Search Results (17,865)

Exchange rate volatility has intensified in recent decades, yet its systematic implications for banking-sector stability remain contested. This study investigates whether exchange rate volatility constitutes a meaningful source of financial fragility using a global panel of 103 countries over the period 2000–2021. Financial stability is proxied by the banking-sector Z-score, while exchange rate volatility is estimated using a EGARCH-based framework to capture time-varying uncertainty. To address cross-sectional dependence, heterogeneity, and endogeneity, the analysis employs Driscoll–Kraay fixed effects, two-step system GMM, and quantile regressions. The results reveal that exchange rate volatility exerts a statistically and economically significant negative effect on banking stability, reducing Z-scores across countries and income groups. The findings remain robust across alternative specifications and estimators. Bank-level fundamentals—capitalisation, liquidity, and credit—enhance stability, whereas higher non-performing loans and risk exposure amplify fragility. Macroeconomic conditions also matter, with stronger growth, institutional quality and external balances supporting resilience, while inflation, economic policy uncertainty and expansionary government spending weaken stability. By integrating time-varying volatility modelling with dynamic panel techniques in a large cross-country setting, this study provides new global evidence that exchange rate volatility is not merely a macroeconomic fluctuation but a structural source of banking-sector risk. The findings carry important implications for macroprudential policy, foreign-exchange management, and coordinated monetary–fiscal responses aimed at safeguarding financial stability in open economies. Full article

This study investigates the determinants of GDP per capita across 26 European Union member states over the period of 2006–2024, with a particular focus on entrepreneurship, institutional quality, and macroeconomic factors. Given the presence of long-run income differences across EU countries, the analysis explicitly accounts for structural heterogeneity in economic development and institutional capacity. To ensure robust estimation in the presence of cross-sectional dependence and slope heterogeneity, the study employs advanced panel econometric techniques, including tests for cross-sectional dependence, unit roots, and cointegration. Long-run relationships and short-run dynamics are estimated using the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model, complemented by robustness checks based on the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators. In addition, the Method of Moments Quantile Regression (MMQR) is applied to capture heterogeneity across different points of the income distribution, thereby reflecting long-run income disparities among EU member states. The empirical results confirm the existence of a stable long-run equilibrium relationship among the variables. The baseline CS-ARDL estimates indicate that institutional quality, entrepreneurial activity, trade openness, and government expenditure exert positive and statistically significant effects on GDP per capita, while financial development exhibits a negative effect and foreign direct investment remains insignificant. In the short run, entrepreneurship and trade openness contribute positively to GDP per capita, whereas government expenditure and credit expansion generate contractionary effects. The robustness analysis using AMG and CCEMG estimators largely supports these findings, as the direction of the coefficients remains consistent across alternative specifications, although some variation in statistical significance is observed due to differences in the treatment of cross-sectional dependence and unobserved common factors. The MMQR results further reveal substantial heterogeneity across the income distribution, indicating that the effects of key determinants vary depending on countries’ long-run income levels. In particular, trade openness and institutional quality exert stronger positive effects in lower-income quantiles, while the adverse effects of excessive financial development are more pronounced in higher-income quantiles. Overall, the findings underscore the importance of promoting productive entrepreneurship, strengthening institutional frameworks, facilitating trade integration, and ensuring efficient financial intermediation to enhance GDP per capita within the European Union. The results also highlight the need for differentiated policy approaches that explicitly account for long-run income heterogeneity, structural differences, and varying institutional capacities across EU member states. Full article

