Search Results (325)

Human development in the European Union remains uneven, and it is still unclear how economic, social, environmental, and institutional conditions jointly shape it. Understanding this question is essential for EU cohesion and sustainability policy, since Member States differ widely in governance capacity and development trajectories. This study proposes and empirically tests an extended Triple Bottom Line framework in which governance is treated as a fourth sustainability subsystem and examines its influence on the Human Development Index (HDI) in the 27 EU member states over 2000–2024 (675 country-year observations). Composite dimension indices are constructed through principal component analysis and validated with KMO and Bartlett diagnostics, and the analysis combines two-way fixed-effects models, Mundlak within–between decomposition, dynamic panels, a parsimonious system GMM estimator, and Driscoll–Kraay standard errors. The institutional dimension is the most robust positive correlate of HDI across all specifications, and its long-run effect remains significant. The environmental dimension is negatively and significantly associated with HDI, revealing a development–environment tension rather than a welfare effect, while CO₂ emissions display a positive coefficient in disaggregated models, reflecting development-stage and energy-structure effects. The economic dimension matters mainly as a long-run structural difference between countries, not as short-run within-country variation, and institutional and environmental effects are more pronounced in Central and Eastern Europe than in Western Europe. The findings imply that EU policies aimed at strengthening governance quality and supporting a just green transition—including the European Green Deal, the Recovery and Resilience Facility (RRF), and cohesion policy instruments—are central levers for sustaining human development. Full article

This study examines the transmission of monetary policy shocks across euro area economies using a Bayesian Panel Vector Autoregressive (PVAR) framework over the period 2010Q1–2024Q4. The analysis focuses on three country groups—Core, Periphery, and Central and Eastern European (CEE) economies—in order to assess whether monetary policy transmission differs across structurally distinct segments of the monetary union. Monetary policy shocks are identified using high-frequency surprises from the Euro Area Monetary Policy Database (EA-MPD). The results indicate substantial heterogeneity in monetary policy transmission across country groups. Core economies generally exhibit more stable adjustment patterns, whereas Periphery economies tend to display greater sensitivity to monetary disturbances, particularly during periods of financial stress. The CEE economies follow a distinct adjustment path associated with their structural characteristics and ongoing convergence processes. Regime-specific estimations further reveal that transmission mechanisms vary across alternative monetary policy environments, with the strongest statistically supported responses observed during the post-sovereign-debt adjustment period. Overall, the evidence indicates that monetary policy transmission within the euro area remains both structurally asymmetric and regime dependent. The study contributes to the literature by combining externally identified monetary policy shocks, Bayesian PVAR estimation, and regime-specific analysis within a unified empirical framework. Full article

This study investigates the relationships among military expenditure, economic growth, energy consumption, and carbon dioxide (CO₂) emissions using panel data for eight Central and Eastern European countries over the period 2000–2023. The analysis employs the Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) estimator to examine both the short-run and long-run dynamics. To ensure the robustness of the findings, the CS-ARDL, Common Correlated Effects Mean Group (CCEMG), and panel FMOLS estimators are additionally applied. The results of the Pedroni, Kao, and Johansen–Fisher panel cointegration tests provide robust evidence of cointegration, confirming the existence of a stable long-run equilibrium relationship among the variables. The long-run estimates indicate that military expenditure and economic growth contribute to lower CO₂ emissions, whereas higher energy consumption increases environmental degradation. In the short run, military expenditure has no statistically significant effect on CO₂ emissions, suggesting that its environmental implications emerge only over a longer time horizon. These findings imply that strategically directed investments in the defense sector, particularly those promoting environmentally friendly technologies, energy efficiency, and technological innovation, can support the alignment of national security objectives with environmental sustainability. The results provide important policy implications for Central and Eastern European countries, highlighting that coordinated policies promoting cleaner energy use, sustainable economic growth, and environmentally conscious defense modernisation can contribute to long-term environmental and economic sustainability. Full article

