Search Results (85)

Europe’s decarbonization calls for an increase in the resources used to ensure a fairer transition. The objective of this study is to evaluate the role of public finance in the decarbonization process, considering the context of various uncertainties. Data from 1995 to 2023 for selected European countries were analyzed in this sense. We used the cross-sectional dependence–consistent Driscoll–Kraay estimator as the main econometric approach and Feasible Generalized Least Squares (FGLS) as a robustness test. The results revealed a positive impact of public debt, world uncertainty, and gross domestic product on renewable energy usage in European countries. Additionally, general fiscal pressure is shown to have a negative impact on the renewable energy used during the analyzed period. The results showcase the importance of public finance tools adjustments in supporting the race to zero breakthroughs and dawdling climate change. Several policy recommendations were made in this regard. Full article

Macroprudential policy, as an important instrument for counter-cyclical regulation, plays a crucial role in enhancing urban economic resilience. Based on this, this paper empirically examines the influence of macroprudential policy on urban economic resilience and its optimization paths using data from 284 prefecture-level cities in China from 2011 to 2023. The research findings indicate that macroprudential policy significantly enhances urban economic resilience, and the conclusion still holds after various robustness tests. Further analysis reveals that the main transmission channels include stimulating digital finance development, promoting industrial structure upgrading, and deepening regional integration. Notably, this effect is particularly pronounced in smart cities, big data pilot zones, and cities with less fiscal pressure. Additionally, the test results of spatial spillover effects show that the direct effect of macroprudential policy on the economic resilience of cities is relatively significant, while the indirect effect is relatively weak. Finally, empirical tests have proved that the improvement of urban economic resilience can further drive regional innovation capability. This study provides empirical support and theoretical references for improving China’s “dual-pillar” regulatory framework and enhancing urban economic resilience. Full article

Municipalities are facing mounting fiscal pressures that contribute to financial distress, often resulting in reduced service delivery and economic instability. Despite extensive research on this topic, there is neither a framework nor established criteria to guide policymakers and practitioners in selecting appropriate models for financial distress prediction (FDP). This study employs a systematic review approach to identify key criteria for evaluating FDP models and proposes a framework to guide the selection of suitable models. Following PRISMA guidelines, 24 peer-reviewed papers published between 2000 and 2025 were identified through Google Scholar, Web of Science, ScienceDirect, Scopus, EBSCOhost, and ProQuest. The analysis revealed ten key criteria for evaluating FDP models in local government, which were organised into four overarching dimensions: performance, conceptual integrity, practical applicability, and contextual fit. Based on these insights, the study proposes a structured framework that assists practitioners in selecting the most appropriate FDP model. The framework enhances conceptual clarity, synthesises fragmented knowledge, and establishes a foundation for policy-relevant early warning systems to strengthen municipal financial management. Full article

High-quality brand development requires both innovation and legal protection. Although innovation and branding reinforce each other, companies must also prioritize legal safeguards to prevent brand image damage caused by infringement. Therefore, a city’s level of innovation and intellectual property protection jointly shapes its brand development potential. Green fiscal policies can incentivize enterprises to invest in eco-friendly technological R&D, thereby providing foundational support for brand development. This study utilizes trademark data (2005–2018) from 299 prefecture-level cities in China and employs a quasi-natural experiment based on the pilot program of “Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction.” A multi-period DID model is utilized to assess whether such fiscal policies enhance urban brand development potential. According to the findings, the policy substantially improves brand potential by raising awareness of intellectual property and restricting industrial energy use. Heterogeneity analysis reveals stronger policy effects in western and eastern urban areas, particularly in cities with more “Time-Honored Chinese Brands,” increased research and development investment, lower fiscal pressure, greater marketization, and non-resource-based economies. These results add to the literature on brand innovation and protection and provide empirical support for the role of green fiscal policy in promoting brand growth potential. Full article