The construction industry is one of the major sources of carbon emissions, and green retrofitting of buildings is an effective pathway to promoting sustainable development in the sector. However, existing research and implementation strategies often struggle to reconcile the needs of governments, businesses, and residents. Therefore, this study proposes a comprehensive research framework that employs bibliometric and text analysis methods to examine implementation barriers in retrofitting projects across four dimensions: policy, cost, technology, and resident satisfaction. The results indicate that retrofitting costs are the primary factor, while technology is a secondary factor. Furthermore, existing policies feature vague technical standards, insufficient incentives, and a lack of differentiation. Conflicts of interest and challenges regarding cost allocation persist throughout the renovation life cycle. Decision-support tools and renovation technologies face limitations and issues regarding applicability. Residents face constraints from multiple factors, including their knowledge base and economic capacity. Based on these findings, the government urgently needs to improve a differentiated policy system and encourage technological R&D and knowledge dissemination. Enterprises must actively respond to policies and optimize their technologies and management practices. Residents need to enhance their energy-saving awareness, participate in retrofitting efforts, and improve their energy consumption behaviors. Full article

This study examines how the allocation of export expansion across sectors affects economy-wide outcomes in Bangladesh. Using a Social Accounting Matrix (SAM) framework, we combine linkage analysis with simulation to evaluate how sectoral export growth propagates through the production network. The results show that the impact of export diversification depends critically on sectoral allocation rather than export intensity alone. While aggregate differences between scenarios are modest, reallocating export growth toward sectors with stronger intersectoral linkages generates larger economy-wide gains in GDP and labor income. In particular, sectors with low initial export shares but high network connectivity—such as agriculture, hunting, forestry, and fishing; retail trade; other community, social and personal services; and inland transport—produce stronger multiplier effects than most export-intensive sectors. These findings highlight a key distinction between export intensity and network centrality, demonstrating that sectors with limited direct export participation can play a central role in transmitting economic gains. The results provide a network-based perspective on export diversification and offer policy-relevant insights for designing strategies that promote more inclusive and efficient economic growth. Full article

Political polarization and policy uncertainty have become increasingly consequential for regional economic adjustment, yet their joint role in shaping socioeconomic resilience remains underdeveloped in the literature. This study advances the debate by conceptualizing regional resilience as the outcome of a multi-layer socioeconomic system in which external policy disturbances, institutional fragmentation, and structural adaptive capacity interact over time. Using balanced panel data for 16 Korean regions from 2004 to 2023, the analysis develops an integrated empirical framework that combines panel local projections, threshold estimation, structural moderation tests, dynamic robustness checks, and forward-looking machine-learning prediction. The results show that policy uncertainty is associated with lower regional socioeconomic resilience and that this effect persists over time. More importantly, political polarization does not simply accompany weaker resilience; it amplifies the transmission of uncertainty shocks, especially once institutional fragmentation crosses a critical threshold. Structural conditions further shape this process. Digital transformation, industrial diversification, and financial depth reduce vulnerability, whereas trade exposure intensifies it. These findings indicate that resilience is not determined by economic structure alone, nor by institutional instability in isolation. It emerges from the interaction between disturbance, amplification, and adaptive capacity within a regional system. The predictive analysis reinforces this interpretation. Variables identified as central in the econometric models also carry forward-looking information about future vulnerability states. This study therefore contributes not only by combining methods, but by linking explanation and prediction within a single systems-oriented account of regional resilience. The Korean case shows how institutional coherence and structural adaptability jointly condition resilience under uncertainty. Full article

Posidonia oceanica meadows are among the most valuable coastal ecosystems in the Mediterranean Sea, providing key ecological functions and socio-economic benefits. Despite conservation efforts, these meadows declined markedly throughout the late 20th century due to cumulative human pressures, although their condition has stabilised more recently under protection, and natural recolonization has even begun in some areas. In this context, active restoration through transplantation has expanded considerably, particularly in response to recent policy initiatives, and is now contributing to the recovery of these ecosystems. However, long-term monitoring to assess active restoration success remains scarce. This study revisits one of the earliest P. oceanica transplantation interventions, initiated in 1996 in front of the tourist harbour of Rapallo (NW Mediterranean), and evaluates its status after nearly 30 years. Surveys conducted in 2019 and 2024 confirmed the persistence of the transplanted meadow. The restored area increased from approximately 20 m² at establishment to 26.9 m² in 2024, and shoot density reached values comparable to well-developed natural meadows in the region. The observed long-term structural stability highlights the need to assess restoration outcomes over decadal timescales. This case study also suggests that fine-scale site conditions, including hydrodynamic shelter and adequate light availability, can strongly influence long-term restoration success. Full article

