidence from wavelet analysis

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

This paper examines whether the spread between long- and short-terminterest rates contains information about future economic activity in India. Using the yields on securities with maturities ranging from three months to ten years, we construct five different yield spreads at shorter end, longer end, and policy relevant area of the yield curve. We study the predictive power of each of these spreads for output growth within aggregate and time scale framework using wavelet methodology. We find that predictive power holds only at lower frequencies for the spreads which are constructed at shorter end and policy relevant areas of yield curve. However, spreads which are constructed at the longer end of the yield curve do not seem to have predictive information for output growth.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. Since time and frequency are inversely related, higher time scales represent lower frequencies of time series and vice-versa.

  2. For constructing the spreads at different areas of yield curve, we followed Tkacz (2004).

  3. Since \(\mathrm{A}_{4}\) components represent the non-stationary component of the time series, in our regression analysis, they were not tested for predictive power.

  4. Sp (1, 3) refers to the yield spread constructed at the shorter end of yield curve. Sp (5, 3) and Sp (10, 3) refer to yield spreads constructed at the policy relevant area of yield curve Sp (10, 5), and Sp (10, 8) represent the yield spreads constructed at the longer end of yield curve.

References

  • Adel S, Martin C, Heather JR, Jose AM (2006) The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms. Physica A 368(2): 511–521

    Google Scholar 

  • Aguiar-Conraria L, Azevedo N, Soares MJ (2008) Using wavelets to decompose the time-frequency effects of monetary policy. Physica A 387(12):2863–2878

    Article  Google Scholar 

  • Ang A, Piazzesi M, Wei M (2006) What does the yield curve tell us about GDP? J. Economics 131:359–403

    Article  Google Scholar 

  • Bhaduri S, Saraogi R (2010) The predictive power of the yield spread in timing the stock market. Emerging Markets Review 11:261–272

    Article  Google Scholar 

  • Bonser-Neal C, Morley TR (1997) Does the yield spread predict real economic activity? A multicountry analysis. Economic Review, Federal Reserve Bank of Kansas City. Third Quarter. 37–53

  • Bordo MD, Haubrich JG (2008) Forecasting with the yield curve, level, slope, and output. Economic Letters 99:48–50

    Article  Google Scholar 

  • Caroline J (2004) Why did the term structure of interest rates lose its predictive power? Economic Modelling 21(3):509–24

    Article  Google Scholar 

  • Crowley P (2007) A guide to wavelets for economists. Journal of Economic Surveys 21(2):207–267

    Article  Google Scholar 

  • Daubechies I (1992) Ten Lectures on Wavelets. SIAM, Philadelphia

    Book  Google Scholar 

  • Dotsey M (1998) Predictive content of the interest rate yield spread for future economic growth. The Federal Reserve. Bank of Richmond Economic Quarterly. Summer 84(3):31–51

    Google Scholar 

  • Estrella W, Hardouvelis G (1991) The term structure as predictor of real activity. Journal of Finance 46: 555–576

    Google Scholar 

  • Estrella A, Mishkin F (1997) The predictive power of the term structure of interest rates in Europe and the United States. European Economic Review 41:1375–1401

    Article  Google Scholar 

  • Fisher C, Felmingham B (1998) The Australian yield curve as a leading indicator of consumption growth. Applied Finance Economy 8(6):627–635

    Article  Google Scholar 

  • Gabor D (1946) Theory of communications. J. Inst. Elect. Eng 93:429–457

    Google Scholar 

  • Gallegati M, Ramsey JB, Semmler W (2011) The US Wage Phillips Curve across Frequencies and over Time. Oxford Bulletin of Economics and Statistics 73(4): 489–508

  • Gençay R, Selçuk F, Whitcher B (2002) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics. Academic Press, San Diego

    Google Scholar 

  • Hamilton JD, Kim DH (2002) A re-examination of the predictability of economic activity using the yield spread. J. Money Credit Bank 34(2):340–360

    Article  Google Scholar 

  • Kanagasabapathy K, Goyal R (2002) Yield spread as a leading indicator of real economic activity: An empirical exercise on the Indian economy. IMF Working paper Series 2/91

  • Kim A, Limpaphayom P (1997) The effect of economic regimes on the relation between term structure and real activity in Japan. J. Economics Business 49(4):379–392

    Article  Google Scholar 

  • Mallat SG (1989) Multiresolution approximations and wavelet orthonormal bases of \(\text{ L }^{2}\)(R). Trans Amer Math Soc 315:69–87

    Google Scholar 

  • Nakaota H (2005) The term structure of interest rates in Japan: The predictability of economic activity. Japan and the World Economy 17(3):311–26

    Article  Google Scholar 

  • Newey WK, West KD (1987) A simple, positive semi-definite, hetroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703–708

    Google Scholar 

  • Peel DA, Taylor MP (1998) The slope of the yield curve and real economic activity: tracing the transmission Mechanism. Economic Letters 59:353–360

    Google Scholar 

  • Percival DB, Walden AT (2000) Wavelet Methods for Time Series Analysis. Cambridge Press, Cambridge

    Book  Google Scholar 

  • Ramsey JB (2002) Wavelets in economics and finance: past and future. Studies in Nonlinear Dynamics and Econometrics 6(3):1–27

    Google Scholar 

  • Ramsay JB, Lampart C (1998a) The decomposition of economic relationships by time scale using wavelet: expenditure and income. Studies Nonlinear Dyn Econ 3:23–42

    Google Scholar 

  • Ramsay JB, Lampart C (1998b) Decomposition of economic relationships by time scale using wavelets. Macroeconmic Dynamics 1:49–71

    Google Scholar 

  • Rosenberg JV, Maurer S (2008) Signal or Noise? Implications of the Term Premium for Recession Forecasting. Federal Reserve Bank of New York- Economic Policy Review 14:1–11

    Google Scholar 

  • Stock JH, Watson MW (1989) New indexes of coincident and leading economic indicators. NBER Macroeconomics Annual 4:351–409

    Article  Google Scholar 

  • Stock JH, Watson MW (2003) Forecasting output and inflation: the role of asset prices. Journal of Economic Literature 41(3):788–829

    Google Scholar 

  • Tabak BM, Feitosa MA (2009) An analysis of the yield spread as a predictor of inflation in Brazil: Evidence from a wavelets approach. Expert Systems with Applications 36:7129–7134

    Article  Google Scholar 

  • Tabak BM, Feitosa MA (2010) Forecasting industrial production in Brazil: Evidence from a wavelets approach. Expert Systems with Applications 37:6345–6351

    Article  Google Scholar 

  • Tkacz G (2004) Inflation changes, yield spreads, and threshold effects. International Review of Economics and Finance 13:187–199

    Article  Google Scholar 

  • Venetis IA, Paya I, Peel DA (2003) Re-examination of the predictability of economic activity using the yield spread: a non linear approach. International Review of Economics and Finance 12(2):187–206

    Article  Google Scholar 

  • Zagaglia P (2006) Does the yield spread predict the output gap in the US?. Stockholm University, Working Paper 6

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Firdous Ahmad Shah.

Appendix

Appendix

See Table 6 and Figs. 1, 2 and 3.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dar, A.B., Samantaraya, A. & Shah, F.A. The predictive power of yield spread: evidence from wavelet analysis. Empir Econ 46, 887–901 (2014). https://doi.org/10.1007/s00181-013-0705-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00181-013-0705-6

Keywords

JEL Classification

Navigation