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze how policy formulation, critical junctures, and path dependence shape institutional changes toward sustainable mobility. The evolution of institutional arrangements can be categorized into three phases: the establishment of fuel-oil-based infrastructure and dependency (1970–2003); the diversification of cleaner fuels through compressed natural gas and biofuels (2004–2014); and the development of affordable and clean energy, focusing on biofuels and electrification (2015 to present). In parallel, a quantitative total cost of ownership analysis of vehicles using different fuel types demonstrates how institutional reforms, fiscal incentives, and regulatory support reshape the economic feasibility of low-carbon technologies. Landscape pressures—such as global decarbonization, fuel import dependence, and energy security challenges—interact with niche innovations, including biofuels, electric vehicles, and hybrid systems, to drive systemic transformation. The findings indicate that institutional changes, supported by quantitative economic evidence and technology diffusion, play a pivotal role in realigning Indonesia’s transport energy regime toward a more resilient, inclusive, and sustainable transition. Full article

China’s dual carbon goals necessitate green transformation across industries, with STAR Market enterprises serving as crucial drivers of technological innovation. Existing studies predominantly focus on traditional sectors, overlooking dynamic policy interactions and structural heterogeneity in these technology-intensive firms. This study examines how coordinated environmental tax reforms, green finance initiatives, and equity network synergies collectively shape enterprise green transition, using multi-period difference-in-differences and triple-difference models across 2019 Q3–2023 Q4. By integrating financial records, patent filings, and carbon emission data from 487 STAR Market firms, the analysis identifies environmental cost pressures as the dominant policy driver, complemented by delayed financing incentives and accelerated resource integration through corporate networks. Regional institutional environments further modulate these effects, with areas implementing stricter tax reforms exhibiting stronger outcomes. The findings advocate for adaptive policy designs that align fiscal instruments with regional innovation capacities, optimize financial tools for technology commercialization cycles, and leverage inter-firm networks to amplify sustainability efforts. These insights contribute to refining China’s climate governance framework for emerging technology sectors. Full article

Rural transformation is crucial to alleviating development pressure on traditional agricultural areas and stimulating rural vitality. This study aims to comprehensively analyze the spatio-temporal patterns, identify the key influencing factors, and propose targeted development strategies for rural transformation specifically within Northern Anhui, a quintessential traditional agricultural area in China. Utilizing the entropy method, exploratory spatial analysis, and geographic detector, we systematically evaluated the level of rural transformation and its spatial distribution characteristics across 35 counties and districts in Northern Anhui from 2011 to 2023. The results demonstrate a significant 35.93% increase in the average rural transformation level over the past decade, evolving from an initially low-level pattern to one characterized by “Central high, peripheral low”, with significantly narrowing disparities between counties and districts. Significant global positive spatial autocorrelation was consistently observed, alongside distinct localized clustering, including high-value clusters (H-H) and low-value clusters (L-L). A driver analysis identified investment efficiency, economic development level, industrialization, transportation accessibility, and fiscal revenue level as the predominant factors driving the spatial differentiation of rural transformation, with interaction detection revealing crucial synergistic effects among these factors. These findings provide valuable empirical insights and a scientific basis for formulating differentiated rural development strategies tailored to specific county types within traditional agricultural areas like Northern Anhui, thereby facilitating the rural transformation process in developing countries. Full article

