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Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies

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  • Sharif, Arshian
  • Brahim, Mariem
  • Dogan, Eyup
  • Tzeremes, Panayiotis

Abstract

Cryptocurrencies have been widely used as financial instruments over the past decade. Given the development of the cryptocurrency market and the increasing awareness of greener and more energy-efficient tokens, their connection to the green economy has become a popular topic for understanding economic and policy issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green economy indicators. Therefore, this study examines the correlations and spillover relationships between green economy indices, five black cryptocurrencies, and five clean cryptocurrencies for the U.S., Euro, and Asian markets. To this end, it applies the novel quantile spillover index approach of Ando et al. (2018) to daily data from November 9, 2017, to April 4, 2022. The empirical results show that the overall linkage is stronger for green economy indices and clean cryptocurrencies than for dirty cryptocurrencies. Moreover, green economy indices show net receiving behavior, while cryptocurrencies' results differ across variables, quantiles, and time. In addition, a notable point for clean cryptocurrencies is 2020, which was the start of the COVID-19 pandemic. The overall spillover effect is very high for all quantiles for the three markets, especially for Asia. This outcome signifies the safe harbor property for diversification purposes of the green economy. The results presented in this study are important for investors, regulators and, policymakers, cryptocurrency founders as they seek to be financially integrated and develop a more sustainable business.

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  • Sharif, Arshian & Brahim, Mariem & Dogan, Eyup & Tzeremes, Panayiotis, 2023. "Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
  • Handle: RePEc:eee:eneeco:v:120:y:2023:i:c:s0140988323000920
    DOI: 10.1016/j.eneco.2023.106594
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