This article analyzes the current situation of Central Bank Digital Currencies (CBDCs), which are digital currencies backed by a central bank. It introduces their current status, and how several countries and currency areas are considering their implementation, following in the footsteps of the Bahamas (which has already implemented them in its territory), China (which has already completed two pilot tests) and Uruguay (which has completed a pilot test). First, the sample of potential candidate countries for establishing a CBDC was selected. Second, the motives for implementing a CBDC were collected, and variables were assigned to these motives. Once the two previous steps had been completed, bivariate correlation statistical methods were applied (Pearson, Spearman and Kendall correlation), obtaining a sample of the countries with the highest correlation with the Bahamas, China, and Uruguay. The results obtained show that the Baltic Sea area (Lithuania, Estonia, and Finland) is configured within Europe as an optimal area for implementing a CBDC. In South America, Uruguay (already included in the comparison) and Brazil show very positive results. In the case of Asia, together with China, Malaysia also shows a high correlation with the three pioneer countries, and finally, on the African continent, South Africa is the country that stands out as the most optimal area for implementing a CBDC.

The great advances produced in the field of artificial intelligence and, more specifically, in deep learning allow us to classify images automatically with a great margin of reliability. This research consists of the validation and development of a methodology that allows, through the use of convolutional neural networks and image identification, the automatic recycling of materials such as paper, plastic, glass, and organic material. The validity of the study is based on the development of a methodology capable of implementing a convolutional neural network to validate a reliability in the recycling process that is much higher than simple human interaction would have. The method used to obtain this better precision will be transfer learning through a dataset using the pre-trained networks Visual Geometric Group 16 (VGG16), Visual Geometric Group 19 (VGG19), and ResNet15V2. To implement the model, the Keras framework is used. The results conclude that by using a small set of images, and thanks to the later help of the transfer learning method, it is possible to classify each of the materials with a 90% reliability rate. As a conclusion, a model is obtained with a performance much higher than the performance that would be reached if this type of technique were not used, with the classification of a 100% reusable material such as organic material.

There are different studies that point out that the price of electricity is a fundamental factor that will influence the mining decision, due to the cost it represents. There is also an ongoing debate about the pollution generated by cryptocurrency mining, and whether or not the use of renewable energies will solve the problem of its sustainability. In our study, starting from the Environmental Performance Index (EPI), we have considered several determinants of cryptocurrency mining: energy price, how that energy is generated, temperature, legal constraints, human capital, and R&D&I. From this, via linear regression, we recalculated this EPI by including the above factors that affect cryptocurrency mining in a sustainable way. The study determines, once the EPI has been readjusted, that the most sustainable countries to perform cryptocurrency mining are Denmark and Germany. In fact, of the top ten countries eight of them are European (Denmark, Germany, Sweden, Switzerland, Finland, Austria, and the United Kingdom); and the remaining two are Asian (South Korea and Japan).

This study analyses the current debate around central bank-backed digital currency (CBDC). A comparative study was carried out considering countries for and against implementing a CBDC and their reasons, looking for common causes, differences, etc. The conclusion was that there are opposite tendencies between defenders and detractors of establishing a CBDC. However, today—and taking into account the positions of three large banking institutions (the Federal Reserve of the United States of America, the Bank of Japan and the Bank of England) on establishing (at least in the short term) a CBDC)—it seems that large-scale implementation is still far off. On the contrary, the Chinese Central Bank and banking systems of other countries that have less weight in the world, such as Uruguay, Lithuania and the Bahamas, seem to go against the trend of rejection and are seriously considering its implementation. Although this matter has been dealt with in the theoretical field, more pilot tests such as the one carried out by Uruguay are necessary in order to understand specific effects on the economy, on one hand, and on acceptance of its use by the population, on the other.

The rise of digital technologies and their educational applications increasingly require the development of digital skills among university faculty. This study focuses on examining the level of digital competencies of university faculty and identifying their conditioning factors. To achieve this objective, an ex post facto methodological design with surveys is used. A sample of 216 university teachers from different regions of Ecuador was used. The non-parametric Chi-square test was used to validate the hypothesis of independence of the variables. The results obtained show that university faculty have a mostly intermediate level of digital skills, which is independent of gender, but dependent on the generational cohort. In particular, it is found that younger teachers (millennials) have a more advanced level of digital skills, although this relationship is not very strong. On the other hand, we observe the positive influence of the university’s strategic leadership in terms of technological adoption on the development of teachers’ digital skills. Universities with better technological resources and with training plans focused on the pedagogical application of technology have teachers with a more advanced level of digital skills. All of this leads to the recommendation that education policies should prioritise actions that promote the development of digital competencies among university faculty

This article analyzes the monetary policy of major central banks during the economic crisis generated by the COVID-19 pandemic. Rising public debt in many countries is being financed through asset purchases by monetary authorities. Although these stimulus policies predate the pandemic, they have been significantly boosted as many governments face large financing needs. We have been in a low interest rate environment for years and some governments have issued debt securities at negative rates. In addition, the rise of decentralized cryptocurrencies, based on blockchain technology, has created greater competition in the international monetary system and many governments have considered the creation of centralized virtual currencies, known as central bank digital currencies (CBDCs). We will analyze some relevant cases, with an emphasis on the digital euro project. The methodology is based on the analysis of the evolution of monetary variables. Pearson’s correlation will be used to establish some relationships between them. There is a strong similarity in the expansionary monetary policies of central banks. Although the growth of the money supply has not been passed on to the CPI, it has been passed on to the financial markets and the price of assets such as Bitcoin or gold.