ABSTRACT In this paper, cointegration and causality relationship among human development (HDI), financial development (FDI) and sustainable development (ESG) for five CEECs are investigated. In the study covering the period 1990–2022, Hatemi-J (2008) test was used to investigate cointegration relationships. The results revealed the existence of a long-term relationship between FDI-ESG and HDI-ESG variables in four countries except the Czech Republic. In the causality analysis, Enders and Jones’s (2016) Fourier Granger causality and Gormus et al. (2018) Fourier Toda and Yamamoto tests were first applied. The findings provide strong evidence that human capital has an effect on sustainable development. On the other hand, findings that financial development has an effect on sustainable development were seen only in Romania. However, strong evidence has been obtained in Romania, Hungary and Bulgaria that sustainable development has an impact on financial development. In the last stage, Hatemi-J (2012, 2014) asymmetric causality test, which takes into account the effects of positive and negative cumulative shocks in the causal relationships, was used. In all countries except Poland, causality from positive shocks in HDI to ESG was found. The relationships between FDI and ESG are more limited and complex. This study contributes to the literature by investigating the symmetric and asymmetric relationships between ESG-FDI and ESG-HDI within the scope of CEEC and provides original policy implications based on the findings obtained at the country level.

ABSTRACT This article examines the underlying motives behind the United States’ trade and technological conflict with China since 2018. While the measures undertaken—ranging from tariffs and export controls to investment screening and industrial policy—are often interpreted through the lens of economic protectionism, this paper argues that standard economic theories fail to account for their full scope, intensity, and strategic focus. The article systematically evaluates four leading economic explanations for protectionist behavior—trade balance correction, commodity structure of trade upgrading, terms of trade manipulation, and strategic trade policy—and demonstrates their limitations in explaining the U.S.–China case. It then proposes an alternative analytical framework that integrates realist international relations theory with a modified version of the mercantilist perspective on the commodity structure of trade which incorporates a retaliatory mechanism. This interdisciplinary approach better captures the combined geopolitical and economic underpinnings of U.S. protectionist policies aimed at China, in particular efforts to curb China’s technological rise in semiconductors and dual-use sectors. This interdisciplinary approach contributes to the literature on economic statecraft by incorporating national security concerns into trade policy analysis.

ABSTRACT Since the 1990s, the Czech Republic has witnessed a significant increase in educational attainment, leading to a rise in educational mismatch. This study investigates the prevalence of vertical and horizontal educational mismatch using data from surveys conducted in 2011 and 2022 on Czech prime working-age employees. It provides insights into the evolving dynamics of educational mismatch, identifies the groups of employees most vulnerable to it, and offers suggestions to mitigate this phenomenon, improve labour market outcomes, and optimize the returns to educational investment. The analysis reveals a growing trend of overeducation over the past decade, particularly among women. In addition, substantial differences were found across fields of study. Fields such as the arts and humanities show high levels of both types of educational mismatch, while education and healthcare demonstrate better alignment. The findings – indicating that approximately half of the employee population experiences some form of educational mismatch – underscore persistent inefficiencies in the allocation of educational resources and highlight the private and societal costs associated with overeducation. Overeducated labour represents a strategic reserve of human capital that could facilitate the shift towards a digital and knowledge-driven economy – yet unlocking this potential will require targeted efforts to align qualifications with future labour market needs.

ABSTRACT This article aims to provide new and robust evidence of the effect of air pollution on migration at the level of 70 European cities in the period 2004–2019. We use factor and regression analysis and panel data conducted from Eurobarometer, Eurostat, national statistical offices, and the European Environment Agency. We set a unique approach to examine human migration as we look for a connection between the perceived quality of air of city inhabitants and net migration. The results show that both perceived quality of air and objectively measured pollution can be considered as migration factors. Moreover, we examined that, in general, Eastern European cities attract more migrants than Western European cities and that seaside cities lose more inhabitants due to migration than inland cities, but these differences are not connected to air pollution and thus can be contributed to other non-observed factors.

ABSTRACT The purpose of this study is to identify the most effective supervised machine learning models for predicting the financial performance of companies listed on the BIST100 index. In the rapidly evolving field of financial forecasting, machine learning techniques offer robust predictive capabilities. This research evaluates a range of supervised models, including Tree-Based Models (Decision Trees, Bagging, Random Forests, Adaboost, Gradient Boosting Machine (GBM), Light-GBM, XGBoost, CatBoost), Neural Network-based Models (Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTM)), and Instance-based Learning Models (K-Nearest Neighbors (KNN) and Support Vector Machines (SVM)). The models’ performance is assessed using comprehensive error metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and relative Root Mean Squared Error (rRMSE). The findings reveal that no single machine learning model consistently outperforms others across all companies in the BIST100 index. However, models like XGBoost and Random Forests demonstrate strong and consistent performance, making them particularly effective for financial performance forecasting. Furthermore, deep learning models such as CNNs, RNNs, and LSTMs show promising results, especially for certain firms. The research highlights key insights for investors and financial analysts seeking to leverage machine learning for data-driven decision-making in the Turkish stock market. This study offers a unique contribution to the field by applying and comparing advanced machine learning techniques in the context of the BIST100 index. It provides actionable insights for improving financial prediction accuracy and offers a foundation for further research in other stock market contexts.