This article examines the impact of the EU Directive on the recognition of professional qualifications (2005/36/EC) on the development and strengthening of midwifery in countries that joined the European Union in recent decades, with a particular focus on Central and Eastern Europe. Focusing on experiences from Croatia, Poland, Slovenia, Bulgaria, and the Czech Republic, the paper explores how alignment with the Directive influenced education reform, professional recognition, and scope of practice. Drawing on the experiences presented, we argue that the Directive has functioned as more than a technical requirement for EU accession. By establishing minimum educational standards, it supported the transition from vocational to university-level education, facilitated pathways for the existing workforce to align with new qualification requirements, and contributed to the recognition of midwifery as a distinct regulated profession. It also provided a clear framework for defining midwives’ competencies and scope of practice within health systems, acting both as a protective mechanism, by safeguarding professional standards, autonomy, and professional identity, and as an enabling framework by supporting workforce development, educational reform, and the integration of midwives into health systems during periods of institutional transition. The lessons drawn from these national experiences can inform the ongoing update of the Directive, led by the EU Commission, by illustrating how legislative alignment can strengthen midwifery education and professional recognition, while also supporting countries undergoing or preparing for EU accession. Full article

The study examines the evolution and convergence of the agricultural share in GDP across seven Central and Eastern European countries (Bulgaria, Croatia, the Czech Republic, Poland, Romania, Slovakia, and Hungary) over the period 1995–2024. The main objective is to assess the structural transformation of the agricultural sector and to test the existence of regional convergence. The methodological framework combines descriptive statistics, the Shapiro–Wilk normality test, Spearman correlation analysis, cluster analysis using the Ward method, σ-convergence, β-convergence and ARIMA models for medium-term forecasting. The results reveal a clear downward trend in the agricultural share of GDP across all analysed economies, confirming ongoing processes of modernization and structural reorientation. At the beginning of the period, Romania and Bulgaria exhibited relatively high levels and pronounced volatility, whereas the Czech Republic and Slovakia recorded lower and more stable shares. Over the long term, a significant convergence process becomes evident, as cross-country differences gradually narrow, with most economies recently falling within the range of 1.5–3.5% of GDP. Spearman correlations indicate strong regional synchronization, with the exception of Slovakia, which emerges as an atypical case. Augmented Dickey–Fuller tests confirm that the series are integrated of order one, while the selected ARIMA specifications demonstrate satisfactory predictive performance. Forecasts for 2025–2028 suggest a continued decline or stabilization of the agricultural share in GDP. Overall, the findings confirm the existence of a robust process of structural convergence in the region and provide empirical support for the design of agricultural and economic policy frameworks. Full article

Reducing carbon emissions has become a central objective of sustainable development policies as countries seek to address the environmental challenges associated with climate change and resource depletion. In this context, circular economy practices and energy transition policies have emerged as key mechanisms for achieving environmental sustainability. This study examines the determinants of carbon emissions within the framework of the circular economy and energy transition for selected Central and Eastern European countries (Romania, Poland, Hungary, Bulgaria, Slovakia, and Slovenia) over the period 2010–2024. Using panel data analysis, the study incorporates key variables including circular economy, economic growth, recycling, renewable energy consumption, and urbanization. To enhance the reliability of the empirical estimates, panel unit root tests, the Hausman specification test, fixed-effects estimation, and Driscoll–Kraay robust standard errors are employed to address heteroskedasticity, serial correlation, and cross-sectional dependence. The results indicate that improvements in circular economy practices together with greater renewable energy use are associated with lower carbon emissions, providing empirical support for the proposed hypotheses. Recycling activities are found to increase emissions in the short run, indicating energy-intensive processes. In contrast, the effects of economic growth and urbanization are found to be context-dependent, providing only partial support for the related hypotheses. Overall, the results highlight that carbon emission dynamics are shaped by a complex interaction of economic, structural, and environmental factors, and that policy effectiveness depends on country-specific conditions. By focusing on transition economies in Central and Eastern Europe, this study extends the existing literature through an integrated panel data analysis of circular economy and energy transition policies and offers policy-relevant evidence for the region. Full article