High population growth across developing Pacific countries has increased the share of young people, creating potential for a demographic dividend alongside accelerating digitalisation driven by technology transfer. This study empirically investigates the dynamic relationship between the demographic dividend, digitalisation (ICT access), and economic growth. An endogenous growth framework is employed and extended to incorporate demographic change and information technology adoption, along with education (human capital) and renewable energy use to capture the broader dimensions of sustainable economic growth. The results show that both the demographic dividend and ICT are positively associated with per capita income. Moreover, technology adoption and the demographic dividend exhibit a complementary relationship, implying that improvements in one reinforce the growth effects of the other, while education exerts a positive and statistically significant impact on economic growth. In contrast, renewable energy shows a positive but statistically insignificant effect, suggesting its role is emerging but important for long-term sustainability. In assessing the determinants of digitalisation, the findings indicate that demographic structure and urbanisation contribute positively; however, a substantial share of variation in digitalisation is explained by income levels and mobile phone technology. These results highlight the importance of policies that leverage demographic transition through education and digital technologies, and sustainable energy transitions to accelerate sustainable economic growth and improve welfare outcomes in Pacific developing economies. Full article

Small settlements in Serbia are confronted with long-term processes of depopulation, ageing, and migration, characterised by pronounced spatial and structural heterogeneity. This raises questions about the effectiveness of uniform development policies and underscores the need for a differentiated, place-based approach. The aim of this paper is to identify the demographic heterogeneity of small settlements (with fewer than 100 inhabitants) and to analyse its implications for decentralised territorial development. The research is based on the analysis of 1302 settlements in Serbia, using 26 demographic, socio-economic, and geographical indicators. The methodological framework is based on principal component analysis and cluster analysis, complemented by nonparametric tests and logistic regression. The results indicate pronounced population ageing, low labour potential, and a clear spatial polarisation between accessible and peripheral settlements. Four clearly differentiated types of small settlements are identified. It is concluded that demographic heterogeneity represents a key determinant of development capacity, indicating the need for territorially sensitive and differentiated development policies. In this context, decentralisation and tailored development models may contribute to the revitalisation and long-term sustainability of rural areas. Full article

Urban agriculture plays a critical yet increasingly complex role in sustainable urban development, especially in high-density regions undergoing rapid transformation. Accurate mapping of its spatial distribution and functional composition remains a methodological challenge due to its fragmented landscape, small plot sizes, and multifunctional nature. This study addresses this gap by developing and applying a novel hierarchical classification framework that integrates agricultural land cover types with key socio-economic functions to map urban agriculture in the Pearl River Delta (PRD), China. This framework is structured around agricultural land categories (i.e., cropland, garden, forest, grass, and water body) and further delineated by two primary production functions, planting and breeding, with a third functional dimension, leisure activities, proposed as a conceptual extension for future research. Using unmanned aerial vehicle (UAV) imagery and high-resolution satellite data, we constructed a spatial sample database for urban agriculture. The random forest algorithm was applied to classify urban agriculture with Gaofen-2 imagery, generating detailed spatial distribution maps across the study area, with consistently reliable overall accuracy (79.07–81.82%), though this may be slightly optimistic due to potential spatial autocorrelation between training and testing samples. While the framework performed exceptionally well for spectrally and spatially distinct classes such as water bodies and perennial plantations, challenges remained in discriminating among annual field crops due to spectral similarity. These findings underscore the potential of integrating multi-temporal remote sensing data to capture phenological variations for improved classification. This study provides a replicable, functionally informed mapping approach that not only advances the methodological toolkit for urban agriculture characterization but also offers a valuable evidence base for land use planning, agricultural policy, and sustainable urban development in rapidly urbanizing regions. Full article

