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Interest rate spreads and output: A time scale decomposition analysis using wavelets

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  • Gallegati, Marco
  • Ramsey, James B.
  • Semmler, Willi

Abstract

The information content of several interest rate spreads for future output growth is analyzed using wavelet analysis. The “scale-by-scale” regression analysis shows that standard indicators of the stance of monetary policy, such as the shape of the yield curve, the real federal funds rate, and the credit spread have different information content for future output at different time frames. This is consistent with the idea that allowing for different time scales of variation in the data can provide a deeper understanding of the complex dynamics between real and financial variables, certainly richer than those obtainable using standard aggregate regression methods.

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  • Gallegati, Marco & Ramsey, James B. & Semmler, Willi, 2014. "Interest rate spreads and output: A time scale decomposition analysis using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 283-290.
    • Handle: RePEc:eee:csdana:v:76:y:2014:i:c:p:283-290
    DOI: 10.1016/j.csda.2014.02.024
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    10. Chiara Perricone, 2018. "Wavelet analysis for temporal disaggregation," CEIS Research Paper 444, Tor Vergata University, CEIS, revised 29 Oct 2018.
    11. Mustapha Olalekan Ojo & Luís Aguiar-Conraria & Maria Joana Soares, 2020. "A time–frequency analysis of the Canadian macroeconomy and the yield curve," Empirical Economics, Springer, vol. 58(5), pages 2333-2351, May.
    12. Younis, Ijaz & Shah, Waheed Ullah & Yousaf, Imran, 2023. "Static and dynamic linkages between oil, gold and global equity markets in various crisis episodes: Evidence from the Wavelet TVP-VAR," Resources Policy, Elsevier, vol. 80(C).
    13. João Martins, 2022. "Bond Yields Movement Similarities and Synchronization in the G7: A Time–Frequency Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 189-214, July.
    14. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
    15. Michele Fratianni & Marco Gallegati & Federico Giri, 2019. "Mr Phillips and the medium-run: temporal instability vs. frequency stability," Mo.Fi.R. Working Papers 155, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    16. He, Kaijian & Xu, Yang & Zou, Yingchao & Tang, Ling, 2015. "Electricity price forecasts using a Curvelet denoising based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 1-9.

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