Although it is generally accepted that economic freedom stimulates economic growth, its effects in transitional economies are still up for debate. More empirical research is needed to examine the long-term effects of economic freedom on growth in the Western Balkans, a region characterised by uneven reform trajectories, fiscal pressures, and institutional fragility. This study examines the effects of seven fundamental factors on real GDP per capita growth (annual percentage change) in six Western Balkan nations between 2013 and 2023. These factors include property rights, government spending, government integrity, business freedom, monetary freedom, trade openness, and education spending. Importantly, in order to better capture macroeconomic constraints, it takes into account two fiscal burden indicators: the public debt and the government budget deficit. A triangulated analytical framework is used: Random Forest regression identifies non-linear patterns and ranks the importance of variables; Bayesian Vector Autoregression (VAR) models dynamic interactions and inertia; and the Generalised Method of Moments (GMM) handles endogeneity and reveals causal relationships. The GMM results show that while government integrity (β = −0.0820, p = 0.0206), government spending (β = −0.0066, p = 0.0312), and public debt (β = −0.0172, p = 0.0456) have negative effects on growth, property rights (β = 0.0367, p = 0.0208), monetary freedom (β = 0.0413, p = 0.0221), and the government budget deficit (β = 0.0498, p = 0.0371) have positive and significant effects on growth. Although the majority of economic freedom indicators are statistically insignificant, Bayesian VAR confirms strong growth persistence (GDP(−1) = 0.7169, SE = 0.0373). On the other hand, the Random Forest model identifies the most significant variables as property rights (3.72), public debt (5.88), business freedom (4.65), and government spending (IncNodePurity = 9.80). These results show that the growth effects of economic freedom depend on the context and are mediated by the state of the economy. Market liberalisation and legal certainty promote growth, but their advantages could be offset by inadequate budgetary restraint and difficulties with transitional governance. A hybrid policy approach, one that blends strategic market reforms with improved institutional quality, prudent debt management, and efficient public spending, is necessary for the region to achieve sustainable development. Full article

In the context of the “Dual Carbon” goals and ecological civilization development, enhancing forestry ecological total factor productivity (FETFP) has become vital for advancing green development and environmental governance. Confronted with tightening resource constraints and pressure to transform traditional growth models, whether digital intelligence integration can effectively empower improvements in FETFP requires in-depth empirical validation. Based on publicly available panel data from 30 Chinese provinces spanning 2012 to 2022, this study constructs an index system for measuring digital intelligence integration and FETFP. Using the Double Machine Learning (DML) framework, the study empirically identifies the impact of digital intelligence development on FETFP and explores its internal mechanisms. The key results show that (1) digital intelligence integration significantly enhances FETFP. For every unit increase in digital and intelligent integration, FETFP rises by an average of 19.97%; (2) mechanism analysis reveals that digital intelligence improves FETFP by optimizing the forestry industrial structure, promoting green technological innovation, and amplifying the synergistic effects of fiscal support; (3) and heterogeneity analysis suggests that the positive impact of digital intelligence integration is more pronounced in regions with higher environmental expenditures and stronger green finance support. Accordingly, this study proposes several policy recommendations, including accelerating digital infrastructure development, strengthening foundational digital intelligence capabilities, enhancing support for green innovation, leveraging the ecological multiplier effects of digital transformation, tailoring digital strategies to local conditions, and improving the precision of regional environmental governance. The findings provide robust empirical evidence for improving FETFP in developing and developed economies. Full article

Economic systems face critical challenges, including widening income inequality, unemployment driven by automation, mounting public debt, and environmental degradation. This study introduces Economocracy as a transformative framework aimed at addressing these systemic issues by integrating democratic principles into economic decision-making to achieve social equity, economic efficiency, and environmental sustainability. The research focuses on two core mechanisms: Economic Productive Resets (EPRs) and Economic Periodic Injections (EPIs). EPRs facilitate proportional redistribution of resources to reduce income disparities, while EPIs target investments to stimulate job creation, mitigate automion-related job displacement, and support sustainable development. The study employs a theoretical and analytical methodology, developing mathematical models to quantify the impact of EPRs and EPIs on key economic indicators, including the Gini coefficient for inequality, unemployment rates, average wages, and job displacement due to automation. Hypothetical scenarios simulate baseline conditions, EPR implementation, and the combined application of EPRs and EPIs. The methodology is threefold: (1) a mathematical–theoretical validation of the Cycle of Money framework, establishing internal consistency; (2) an econometric analysis using global historical data (2000–2023) to evaluate the correlation between GNI per capita, Gini coefficient, and average wages; and (3) scenario simulations and Difference-in-Differences (DiD) estimates to test the systemic impact of implementing EPR/EPI policies on inequality and labor outcomes. The models are further strengthened through tools such as OLS regression, and Impulse results to assess causality and dynamic interactions. Empirical results confirm that EPR/EPI can substantially reduce income inequality and unemployment, while increasing wage levels, findings supported by both the theoretical architecture and data-driven outcomes. Results demonstrate that Economocracy can significantly lower income inequality, reduce unemployment, increase wages, and mitigate automation’s effects on the labor market. These findings highlight Economocracy’s potential as a viable alternative to traditional economic systems, offering a sustainable pathway that harmonizes growth, social justice, and environmental stewardship in the global economy. Economocracy demonstrates potential to reduce debt per capita by increasing the efficiency of public resource allocation and enhancing average income levels. As EPIs stimulate employment and productivity while EPRs moderate inequality, the resulting economic growth expands the tax base and alleviates fiscal pressures. These dynamics lead to lower per capita debt burdens over time. The analysis is situated within the broader discourse of institutional economics to demonstrate that Economocracy is not merely a policy correction but a new economic system akin to democracy in political life. Full article

