This paper investigates the heterogeneous effects of tourism on economic growth within the European Union from 2000 to 2019. We employ a panel quantile regression approach to analyse how tourism’s impact varies across countries at different levels of economic development. This methodology, unlike traditional regression techniques, accounts for unobserved heterogeneity and is robust to outliers, making it particularly suitable for the diverse economic landscape of the EU. Our findings confirm the tourism-led growth hypothesis, providing evidence that tourism makes a significant contribution to economic growth, particularly in lower-growth economies. This suggests that tourism serves as a crucial “catch-up” driver, stimulating growth in countries where other economic alternatives may be scarce. Moreover, the obtained results are robust even when controlling for potential endogeneity by using a measure of GDP net of tourism. While our analysis supports the importance of physical capital and a negative effect of corruption, the impact of tourism is found to be most pronounced at lower quantiles of the growth distribution, highlighting its strategic importance for Southern and peripheral European countries seeking to boost economic prosperity.
This study investigates how business environment constraints shape firm performance using micro-level data from the World Bank Enterprise Surveys (WBES). We assess the impact of access to finance, corruption, electricity reliability, political stability, labour regulations, and infrastructure on productivity and output, measured by total factor productivity (TFP), sales per worker, value added per worker, and sales-to-labour cost ratios. To address endogeneity due to reverse causality, omitted variables, and measurement error, we employ an instrumental variables approach using two-stage least squares (2SLS) estimators. The instruments are derived from national-level indicators capturing structural economic and institutional conditions, including capital formation, inflation volatility, education quality, infrastructure, and governance. The findings show that limited access to finance, unreliable electricity supply, and corruption significantly reduce firm performance across multiple metrics. Political instability exerts no shortterm effect on productivity but adversely influences value added per worker, highlighting its long-term implications for investment and growth. Firms constrained by inadequate human capital also perform worse, highlighting the importance of financial inclusion, infrastructure development, and institutional quality. Policy efforts should focus on improving access to finance, strengthening anti-corruption mechanisms, investing in reliable infrastructure, and enhancing regulatory predictability to foster competitiveness and economic resilience.
This article examines the evolution of persistent regional unemployment disparities in the Czech Republic and asks whether district-level unemployment rates converged or diverged between 2005 and 2024. Understanding these dynamics matters for social cohesion, economic resilience, and the design of effective employment policies. The analysis applies an absolute beta-convergence framework, subsequently extended to a spatial lag specification using spatial econometric techniques. District-level unemployment data are analysed for the full period and for several sub-periods. The strongest evidence is found during the 2008-2013 downturn: both the standard and spatial models indicate crisis-driven beta-convergence, with R-2 = 0.734. Districts that entered the crisis with initially low unemployment experienced the largest relative increases, while structurally affected districts with initially high unemployment recorded the lowest relative growth, resulting in a temporary compression of inter-district disparities. By contrast, in expansionary periods the models exhibit limited explanatory power, suggesting that unemployment dynamics are less aligned with a standard beta-convergence mechanism in the absence of major macroeconomic shocks. The results underline the importance of strengthening labour-market resilience through local economic diversification, workforce reskilling, and flexibility-enhancing measures. Persistent structural disparities further point to the need for regionally differentiated policies aimed at mitigating the asymmetric regional impacts of economy-wide shocks and promoting balanced regional development.
The relevance of this research topic sustertems from the emergence of a whole range of systemic risks and threats resulting from the war in Ukraine. Russia's full-scale aggression has exacerbated existing crises and given rise to new challenges in the manufacturing, foreign trade, food, investment and innovation, and environmental sectors. The authors note that, in wartime, it is particularly important to seek ways not only to preserve but also to restore these sectors, as they form the basis for the sustainable development of the country and its regions. The aim of the article is to identify the spatial differentiation of the economic security of Ukraine's regions in wartime through the lens of the economic and environmental dimension. The study is based on a comparative analysis of key indicators (in the pre-war and wartime periods) with a particular focus on the regions of the Ukrainian Black Sea coast, which are considered the primary case study due to their strategic role and vulnerability. The state of national security is analysed across its key dimensions, particularly economic and environmental. The impact of the war, in a regional context, on the main indicators of industrial, food, investment, innovation, foreign economic and environmental security is examined. It is determined that these components collectively form the economic security of Ukraine and its territories. The use of a regional approach to analysis has enabled the authors to identify the most vulnerable 'weak spots' in individual regions and to pinpoint the factors requiring priority attention. It has been demonstrated that differentiating regions by their level of economic security enables the development of strategic documents that will take into account the specific characteristics of each region's resource base, based on their reconstruction potential and prospects for post-war development. It has been established that an important aspect of analysing the security of the country and its regions is taking into account the environmental losses and threats caused by the war, as these have long-term effects and impact the quality of life of the population. The analysis conducted enabled the authors to assess the scale of the negative impact of military operations on various aspects of economic security and to outline strategic directions for overcoming them; a set of measures has been formulated to minimise the consequences of war, restore regional activity and ensure their sustainability in the future.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Czech municipalities keep a substantial and growing volume of bank deposits. An analysis of determinants of unreserved deposits in 2021 suggests that municipalities are precautionary and accumulate fiscal reserves if they can and do so to stabilize their budget management. Signs of low activity of municipal administration such as low creation of new assets and low execution of the approved budget were not related to the volume of unreserved deposits in 2021. The change in the impact of the municipal debt on fiscal savings from strongly negative to weakly positive between 2016 and 2021 calls for more research on the impact of the introduction of new local debt regulation.
