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Energies 2021, 14, 4254 10 of 22 5. Discussion Electricity demand linked to cryptocurrency transactions has grown immensely in recent years. Several factors have driven this energy consumption. Among them are “the increasing difficulty in mining” and “the large number of new market participants that have been attracted by the elevated prices of this developing financial asset” [59]. There are different studies such as the one by [60] that have tried to calculate “an aggregate price of electricity derived from Bitcoin as a function of the mining locations and the prices in these locations”, others such as [15,16] point out that the price of electricity is a fundamental factor that will influence the mining decision, derived from the cost it represents. In the same vein, [61] argue that mining activities will only be profitable in those countries where the cost of electricity is lower than 0.14 USD/kWh and have the most efficient mining technology. In our study we proposed a study in which, taking into account several determinants of cryptocurrency mining, we detected those countries that would be optimal from the point of view of environmental sustainability, to carry out this activity. However, there are authors such as [15] who point out that “renewable energies will not solve the problem of Bitcoin sustainability”; and although this is possible in the long term, at least in the short or medium term, cryptocurrency mining in countries where energy is generated in a sustainable way instead of more polluting sources such as coal, will be a relief for the environment. Thus, studies such as that of [62] point out that Bitcoin mining and the potential profits derived from it can incentivize the development of wind farms or renewable and sustainable energy sources. Furthermore, [63] point out that “a sustainable energy strategy focused on the penetration of renewable energy power sources, together with the use of energy efficient mining hardware, will alleviate Bitcoin’s carbon footprint”; and according to [64], cryptocurrency mining is an opportunity for renewable energy. Along the same lines, [16] indicate that “Blockchain applications are expected to reshape the renewable energy market”. In our study to detect the most sustainable countries to carry out cryptocurrency mining activity, we used the following as variables: First, electricity prices (kWh, U.S. Dollar). These data, present the limitation that they refer to the year 2020, possibly having suffered some variation in the average price during the period until 2021. Secondly, we took the production of electricity from renewable sources (% of total) as a variable. This variable has the same limitation, and that is that it refers to the closest data, which is the year 2020, and differences may have occurred in some countries. The third variable we used was the average temperature per country in degrees Celsius. The limitation of this variable is that the 1961–1990 series was used, as we had not obtained more recent data to cover the selected sample of countries. Regarding the prohibition of mining/operation with cryptocurrencies by country, the limitation of this variable is given by the following; and that is that we have only taken as negative those countries that have “reliably” banned cryptocurrencies in their territory, but most of them have not made any pronouncement. This generates a de facto situation of illegality: it is not forbidden to operate with cryptocurrencies, but there is no clear regulatory framework either. Of the variables R&D&I research and development expenditure (% of GDP), human capital index, and most sustainable countries, we did not detect any significant limitations. Our statistical analysis sample (N) consists of 133 countries for which complete data are available, despite the fact that 144 countries appear in the initial dataset. The difference is due to missing data on the human capital index variable in several countries. After applying the regression, R-squared yields a result of 0.787. In addition, the Durbin–Watson test on our proposed model is 2.074, is very close to the value of 2, which according to this test indicates that there is absence of autocorrelation in the regression model used. Furthermore, after performing the ANOVA test, the p-value (Sig.) is less than 0.05. Therefore, the hypothesis presented can be accepted. Based on the Environmental Performance IndexPDF Image | Cryptocurrency Mining from an Economic and Environmental
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