With the accelerating processes of globalization and urbanization, metropolitan fringe areas—situated at the intersection of urban expansion and rural transformation—have become critical focal points in urban geography, regional economics, and urban–rural planning. Within the context of China’s new urbanization strategy and the national “dual circulation” framework, the role of policy evolution in shaping spatial development has become increasingly significant. Specifically, in metropolitan fringe zones such as Shenzhen’s Guangming District, the complex interplay between overlapping policies and local path dependencies has generated a distinctive logic of spatial restructuring. Taking this area as a case study, this research investigates the influence of national policies on regional evolution and spatial reconstruction. The findings demonstrate that, under sustained policy guidance, Guangming District has experienced a three-stage process of spatial restructuring, characterized by a dynamic and tightly coupled relationship between policy instruments and spatial forms across different developmental phases. Full article

This study systematically examines the impacts of extreme temperatures on the digital economy development index and the underlying mechanisms based on panel data from 281 prefecture-level cities in China from 2012 to 2023. This study explicitly distinguishes the distinctive adaptive capacity of the digital economy in responding to climate risks. Through global and local spatial autocorrelation analysis, the study finds that both extreme temperatures and the digital economy exhibit significant spatial clustering. This study employs the spatial Durbin model (SDM) and effect decomposition and further incorporates the GS2SLS estimator alongside dual instrumental variables constructed from historical geographic characteristics to address endogeneity, thereby identifying the asymmetrical impacts of extreme heat and extreme cold on the digital economy with great rigor. Specifically, extreme heat fosters short-term local digital demand that is subsequently translated into long-term growth in IT human capital and infrastructure, thereby increasing the DEDI. However, its net spatial effect is inhibitory due to energy crowding out. Extreme cold, by contrast, primarily disrupts supply chains and intensifies energy consumption, with its impact largely confined to the local scope. Green technological innovation mitigates the impact of extreme heat on the digital economy through demand substitution, while, under extreme cold, it manifests as the physical protection of infrastructure. Meanwhile, an optimized industrial structure substantially reduces the economy’s dependence on supply chains, amplifying the promotional effect of extreme temperatures on the digital economy and reflecting the transformation capacity of regions under complex environmental conditions. Heterogeneity analysis demonstrates that the effects of extreme temperatures vary significantly across different urban agglomerations, economic zones, geographic regions and city types. This study not only extends the theoretical framework for the economic assessment of climate risks and spatial econometric analysis to the climate sensitivity of the digital economy but also provides empirical evidence for understanding the complex relationship between climate change and digital economy development and offers references for differentiated policies in a coordinated regional digital economy. Full article

Electricity infrastructure is widely regarded as a fundamental prerequisite for supporting sustainable industrial development and driving corporate digital transformation under energy constraints. Taking the quasi-natural experiment of changes in electricity supply resulting from the cross-regional power transmission of the Three Gorges Project, and using data from China’s A-share listed manufacturing companies over the period 2000 to 2023, this paper constructs a multi-period difference-in-differences model to investigate whether improvements in electricity infrastructure promote corporate digital transformation and to examine their potential role in supporting sustainable economic development. The empirical results indicate that improvements in electricity infrastructure significantly enhance the level of corporate digital transformation. In the mechanism analysis, the alleviation of financing constraints and the increase in R&D investment play important mediating roles in the process through which electricity infrastructure affects corporate digital transformation. Further heterogeneity analysis reveals that the above effects are more pronounced in non-STAR Market enterprises, labor-intensive enterprises, asset-intensive enterprises, state-owned enterprises, and regions characterized by relatively lower levels of marketization. This study reveals the intrinsic relationship between electricity infrastructure and corporate digital transformation at the micro level, provides empirical evidence for understanding how energy infrastructure supports sustainable digital transformation and enhances long-term economic resilience, and offers policy implications for promoting the coordinated development of energy security and the digital economy. Full article

