HIERARCHICAL CLUSTER ANALYSIS OF BITCOIN MINING ACCORDING TO ENVIRONMENTAL AND ECONOMIC IMPACT

The spread of cryptocurrencies across the world raises many issues about their environmental and economic impact. This thesis aims to identify the best and worst countries for Bitcoin mining based on environmental and economic indicators and understand the factors contributing to their rankings. Using hierarchical cluster analysis and k-means clustering, the author finds the countries with the worst environmental conditions for Bitcoin mining and identifies countries that face certain economic problems where Bitcoin mining can partially improve those economic indicators. Based on this and existing literature, the author indicates the importance of electricity mix and energy production factor in determining environmental impact of Bitcoin mining. The research includes also an overview of Latin American and the Caribbean region in terms of their mining activity as suggested classification identified thar region as the best one for scaling Bitcoin mining industry. By providing a comprehensive overview of the economic and environmental impact of Bitcoin mining, this thesis can help policymakers make informed decisions.