The article examines the level of concentration in the ESG bond market in Central and Eastern European (CEE) countries over the period 2020–2025. The aim of the study is to assess the structure of this market in terms of value, volume, product composition, and sectoral distribution. The analysis employs the Herfindahl–Hirschman Index (HHI), which enables the measurement of concentration levels across the respective dimensions. The data are sourced from the Environmental Finance Data database. The results indicate that the ESG bond market in the CEE region is characterized by a high degree of geographical concentration, with the dominance of a limited number of countries, namely Poland, the Czech Republic (Czechia), and Hungary. At the same time, a very strong product concentration persists. Green bonds play a predominant role, while other types of instruments remain of limited significance. A high level of concentration is also observed in the structure of issuers and economic sectors. Despite an increase in both the value and number of issuances, no clear diversification of the market has occurred. The findings suggest that the development of the ESG bond market in CEE countries is uneven and is concentrated around a limited number of participants and market segments. Full article

The study analyses the determinants of national competitiveness in Central and Eastern Europe, with a primary focus on the role of human capital. The primary objective of this study is to identify disparities in the levels of competitiveness and human capital between the V4 countries and other countries in the Central and Eastern European region. The subsequent objective is to identify the impact of year-on-year changes in human capital on competitiveness across the entire region under study in the context of other key macroeconomic and institutional determinants. In the comparative section of the study, a panel regression model with random effects and robust standard errors according to Arellano was utilized. Conversely, a model with fixed effects and robust standard errors (PCSE), employing first differences of variables with a two-year lag, was employed to identify the determinants of competitiveness. The findings of the comparative analysis demonstrated the presence of statistically significant disparities between the V4 countries and other countries in the Central and Eastern European region, exclusively in the domain of human capital. The level of competitiveness is similar across the entire region. The findings of the panel regression analysis demonstrated that year-on-year changes in the quality of human capital do not exert a statistically significant impact on the WCI with a two-year lag. This finding contradicts the theoretical assumptions that underpin the WCI. The predominant factors influencing competitiveness were identified as the control variables of government effectiveness, the inflation rate, and the level of gross debt. The originality of the study lies primarily in the use of a comprehensive WCI instead of partial competitiveness indicators and in the integration of multiple institutional and macroeconomic aspects into the model, thereby filling an existing gap in literature. Full article

This paper aims to assess the relationship between foreign direct investment (FDI) and economic development/employment rate over the period 2013–2023 for Romania, as well as for other European Union country groups (Central and Eastern Europe, Northern and Western Europe and Peripheral Europe). In this respect, we used the Panel FEGLS method adjusted with cross-section SUR and found a positive relationship between FDI and Gross Domestic Product (GDP) per capita for all panels, the strongest estimated relationship being identified for Romania (followed by the one specific to Central and Eastern European states), considering the important role of the level of economic development in shaping these differences. Regarding the relationship between FDI and employment rate, we also found positive coefficients, the highest ones being identified for Central and Eastern Europe and Romania. However, the weakest estimated relationship between FDI and GDP per capita/employment was identified for the Peripheral Europe countries. Full article

This study assesses the impact of research and development (R&D) tax incentives on the intensity of business R&D expenditure in Central and Eastern European countries and derives policy implications for Ukraine. The analysis uses a balanced panel of 11 new EU member states covering the period 2010–2023, based exclusively on officially published data. The main method is a two-way fixed-effects panel regression with country and year effects, clustered standard errors, alternative lag structures, heterogeneity analysis and robustness checks. The baseline specification shows that a 0.10 increase in the implicit subsidy rate is associated with an approximately 0.10 percentage point increase in Business Expenditure on R&D (BERD) to GDP two years later. However, the effect is strongly conditional on absorptive capacity: it is statistically significant in countries with a developed R&D base and practically absent in countries with a weak base. The estimated private R&D additionality ratio falls below one under the stated assumptions, indicating that the estimated effect does not imply more than one unit of additional private investment per unit of fiscal support. For Ukraine, the results support a gradual introduction of R&D tax incentives combined with structural measures that strengthen human capital, institutional capacity and links between science and business. Full article