Population aging poses significant challenges to the sustainability of pension systems. This study presents an integrated methodological approach that uniquely combines actuarial life-cycle modeling with agent-based simulation to assess the potential of Reverse Mortgage Loans (RMLs) as a dual lever for enhancing retiree welfare and supporting pension system resilience under demographic and financial uncertainty. We explore Reverse Mortgage Loans (RMLs) as a potential financial instrument to support retirees while alleviating pressure on public pensions. Unlike prior research that treats individual decisions or policy outcomes in isolation, our hybrid model explicitly captures feedback loops between household-level behavior and system-wide financial stability. To test our hypothesis that RMLs can improve individual consumption outcomes and bolster systemic solvency, we develop a hybrid model combining actuarial techniques and agent-based simulations, incorporating stochastic housing prices, longevity risk, regulatory capital requirements, and demographic shifts. This dual-framework enables a structured investigation of how micro-level financial decisions propagate through market dynamics, influencing solvency, pricing, and adoption trends. Our central hypothesis is that reverse mortgages, when actuarially calibrated and macroprudentially regulated, enhance individual financial well-being while preserving long-run solvency at the system level. Simulation results indicate that RMLs can improve consumption smoothing, raise expected utility for retirees, and contribute to long-term fiscal sustainability. Moreover, we introduce a dynamic regulatory mechanism that adjusts capital buffers based on evolving market and demographic conditions, enhancing system resilience. Our simulation design supports multi-scenario testing of financial robustness and policy outcomes, providing a transparent tool for stress-testing RML adoption at scale. These findings suggest that, when well-regulated, RMLs can serve as a viable supplement to traditional retirement financing. Rather than offering prescriptive guidance, this framework provides insights to policymakers, financial institutions, and regulators seeking to integrate RMLs into broader pension strategies. Full article

With the support of the dual-carbon strategy and related policies, China’s offshore wind power has experienced rapid development. However, constrained by the inherent intermittency and volatility of wind power, large-scale expansion poses significant challenges to grid integration and exacerbates government fiscal burdens. To address these critical issues, this paper proposes a multi-market coupling trading model integrating energy storage-equipped offshore wind power into electricity–carbon–green certificate markets for large-scale grid networks. Firstly, a day-ahead electricity market optimization model that incorporates energy storage is established to maximize power revenue by coordinating offshore wind power generation, thermal power dispatch, and energy storage charging/discharging strategies. Subsequently, carbon market and green certificate market optimization models are developed to quantify Chinese Certified Emission Reduction (CCER) volume, carbon quotas, carbon emissions, market revenues, green certificate quantities, pricing mechanisms, and associated economic benefits. To validate the model’s effectiveness, a gradient ascent-optimized game-theoretic model and a double auction mechanism are introduced as benchmark comparisons. The simulation results demonstrate that the proposed model increases market revenues by 17.13% and 36.18%, respectively, compared to the two benchmark models. It not only improves wind power penetration and comprehensive profitability but also effectively alleviates government subsidy pressures through coordinated carbon–green certificate trading mechanisms. Full article