The critical role of green consumption in mitigating carbon emissions is widely acknowledged. As a prerequisite for green consumption, consumer green awareness (CGA) plays a pivotal role in advancing sustainable development. This study constructs a comprehensive indicator system for CGA from the three dimensions of “antecedent-behavior-outcome” and measures the CGA levels of 30 provinces in China from 2014 to 2022. Using the Theil index, kernel density estimation, Moran’s I, and Markov chain methods, we analyze its spatiotemporal evolution characteristics. Furthermore, spatial econometric models are applied to explore its driving factors. The results show that China’s CGA exhibits sustained growth during the study period, but regional disparities are widening, driven by inter-regional rather than intra-regional differences. Moreover, China’s CGA gradually demonstrates the long-tailed and multimodal distribution, accompanied by emerging spatial clustering effects. In terms of transition dynamics, CGA demonstrates a short-term “gradient lock”, which is substantially alleviated when spatial spillover effects are incorporated. Additionally, we find that economic development, the advancement of emerging industries, accelerated urbanization, emphasis on education, and policy guidance significantly promote CGA, while overconsumption inhibits CGA. Among these factors, economic development, informatization, e-commerce, education, and policy guidance show significant spillover effects. Full article

Enhancing urban energy efficiency is central to low-carbon transition and broader urban sustainability. However, whether innovation-oriented urban policy can generate such gains, through which channels it operates, and whether its effects extend beyond pilot cities remain insufficiently understood. Focusing on China’s Innovative City Pilot (ICP) program, this study uses panel data for 274 Chinese cities from 2006 to 2022 and treats the staggered implementation of the program as a quasi-natural experiment. A multi-period difference-in-differences model is employed to examine the impact of the ICP program on urban energy efficiency. The results show that the ICP program significantly improves urban energy efficiency, and this conclusion remains robust across a series of robustness checks. Mechanism analysis further suggests that the policy effect operates through lower per capita carbon emissions and stronger green technological innovation. Heterogeneity analysis shows that the effect is more pronounced in larger cities, economically more developed cities, and cities with stronger pre-existing innovation capacity. Spatial analysis indicates that the program generates not only significant local benefits but also positive spillover effects on neighboring cities. Overall, these findings suggest that innovation-oriented urban policies can promote energy-efficient, low-carbon, and more sustainable urban development, while highlighting the importance of regional coordination and local innovation capacity in shaping policy effectiveness. Full article

Amid Europe’s demographic decline and the intensifying global “war for talent,” migration is increasingly viewed as a critical source of human capital capable of sustaining economic growth and welfare systems. Nevertheless, the literature on Macro-Talent Management (MTM) has primarily focused on the attraction of highly skilled expatriates, paying limited attention to how national integration systems shape the broader capacity of countries to attract and retain migrant talent. Addressing this gap, the present study conceptualizes migrant integration as a strategic component of macro-level talent management and evaluates the “talent attractiveness” of different European welfare and migration regimes. Methodologically, the study develops a multi-criteria evaluation framework based on the PROMETHEE II (Preference Ranking Organization Method for Enrichment of Evaluations) outranking method, enabling the simultaneous assessment of institutional, socio-economic, and administrative dimensions of migration governance. The model integrates nine indicators combining policy inclusiveness (e.g., Migrant Integration Policy Index—MIPEX (Migrant Integration Policy Index), citizenship accessibility), labor market outcomes (employment and gender gaps), and systemic pressures on migration management (asylum applications). By integrating policy indicators with real-world labor market performance and administrative capacity, the proposed framework offers a novel analytical tool for comparative migration policy evaluation and decision support. The empirical application covers six European countries representing distinct migration regimes: Portugal, Sweden, France, Poland, Greece, and Germany. The results challenge the conventional assumption that economic strength alone determines migrant attractiveness. Portugal emerges as the most attractive destination, demonstrating that inclusive rights-based integration policies can offset lower GDP levels. In contrast, Germany ranks last in the sample, revealing signs of systemic overextension due to extreme administrative pressure, while Greece occupies the fifth position characterized by structural integration deficits. The study contributes to the literature by linking migration governance, integration policy effectiveness, and macro-level talent management and by introducing a multi-criteria decision-analytic approach for evaluating national migration systems in Europe. The study offers a reassessment of the ‘talent attractiveness’ of European welfare models in a post-pandemic context (2023). Full article