Miguel Ángel Echarte Fernández

The purpose of this research is to identify and analyse the impact of socio-economic, technological and institutional factors on countries performance in terms of sustainable development. It presents a study of the structural factors that influence sustainable development using panel data from 165 countries between 2000 and 2023. The UN SDG Index Score has been modelled as a dependent variable, incorporating World Bank predictors related to access to information technology, the labour market, institutional quality, per capita income and economic inequality. Five progressive models have been estimated, applying fixed effects methodology and validating the basic assumptions of linear regression with panel data. The results are partial and subject to revision as new controls and methodological improvements are incorporated in later stages, but it has been observed that access to communication technologies and good institutional quality favour sustainable development goals, while a high level of inequality has a negative impact on these goals. First published online 5 August 2026

Reducing the risk of fraud in credit card transactions is crucial for the competitiveness of companies, especially in Latin American countries. This study aims to establish measures for preventing and detecting fraud in the use of credit cards in shops through analytical methods (data mining, machine learning and artificial intelligence). To achieve this objective, the study employs a predictive methodology using descriptive and exploratory statistics and frequency, frequency & monetary (RFM) classification techniques, differentiating between SMEs and large businesses via cluster analysis and supervised models. A dataset of 221,292 card records from a Latin American merchant payment gateway for the year 2022 is used. For fraud alerts, the classification model has been selected for small and medium–sized merchants, and the multilayer perceptron (MLP) neural network has been selected for large merchants. Random forest or Gini decision tree models have been selected as backup models for retraining. For the detection of punctual fraud patterns, the K-means and partitioning around medoids (PAM) models have been selected, depending on the type of trade. The results revealed that the application of the identified models would have prevented between 48 and 85% of fraud transactions, depending on the trade size. Despite the promising results, continuous updating is recommended, as fraudsters frequently implement new fraud techniques.

This study investigates the application of memes as a didactic tool in university-level social sciences education to address the learning needs of generation Z students. In the present study, the problem of the reduction in the academic performance of students is presented to us. With this research we have sought to contrast if the meme tool can help to give an answer to this problem. The methodology was implemented in business administration, economics, and law courses. Students were tasked with designing memes related to course content. A total of 110 memes were submitted by students, and 45 participants completed an evaluation questionnaire. Correlations and a linear regression model were used mainly for data analysis. Regarding the analysis of the results obtained in specific business subjects, where 68 students were evaluated, it should be noted that the meme variable is the second most significant variable in the final grade obtained. This data seems to indicate that, if the students have been able to synthesize part of the contents in memes, this has helped them in a better assimilation of the subject, and to pass it successfully. We certainly know that young people spend a lot of their time on platforms, and the language of memes is familiar to them. These findings suggest that memes can be an effective and engaging educational tool, offering valuable benefits in the digital age for both students and educators.

The rural environments in large parts of Europe are subject to strong demographic pressures (such as depopulation and aging) that have a negative impact on the functioning and development of these lesser-populated regions. The solution to this problem may be locating companies based on high technology, as they have great potential to transform and stimulate economic activities in various areas. The purpose of this chapter is to analyze the role of promoting technological entrepreneurship in rural areas in maintaining their populations and generating economic development opportunities as well as analyzing the tax incentive policies for start-ups in Castile and León (Spain) and the policy of promoting technology start-ups by donating space, parks, and businesses. The analysis is related to the evolution of populations and the formation of firms before and after the application of these policies. The results of the conducted research show that technological entrepreneurship in rural areas is a good strategy for repairing the populations and generating opportunities for economic development. Therefore, the promotion of start-ups can bring a significant increase in productivity in a short amount of time and contribute to the consolidation of local populations.

This article aims to analyse the asset-backing risk of stablecoins, focusing on international accounting standards, classification criteria, and auditing standards and using Tether as a case study. It examines Tether’s issuance, backing, controls, ratios, and regulations to assess risk transmission and mitigation. The results suggest a need for unified and strengthened accounting and auditing standards to enhance user confidence. Liquidity, solvency, and debt ratios were applied to Tether's balance sheets; while Tether has made efforts to increase its transparency, and although it possesses highly liquid assets, challenges remain regarding its liquidity, solvency, and debt. An independent auditors' valuation is crucial for investor confidence, demonstrating that more specific regulations are required for stablecoins. Future research should explore other stablecoins to comprehensively understand the accounting and auditing challenges in the field.

