Implications of cryptocurrency energy usage on climate change

Dongna Zhang, Xihui Haviour Chen, Chi Keung Lau and Bing Xu

Technological Forecasting and Social Change, 2023, vol. 187, issue C

Abstract: This study investigates the environmental implications of cryptocurrency energy consumption on climate change. Using a spectrum of approaches, including Granger causality across quantiles, cross-quantilograms, and dynamic connectedness, we provide novel evidence on the nexus between Bitcoin mining and climate change. First, we find a significant Granger causality between carbon dioxide (CO2) emissions and the energy usage of Bitcoin that concentrates on the right-tail quantiles. Second, we show that the directional predictability from hash rate, blockchain size, and Bitcoin returns to Bitcoin electricity consumption is heterogeneous. We also discover significant directional predictability between the energy usage of Bitcoin mining and CO2 emissions. Third, the dynamic connectedness results show that hash rate transmits the most substantial net spillover effects to CO2 emissions and Bitcoin electricity consumption. Accordingly, hash rate exerts a major influence on Bitcoin electricity consumption and climate change. This study highlights the necessity of stimulating technological advances in developing energy-efficient decentralized finance consensus algorithms to transform the cryptocurrency market into a climate-friendly market. The results provide policy implications by emphasizing the importance of cryptocurrency ecosystem decarbonization in addressing environmental concerns.

Keywords: Climate change; Technological innovation; Cryptocurrency; Bitcoin; CO2 emissions (search for similar items in EconPapers)
JEL-codes: C21 O13 O16 O33 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:187:y:2023:i:c:s0040162522007405

DOI: 10.1016/j.techfore.2022.122219

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