The expansion of the European Union Emissions Trading System to road transport and buildings (ETS2) raises significant concerns regarding the distributive social impacts of carbon pricing on vulnerable households, particularly in regions characterized by high car dependency, limited public transport accessibility, and pronounced territorial inequalities. This paper aims to develop an integrated conceptual framework for analyzing transport poverty in the context of ETS2 and the just climate transition. The study adopts a conceptual–analytical approach based on a structured literature review of peer-reviewed publications and EU policy documents, combined with a qualitative policy analysis focused on Bulgaria as a critical case. The paper identifies six interacting analytical dimensions of transport poverty—economic vulnerability, spatial vulnerability, mobility dependency, infrastructure vulnerability, climate-policy exposure, and social vulnerability—and maps the causal pathways through which carbon pricing mechanisms may intensify mobility deprivation, particularly among low-income, rural, and forced-car-ownership households. The analysis demonstrates that ETS2 may exacerbate existing socio-spatial inequalities unless accompanied by well-designed compensatory, accessibility-oriented, and territorially sensitive policy measures. The Bulgarian case illustrates the specific structural risk factors prevalent in Central and Eastern European countries. The paper contributes to the emerging academic literature on transport poverty by positioning it as a critical dimension of the just climate transition and by providing a conceptual foundation for future empirical research within the ACTETS2 project framework. Full article

This study examines whether digital capabilities constitute a necessary condition for green innovation and firm competitiveness in the context of increasing sustainability and digital transformation pressures. Although prior research frequently links digitalization to improved environmental and business outcomes, limited evidence exists on whether firms must achieve a minimum level of digital capability to successfully generate green innovation and sustain competitive performance. To address this gap, the study investigates the relationships among digital capabilities, green innovation, and firm competitiveness using Partial Least Squares Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA). Using survey data from 740 firms across Hungary, Romania, Poland, Austria, and other Central and Eastern European (CEE) countries, the findings demonstrate that digital capabilities significantly enhance both green innovation and firm competitiveness. Green innovation further acts as a mediating mechanism through which digital capabilities translate into superior competitive outcomes. Importantly, the NCA results reveal that digital capabilities are not merely beneficial but represent a necessary condition for achieving high levels of green innovation and competitiveness within the studied sample of CEE firms, suggesting a threshold relationship that warrants further causal investigation. Firms with higher digital maturity consistently outperform less digitally developed firm. Firms with higher digital maturity consistently outperform less digitally developed firms in leveraging sustainability-oriented innovation strategies. The study contributes to the literature by advancing understanding of how digital transformation capabilities support sustainable competitiveness and by combining sufficiency and necessity analytical approaches to examine these relationships. The findings also provide practical implications for managers and policymakers by highlighting the strategic importance of investing in digital capabilities to simultaneously support environmental sustainability and long-term competitive performance. Full article

This paper investigates the relationship between green vocational education and training (VET), structural economic features, and green employment in Central and Eastern European (CEE) economies. For the purpose of the research, an initial database covering the post-2010 period was assembled from Eurostat and related statistical sources. Due to data availability and cross-country comparability constraints, the final empirical analysis employs a balanced panel of six EU Member States covering the period 2018–2022. The empirical analysis employs pooled OLS and fixed-effects estimators over the period 2018–2022, following a stepwise modeling strategy to assess baseline relationships and robustness. The results show that VET enrollment alone is not a reliable predictor of green employment growth, while VET graduation rates exhibit a more consistent—yet not robust—association once country-specific heterogeneity is controlled for. By contrast, structural reliance on industrial sectors is consistently linked to lower green employment shares, while environmental tax revenues demonstrate modest positive effects. Overall, the findings suggest that green employment dynamics are driven primarily by structural and macroeconomic conditions rather than by skill formation alone. The study contributes to the literature on the green transition by providing an integrated perspective on the interaction between skills, structural transformation, and policy incentives in shaping sustainable labor market outcomes. Full article

