Could Cryptocurrency Policy Uncertainty Facilitate U.S. Carbon Neutrality?

Chi-Wei Su, Yuru Song, Hsu-Ling Chang, Weike Zhang and Meng Qin ()
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Chi-Wei Su: School of Businesses, Wuchang University of Technology, Wuhan 430223, China
Yuru Song: Graduate Academy, Party School of the Central Committee of the Communist Party of China (National Academy of Governance), Beijing 100091, China
Hsu-Ling Chang: Department of Accounting, Ling Tung University, Taichung 408284, Taiwan, China
Weike Zhang: School of Public Administration, Sichuan University, Chengdu 610065, China
Meng Qin: School of Marxism, Qingdao University, Qingdao 266071, China

Sustainability, 2023, vol. 15, issue 9, 1-15

Abstract: Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model; the former’s impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE; that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.

Keywords: cryptocurrency policy uncertainty; carbon neutrality; mixed-frequency data; MF-VAR model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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