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The environmental consequences of blockchain technology: A Bayesian quantile cointegration analysis for Bitcoin

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  • Michael L. Polemis
  • Mike G. Tsionas

Abstract

In recent years, there is a widespread belief among researchers and academicians that Bitcoin usage is imposing an additional burden on the environment inducing climate change. Although several studies have focussed on issues related to the energy consumption of the basic cryptocurrencies, an open question remains regarding the environmental depiction of Bitcoin. By resorting to Bayesian analysis and quantile cointegrated vector autoregression (CQVAR), this study seeks to disentangle the driving forces that shape the carbon footprint of Bitcoin. The sample used in the empirical analysis consists of a daily panel dataset covering 50 countries over the period 2016–2018. The empirical findings corroborate a causal effect between the use of Bitcoin and its underlying carbon dioxide emissions generated by the increasing energy load. The CQVAR is associated with positive marginal posterior means for most of the covariates of the model across all the estimated quantiles. In contrast, there is a negative and statistically significant relationship between Bitcoin miner's revenue and carbon emissions, uncovering a multimodal distribution pattern of the marginal posterior densities which is stronger at higher than in lower quantiles. This finding suggests that the lower (higher) miner's Bitcoin revenues, the more abrupt (gradual) the effect on environmental degradation. Therefore, a sustainable energy strategy focussing on the penetration of renewable energy sources along with the use of energy‐efficient mining hardware will alleviate the carbon footprint of Bitcoin.

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  • Michael L. Polemis & Mike G. Tsionas, 2023. "The environmental consequences of blockchain technology: A Bayesian quantile cointegration analysis for Bitcoin," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1602-1621, April.
    • Handle: RePEc:wly:ijfiec:v:28:y:2023:i:2:p:1602-1621
    DOI: 10.1002/ijfe.2496
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