Abstract The role of foreign exchange interventions in monetary policy conduct is an ongoing debatable issue, especially in inflation-targeting emerging economies, where monetary authority can follow other targets rather than price stability. This paper examines whether interventions in foreign exchange markets affect the setting of interest rates in countries where price stability is the main target of monetary policy. We used the ARDL model to investigate the matter of the intervention policy as well as its asymmetric impacts on monetary policy. The results provide evidence of the significant effect of foreign exchange interventions on monetary policy in inflation-targeting emerging economies, implying the existence of fear of floating. Particularly, interest rate changes can mitigate or accommodate the intervention policy, depending on countries. Furthermore, the interventions have asymmetric effects on monetary policy, showing the bias toward sales interventions. While sales interventions play a more pronounced effect in most emerging economies, excepting for Mexico where purchase intervention effect is of more importance.

Abstract The concept of a hierarchy of money or the idea that a number of instruments constitute money and that they are hierarchically related to one another is relatively recent and yet quite widespread. However, it is argued, that its comprehension differs. The most elaborated cases in which differing treatments of the term can be found are Modern Money Theory (MMT) and the Money View. At first sight, the MMT’s model of money hierarchy focuses on a hierarchy within a specific unit of account whereas the Money View perceives hierarchy not only within an individual unit of account but also across various units of accounts. But, as is shown, differences are more fundamental. It is argued that different comprehension can be explained by the different distinctions between money and credit and concept of monetary sovereignty within each approach rather than the concept of hierarchy itself. The concept of hierarchy acts, in fact, as a framework that ensures consistency in the use of different money instruments on those level.

Abstract Education is a key area that should matter to the whole society. Measuring efficiency in education is a widely discussed academic and professional topic. The presented article focuses on investigating the efficiency of 57 elementary schools in the city of Bratislava. We used a two-step approach. In addition to measuring the output efficiency of elementary schools through the analysis of the non-parametric Data Envelopment Analysis method (DEA) with variable returns of scale (VRS), we also performed regression analyses to examine the connection between contextual variables and the measured output efficiency. The analysis shows that the achieved output efficiency is positively associated by the technical equipment of schools, staff in schools and the establishment (prestige) of schools in society. We noted a negative association with the number of students with special needs. Our findings can serve the city administration, as they can largely influence the monitored parameters by their own decision.

Abstract Examining the relationship between sustainability and economic development was covered by research over the past decades. The initial goal of the present research is to evaluate the contribution of renewable energy sector value added to the national economic development in Denmark. The research tasks of this study include assessment of carbon dioxide allowances and environmental taxation as well as the effect of other factors in terms of their contribution to the economic growth. The application of the regression analysis in order to examine the relationship between renewable energy industry and national economic development in Denmark shows that the increasing of renewable energy value added leads to the sizeable expansion of the gross domestic product. From the environmental-economic standpoint this is presumably the first research to make unambiguous conclusion, that proves significance of renewable energy value added for economic development in Denmark. Likewise, the results of the present study prove that expanding usage of carbon dioxide (CO₂) allowances in Denmark leads to quite considerable increase of the gross domestic product. Besides that, this study provided evidence regarding positive and statistically significant impact of the other factors on the economic growth.

Abstract Great differences are observed in the way of living, the quality of living, and the type of property ownership in individual countries of the world. However, housing affordability is currently a significant issue in every developed country. At the same time, it is also an important factor of economic development on both the national and regional level. The paper is focused on the comparison of housing affordability in the Czech and Polish regions. The presented research combines four different commonly used indicators of housing affordability (financial and physical) into a newly defined index and applies it to the Czech Republic and Poland regions for the period 2020-2022. The aim is the comparison of Czech and Polish regions according to the selected housing indicators and calculated standard housing affordability index SAI, which is a newly created index compiled by the authors. The result of the research is a calculation of housing availability in a total of 30 Czech and Polish regions and a comparison of the development of housing availability in 2020 and 2022 in these regions. The result of the research is the finding that the availability of housing in the Czech regions is on average lower than in the Polish regions and, in addition, that the availability has decreased compared to 2020 in both the Czech and Polish regions by 2022.