One of the EU's main priorities is to boost the competitiveness of its member states through subsidies from the European Structural Funds. As SMEs are key elements of competitiveness, their support through various subsidy programmes is important. However, as our research shows, the distribution of funds among SMEs is highly unequal. While some SMEs are very successful in obtaining subsidies, others (especially the smallest ones) are not. Using a robust dataset of Czech companies, we have identified subsidy ‘sharks‘ receiving multiple times more funds, compared to mediocre ‘salmons‘ and lowly supported ‘daces‘. While using counterfactual design with control for a subsidy dose and taking labour productivity as a proxy for competitiveness, we have found out that the subsidy dose really matters. It seems that the higher the dose, the lower the impact on competitiveness. Since, on average, subsidies led to higher competitiveness of beneficiaries, the subsidy daces significantly outpaced sharks. From a policy perspective, limiting support per beneficiary could lead to higher effectiveness of support programmes. This study also highlights the importance of the subsidy dose in evaluation practice and research.
Tony Lawson, the leading figure of the Cambridge Social Ontology Group, recently published a series of papers devoted to the question of the nature of money. These contributions have to be understood in the context of his broader approach to social ontology, the so called social positioning theory. While at first glance Lawson’s monetary ideas might appear disconnected and sometimes even contradictory or mistaken, there is a consistent vision behind them which is Lawson general social ontology. Lawson’s elaboration of the nature of money is not the only one compatible with the social positioning theory and an alternative one is briefly proposed in the paper. While systematising various Lawson’s monetary contributions, attention has been paid to several particular discrepancies and mistakes and their rectification. At the end of the paper, some lessons from analysing Lawson’s monetary contributions are drawn for his general approach to social ontology.
As the success rate of international development projects might be still below expectations, several studies have explored whether and how the use of project management (PM) tools might improve internal and external project performance. This article looks specifically at four selected Central and Eastern European countries and evaluates a newly collected data set. Based on a survey, the study examines the adoption of PM tools among project managers in the region. Furthermore, with the use of cluster analysis, it suggests that the tools are adopted progressively in four stages that differ culturally from other international studies. Last but not least, using structural equation modelling, the research indicates that among the surveyed project managers, the use of stage 1 tools might directly contribute to the improvement of internal project results and that these internal results might then have a positive impact also on the external project performance.
The research aims to analyse the influence of selected factors on the demand for urban public transport in the Czech Republic. Urban public transport is important publicly provided service worldwide. In the Czech Republic this means public ownership of transport companies and massive subsidies from municipal budgets. In line with the literature, we tested the effects of the fares, the quality of services offered, the population´s income, car ownership, the urban population´s size and employment level. Using cointegration and regression analyses of data for 2004 to 2019, we constructed unique demand models for selected cities. Our analysis revealed a positive effect of quality, fuel price (as a cost associated with car ownership), and the urban population´s size. In contrast, unemployment and the price of fares have a negative effect on demand. The income effect depends on whether the transport company operates vehicles that cope better with traffic congestion.
This article aims two EU member countries (i.e. Portugal and Germany) from different regions in Europe which have, for decades, been following common strategies regarding HSR development. The authors discuss the economic profitability vs. political aims, which were related to rail modernization. The text outlines the historic background of early railway construction, important milestones for a new level of rail planning in the 1980s and 1990s in both Portugal and Germany and delays in the realization of HSR projects, their rising costs, and the opposition of the public against the new lines. The experience of the countries under scope serves as an example for other EU members who have plans to take part in the Trans-European Transport Network.
