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Testing for wavelet based time-frequency relationship between oil prices and US economic activity

Author

Listed:
  • Syed Ali Raza
  • Muhammad Shahbaz

    (GATECH - College of Computing - Georgia Institute of Technology [Atlanta])

  • Rafi Amir-Ud-Din
  • Rashid Sbia

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Nida Shah

Abstract

This study investigates the empirical association of oil prices with economic activity in developed open economy namely: The United States by using the wavelet transform framework. This methodology enables the decomposition of time-series at different time-frequencies. In this study, we have used maximal overlap discrete wavelet transform, wavelet covariance, wavelet correlation, continuous wavelet power spectrum, wavelet coherence spectrum and wavelet based Granger causality approaches to analyze the relationship between oil prices and economic activity. The present study uses month frequency data for the period of 1979M1-2013M7. The results indicate that oil prices have positive impact on economic activity and the feedback effect exists between oil prices and economic activity.

Suggested Citation

  • Syed Ali Raza & Muhammad Shahbaz & Rafi Amir-Ud-Din & Rashid Sbia & Nida Shah, 2018. "Testing for wavelet based time-frequency relationship between oil prices and US economic activity," Post-Print hal-01982294, HAL.
    • Handle: RePEc:hal:journl:hal-01982294
    DOI: 10.1016/j.energy.2018.02.037
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