The objective of this article is to analyze the two most important monetary laws that have been implemented in El Salvador, namely the Monetary Integration Law (MIL) and the Bitcoin Law. The most important articles of both laws will be analyzed, as well as the consequences of dollarization, and the possible advantages and risks associated with the adoption of Bitcoin as legal tender. Although this measure may have some positive aspects by encouraging financial innovation and facilitating remittances, the macroeconomic risk is very high due to the volatility of this cryptocurrency. So far no positive results have been achieved as the acceptance has been very low and there has been a depreciation of the asset in recent months.

Los países de la región del Caribe, Centroamérica y Sudamérica han irrumpido con fuerza e indiscutible liderazgo en la adopción del dinero digital, ya sea apostando por las monedas digitales emitidas y respaldadas por un banco central (CBDC) o por las monedas virtuales descentralizadas (DEFI), lideradas por Bitcoin y Ether. El objetivo del artículo es identificar las razones que llevan a un país o zona monetaria a decantarse por alguno de estos sistemas. Una vez estudiadas las ventajas y desventajas del uso de las divisas virtuales centraremos el análisis en doce variables sobre el uso de dinero móvil extraídas del GFI (Global Findex Indicator) de los años 2011, 2014, 2017 y 2021 de todos estos países. El presente artículo demuestra, entre otras cuestiones, que la apuesta por un dinero digital basado en CBDC o DEFI depende más de la elección política de los dirigentes del país en cuestión que de criterios socioeconómicos.

Wilhelm Röpke (1899–1966) studied in detail the process of deglobalization experienced during the period from World War I to World War II (between 1914 and 1945). A comprehensive theory of international economic integration can be developed from his contributions. The current international context has brought these writings back to the forefront. In particular, since the onset of the Great Recession (2008), many scholars have discussed the possibility that the international economy has entered a new phase of deglobalization. The tragic events of the COVID-19 pandemic and the war in Ukraine may have accelerated any deglobalization. The aim of this chapter is to present Röpke's theory of international economic integration and to use this theory to interpret the contemporary context.

El propósito de este trabajo es mostrar una previsión del entorno económico-financiero para la Real Federación Española de Atletismo (RFEA) después del COVID19 basados en el enfoque de la Economía Austriaca. Para ello, llegamos a distintos escenarios utilizando una previsión de los ingresos de la RFEA con la versión AAA del algoritmo Exponential Triple Smoothing (ETS) e interpretamos los resultados basándonos en el enfoque de la Economía Austriaca con información sobre la situación económica española y el presupuesto del Consejo Superior de Deportes (CSD) como principal fuente de financiación. Los resultados muestran que, aunque las federaciones nacionales, como la RFEA, tengan un patrimonio neto suficiente para absorber los resultados negativos y el comportamiento responsable no se premia en esos organismos públicos o semipúblicos, el CSD debería intentar adaptar sus gastos al nuevo nivel de ingresos previstos para evitar problemas financieros mayores en el futuro. El resultado del trabajo puede servir como punto de partida para una reflexión sobre el futuro de la RFEA y de cualquier otra Federación Deportiva.

Financial inclusion, which consists of having a financial system that is easily accessible to citizens, is identified by various international organizations such as the new UN Agenda 2030, as a priority objective. This objective is particularly relevant in rural areas, where access to these services is more difficult, as citizens have to travel several kilometers to access them. In this study, we analyze the current situation of the Polish financial sector in terms of its accessibility, in order to measure the degree of financial inclusion. For this purpose, we use three combined methodologies. Initially, a data extraction from the Central Bank of Poland was carried out. Subsequently, three methodologies are applied to calculate financial inclusion. First, we apply the criteria of the Financial Access Survey (FAS) of the International Monetary Fund. Secondly, the Access to Cash Index (ACI) methodology by calculating a score that describes the access to banking services according to certain items. Finally, we applied the nearest neighbor methodology to detect in each voivodship those points where it is most difficult (measured in km distance) to access banking services. Some areas, especially in rural areas of the different voivodeships, present certain problems when it comes to accessing banking services. Therefore, the fulfillment of SDG 8.10 will be more difficult to achieve in these areas. The public authorities must pay attention to this, in order to reach the commitments acquired with the 2030 agenda, in terms of financial inclusion.