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The Relationship Between Financial Variables and Real Economic Activity: Evidence From Spectral and Wavelet Analyses

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  • Kim Sangbae

    ()
    (Monash University)

  • In Francis Haeuck

    ()
    (Monash University)

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    Abstract

    Many empirical studies find that financial variables possess a predictive power over real economic activity. To examine this relationship, we adopt two time-series techniques: spectral analysis and a newly developed method, wavelet analysis. The major innovation of this paper is to apply wavelet analysis to the investigation of the relationship between various financial variables and real economic activity. Spectral analysis reports that US industrial production and financial variables have a common component in the long run and a varying lead-lag relationship, depending on the cycles. It implies that the relationship between US industrial production and the financial variables is not constant over time. This result is consistently confirmed by wavelet analysis. The lead-lag relationship, in the sense of Granger causality, varies over time, depending on the wavelet time scale.

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    Bibliographic Info

    Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

    Volume (Year): 7 (2003)
    Issue (Month): 4 (December)
    Pages: 1-18

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    Handle: RePEc:bpj:sndecm:v:7:y:2003:i:4:n:4

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    Cited by:
    1. Patrick Crowley, 2005. "An intuitive guide to wavelets for economists," Econometrics 0503017, EconWPA.
    2. Rabeh Khalfaoui & Mohammed Boutahar, 2012. "Portfolio Risk Evaluation An Approach Based on Dynamic Conditional Correlations Models and Wavelet Multi-Resolution Analysis," AMSE Working Papers 1208, Aix-Marseille School of Economics, Marseille, France.
    3. Kim, Sangbae & In, Francis, 2007. "On the relationship between changes in stock prices and bond yields in the G7 countries: Wavelet analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(2), pages 167-179, April.
    4. Haven, Emmanuel & Liu, Xiaoquan & Shen, Liya, 2012. "De-noising option prices with the wavelet method," European Journal of Operational Research, Elsevier, vol. 222(1), pages 104-112.
    5. Nachane, D.M. & Dubey, Amlendu Kumar, 2011. "The vanishing role of money in the macro-economy: An empirical investigation for India," Economic Modelling, Elsevier, vol. 28(3), pages 859-869, May.
    6. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    7. Cifter, Atilla & Ozun, Alper, 2007. "Multiscale Systematic Risk: An Application on ISE-30," MPRA Paper 2484, University Library of Munich, Germany.
    8. Masih, Mansur & Alzahrani, Mohammed & Al-Titi, Omar, 2010. "Systematic risk and time scales: New evidence from an application of wavelet approach to the emerging Gulf stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 10-18, January.
    9. D.M. Nachane & Amlendu Kumar Dubey, 2008. "The vanishing role of money in the macroeconomy: An Empirical investigation based on spectral and wavelet analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2008-022, Indira Gandhi Institute of Development Research, Mumbai, India.
    10. Huang, Shian-Chang, 2011. "Wavelet-based multi-resolution GARCH model for financial spillover effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2529-2539.
    11. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu, 2013. "The influence of the international oil prices on the real effective exchange rate in Romania in a wavelet transform framework," Energy Economics, Elsevier, vol. 40(C), pages 714-733.
    12. Gallegati, Marco & Ramsey, James B., 2013. "Bond vs stock market's Q: Testing for stability across frequencies and over time," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 138-150.
    13. Marco Gallegati & Mauro Gallegati, 2005. "Wavelet variance and correlation analyses of output in G7 countries," Macroeconomics 0512017, EconWPA.
    14. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    15. Crowley , Patrick & Maraun , Douglas & Mayes , David, 2006. "How hard is the euro are core? An evaluation of growth cycles using wavelet analysis," Research Discussion Papers 18/2006, Bank of Finland.
    16. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.
    17. Buerhan Saiti & Azlan Ali & Naziruddin Abdullah & Sulaiman Sajilan, 2014. "Palm Oil Price, Exchange Rate, and Stock Market: A Wavelet Analysis on the Malaysian Market," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(1), pages 13-27.

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