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Renewable energy consumption and industrial production: A disaggregated time-frequency analysis for the U.S

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  • Hoang, Thi Hong Van
  • Shahzad, Syed Jawad Hussain
  • Czudaj, Robert L.

Abstract

This paper aims to analyze the interaction between renewable energy consumption and industrial production for the U.S. over the 1981–2018 period. We contribute to the existing literature by the disaggregation of renewable energy sources (hydropower, geothermal, and biomass), by the consideration of time and frequency through wavelet techniques and the time-varying Granger causality test recently proposed by Shi et al. (2018). Based on monthly data, wavelet results show a positive co-movement between industrial production and biomass energy consumption at low frequencies, meaning in the long term only. The bootstrap rolling-window Granger causality test indicates a bi-directional predictability between renewable energy consumption and industrial production in crisis and turmoil periods only. These results are found to be robust to the inclusion of control variables (non-renewable energy consumption and crude oil prices) and to the selection of the lag length for the corresponding VAR model.

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  • Hoang, Thi Hong Van & Shahzad, Syed Jawad Hussain & Czudaj, Robert L., 2020. "Renewable energy consumption and industrial production: A disaggregated time-frequency analysis for the U.S," Energy Economics, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319302051
    DOI: 10.1016/j.eneco.2019.06.018
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    Keywords

    Renewable energies; Disaggregated sources; Industrial production; U.S.; Wavelet; Granger causality; Rolling-window;
    All these keywords.

    JEL classification:

    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation

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