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Fossil Fuel-Based versus Electric Vehicles: A Volatility Spillover Perspective Regarding the Environment

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  • Shailesh Rastogi

    (Symbiosis Institute of Business Management Nagpur, Symbiosis International (Deemed) University, Pune 440008, India)

  • Jagjeevan Kanoujiya

    (Symbiosis Institute of Business Management Nagpur, Symbiosis International (Deemed) University, Pune 440008, India)

  • Satyendra Pratap Singh

    (Alliance School of Business, Alliance University, Bengaluru 562106, India)

  • Adesh Doifode

    (Symbiosis School of Banking & Finance, Symbiosis International (Deemed) University, Pune 412115, India)

  • Neha Parashar

    (Symbiosis School of Banking & Finance, Symbiosis International (Deemed) University, Pune 412115, India)

  • Pracheta Tejasmayee

    (Symbiosis Institute of Business Management Nagpur, Symbiosis International (Deemed) University, Pune 440008, India)

Abstract

Due to environmental concerns, electric vehicles (EVs) are gaining traction over fossil fuel-based vehicles. For electronic devices, including vehicles, copper is the key material used for building. This situation draws attention to the impact of copper prices, crude oil prices, and exchange rates on the economic viability of using EVs over fossil fuels. We use the volatility spillover effect (VSE) to determine the financial viability of these two types of vehicles in the context of environmental issues. Daily data on copper prices, crude oil, exchange rate, and the BSE100 ESG (“Bombay Stock Exchange 100 Environmental, Social and Governance”) index are taken from 1 November 2017 to 20 September 2022. Two popular multivariate GARCH (“Multivariate Generalized Autoregressive Conditional Heteroscedasticity”) family models, i.e., the BEKK (“Baba–Engle–Kraft–Kroner”)-GARCH (BG) and DCC (“Dynamic Conditional Correlation”)-GARCH (DG) models, are utilized to find volatility connections between these variables. These are appropriate GARCH models to observe the volatility dependence of one market on another market. It is found that there exist volatility effects of copper and exchange rate on the S&P BSE100 ESG Equity Index Price, which we will refer to here as ESG. However, crude oil is found to be insignificant for ESG. The novelty of this study is in the use of volatility spillover to determine economic viability. The volatility effects of copper prices are positive for ESG in the short run and negative for long-term volatility. The exchange rate has a positive volatility effect on ESG in the long run. Surprisingly, we find that EVs are technologically better than fossil fuel-based vehicles as a possible sustainable energy source. We observe studies that have raised similar concerns about EVs’ lack of business sense compared to fossil fuels. However, using VSE to explore financial viability offers a fresh perspective. Based on the findings of the current study, it is recommended that policymakers and researchers revisit their support for EVs as an alternate and sustainable source of energy.

Suggested Citation

  • Shailesh Rastogi & Jagjeevan Kanoujiya & Satyendra Pratap Singh & Adesh Doifode & Neha Parashar & Pracheta Tejasmayee, 2023. "Fossil Fuel-Based versus Electric Vehicles: A Volatility Spillover Perspective Regarding the Environment," JRFM, MDPI, vol. 16(12), pages 1-16, November.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:12:p:494-:d:1285330
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    References listed on IDEAS

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    1. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. A.S.M. Sohel Azad, 2009. "Efficiency, Cointegration and Contagion in Equity Markets: Evidence from China, Japan and South Korea," Asian Economic Journal, East Asian Economic Association, vol. 23(1), pages 93-118, March.
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