As global urbanization accelerates amidst compounding risks, comprehensive urban resilience assessment has emerged as a pivotal issue in optimizing risk governance pathways. Grounded in the Pressure–State–Response (PSR) theoretical framework, this study constructs a multidimensional evaluation system for comprehensive urban resilience. Through the integration of a combined weighting method and the TOPSIS model, we systematically measure resilience levels across 13 prefecture-level cities in Jiangsu Province, with the obstacle degree model employed to identify critical resilience constraints. The findings reveal significant spatial heterogeneity in regional resilience patterns. High-resilience cities establish positive feedback mechanisms through economic foundations, innovation-driven strategies, and institutional coordination. Conversely, low-resilience cities face multidimensional constraints, including industrial structure imbalance, inadequate social security systems, and infrastructure deficiencies. The resilience disparity stems from the coupling effects of systemic multidimensional elements, with three core obstacles identified: energy consumption and population pressure in the Pressure dimension, medical resource scarcity and innovation deficit in the State dimension, and fiscal expenditure inefficiency in the Response dimension. The study proposes strategic interventions, including fiscal structure optimization, cross-regional resource coordination enhancement, and innovation–translation mechanism improvement, to facilitate urban systems’ transformation from passive resistance to proactive adaptation. This research provides novel perspectives for analyzing complex system resilience evolution and offers scientific grounds for urban agglomeration risk prevention and sustainable development. Full article

Amid the global drive to enhance public sector performance in the digital economy era, improving government spending efficiency has become a critical governance objective. This study investigates the impact of digital inclusive finance on government spending efficiency from a digital finance systems perspective using county-level panel data in China’s Yangtze River Delta for the period 2014–2022 and constructing the fixed-effects model and instrumental variable method to estimate the effect of digital inclusive finance and explore its underlying mechanisms. Heterogeneity across regions with varying economic development levels is analyzed, and fiscal pressure is examined as a potential mediating factor. The results indicate that (1) digital inclusive finance significantly enhances government spending efficiency, primarily through broad service coverage and deep usage of digital financial services such as mobile payments, digital credit, and insurance; (2) the positive effect is more pronounced in counties with lower government spending efficiency and economic development; and (3) fiscal pressure acts as a key transmission channel, with broader digital inclusive finance coverage helping to alleviate fiscal stress and improve government spending efficiency. These findings offer empirical insights into the role of digital finance in promoting effective and adaptive public financial governance. Full article

This study examines the impact of economic policy uncertainty (EPU) on agricultural land conversion. Using a newspaper-based index of EPU and a comprehensive panel dataset covering 270 prefecture-level cities in China, we estimate a city fixed effects model to explore this relationship. Our results indicate that a one-standard-deviation increase in EPU leads to a 22.2% increase in the conversion of agricultural land to urban residential, commercial, and industrial uses. This finding suggests that the surge in EPU triggered by the global financial crisis accounts for approximately 45% of the increase in agricultural land conversion. The adverse effect on agricultural land preservation mainly stems from intensified fiscal pressures and heightened demands on local governments to meet economic growth targets. To address potential endogeneity concerns, we employ the one-period lagged U.S. EPU index and its temporal variations as an instrument for China’s EPU, leveraging cross-country spillover effects. Our instrumental variable estimates confirm the validity of the land conversion effect and its underlying mechanisms. Furthermore, we find that the effects of EPU are particularly pronounced in cities located in non-eastern China and those that depend heavily on fixed asset investment for local economic development. Finally, our analysis of potential policy interventions to mitigate EPU-induced agricultural land loss suggests that strengthening market-oriented reforms and reducing province-level quotas on agricultural land conversion can effectively offset the impact of rising EPU. Full article