This study examines how individual political predispositions and national mobilisation contexts jointly structure protest participation in contemporary Europe across the pre-pandemic, pandemic and post-pandemic periods. Using data from Rounds 9, 10 and 11 of the European Social Survey (2018–2023), the analytical sample includes 106,106 respondents from 33 countries. Descriptively, protest participation remains a minority behaviour, yet displays pronounced cross-national heterogeneity, with participation rates ranging from below 3% in several Central and Eastern European countries to nearly 20% in the most mobilised contexts and remains remarkably stable across rounds at approximately 8.5%. Building on resource mobilisation theory, political process approaches and New Social Movements perspectives, the analysis conceptualises protest participation not as an isolated behavioural act but as the outcome of interactions between individual resources, evaluative orientations toward democratic institutions and broader mobilisation environments. Logistic regression models, country fixed-effects specifications and multilevel models with random intercepts are used to assess these relationships. At the individual level, political engagement emerges as the strongest predictor of participation: higher political interest is associated with substantially higher protest propensity, while ideological self-placement indicates lower participation among respondents positioned further to the right. Younger age and higher education also increase participation. Lower satisfaction with democracy and stronger perceptions of inequality are consistently associated with protest behaviour, supporting grievance-based interpretations linked to democratic evaluations rather than material deprivation alone. Country fixed-effects and multilevel models confirm that these individual-level associations are robust within countries, while significant between-country variation persists (random-intercept SD = 0.554), indicating that national mobilisation environments shape baseline levels of protest participation. Multilevel results further reveal that protest participation was significantly lower during the pandemic period (Round 10) relative to the pre-pandemic baseline, with only partial recovery in the post-pandemic period. A cross-round comparison demonstrates that the core individual-level associations are stable across all three periods, indicating that these relationships reflect durable structural patterns rather than dynamics specific to any particular mobilisation cycle. Beyond this overall stability, the analysis identifies two theoretically informative exceptions: subjective financial difficulty is significant only in the pre-pandemic period and gender differences in protest participation attenuate over time—patterns consistent with broader shifts in protest repertoires during and after the pandemic. These findings make three contributions to the comparative literature on contentious politics. First, by extending the analysis across three ESS rounds, the study demonstrates the temporal robustness of individual-level determinants of protest—an empirical question rarely addressed in the existing literature. Second, the multilevel design with round fixed effects allows for direct estimation of pandemic-related suppression and post-pandemic recovery in protest activity at the aggregate level. Third, the cross-national scope and temporally structured comparison provide new evidence on how individual political predispositions interact with shifting mobilisation environments across a period of exceptional socio-political strain in Europe. Full article

Background/Objectives: Multidrug-resistant tuberculosis (MDR-TB) remains a major public health challenge in the WHO European Region, which reports the highest global proportion of rifampicin-resistant and MDR-TB cases. Whole-genome sequencing (WGS) has emerged as a key tool for improving drug-resistance detection and supporting molecular surveillance. However, the level of genomic implementation across Central and Eastern Europe (CEE) remains insufficiently characterized. This scoping review aimed to evaluate the use of WGS for MDR-TB in CEE countries and to classify implementation maturity using a predefined framework (L0–L4). Methods: A structured search of PubMed/MEDLINE and Web of Science identified original studies published in English between 2015 and 2026 reporting genomic applications in MDR-TB across 13 predefined CEE countries. Data were extracted on sequencing approaches, resistance prediction, transmission analysis, monitoring of new or repurposed drugs, bioinformatic pipelines, and programmatic integration. Countries were categorized according to a five-level maturity model based on documented capacity, scope of application, and integration into national tuberculosis programs (NTPs). Results: Twenty-eight studies were included. WGS was used in 23/28 studies (82.1%), predominantly for genomic resistance prediction (25/28). Transmission analysis was reported in 19/28 studies, with heterogeneous single nucleotide polymorphism (SNP) thresholds and clustering methodologies. Monitoring of resistance to new or repurposed drugs was described in 8/28 studies. No country achieved Level L4 (formally integrated genomic surveillance). Four countries were classified as L3 and nine as L2, while no L0 or L1 settings were identified. Conclusions: Countries in Central and Eastern Europe demonstrate increasing operational use of WGS for MDR-TB, primarily driven by clinical resistance prediction. However, the lack of formal integration into national surveillance systems highlights a persistent gap between technological adoption and structured public health implementation. Strengthening programmatic integration and methodological standardization is essential for advancing genomic surveillance of MDR-TB in the region. Full article