Search Results (206)

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

We investigate whether China’s Value-Added Tax (VAT) Credit Refund policy influences firms’ sustainable development capability (SDC), which reflects innovation-driven growth and green development. Exploiting the 2018 implementation of the VAT Credit Refund policy as a quasi-natural experiment, we employ a difference-in-differences (DID) approach and find causal evidence that the policy significantly enhances firms’ SDC. This suggests that fiscal instruments like VAT refunds are valued by firms as drivers of long-term sustainable and high-quality development. Our mediating analyses further reveal that the policy promotes firms’ SDC by strengthening artificial intelligence (AI) capabilities and facilitating intelligent transformation. This mechanism “AI Capability Building—Intelligent Transformation” aligns with the socio-technical systems theory (STST), highlighting the interactive evolution of technological and social subsystems in shaping firm capabilities. The heterogeneity analyses indicate that the positive effect of VAT Credit Refund policy on SDC is more pronounced among small-scale and non-high-tech firms, firms with lower perceived economic policy uncertainty, higher operational diversification, lower reputational capital, and those located in regions with a higher level of marketization. We also find that the policy has persistent long-term effects, with improved SDC associated with enhanced ESG performance and green innovation outcomes. Our findings have important implications for understanding the SDC through the lens of STST and offer policy insights for deepening VAT reform and promoting intelligent and green transformation in China’s enterprises. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Economic policy uncertainty is an important macroeconomic risk factor that can have direct effects on investment decisions, growth dynamics, and public finance. In particular, its potential impact on tax revenue is critical in terms of fiscal sustainability. This study investigates the Granger-causal relationship between economic policy uncertainty, total tax revenue, and economic growth in G7 economies over the 1997–2021 period, applying symmetric and asymmetric panel causality tests. The empirical findings revealed evidence of causality between economic policy uncertainty and tax revenue and between economic growth and economic policy uncertainty. In asymmetric analyses where the effects of positive and negative shocks were separated, the direction of causal relationships differed between countries. These results imply that asymmetric effects vary by country. Overall, the empirical findings suggest that enhancing transparency and predictability in tax systems could play a vital role in reducing economic policy uncertainty and thus positively affect tax revenue performance and fiscal resilience. Full article

The transition toward a circular water economy addresses accelerating water scarcity and pollution. A PRISMA-2020 systematic review of 50 peer-reviewed articles (January 2018–April 2024) mapped current technologies and management strategies, seeking patterns, barriers, and critical bottlenecks. Bibliometric analysis revealed the following three dominant patterns: (i) rapid diffusion of membrane bioreactors, constructed wetlands, and advanced oxidation processes; (ii) research geographically concentrated in Asia and the European Union; (iii) industry’s marked preference for by-product valorization. Key barriers—high energy costs, fragmented regulatory frameworks, and low social acceptance—converge as critical constraints during scale-up. The following three practical action lines emerge: (1) adopt progressive tariffs and targeted tax credits that internalize environmental externalities; (2) harmonize water-reuse regulations with comparable circularity metrics; (3) create multi-actor platforms that co-design projects, boosting local legitimacy. These findings provide policymakers and water-sector practitioners with a clear roadmap for accelerating Sustainable Development Goals 6, 9, and 12 through circular, inclusive, low-carbon water systems. Full article

As Chinese firms play pivotal roles in global supply chains, multinational corporations face increasing pressure to ensure ESG accountability across their sourcing networks. Current ESG rating systems lack transparency in incorporating China’s unique industrial, economic, and cultural factors, creating reliability concerns for stakeholders managing supply chain sustainability risks. This study develops an explainable artificial intelligence framework using SHAP and permutation feature importance (PFI) methods to predict the ESG performance of Chinese firms. We analyze comprehensive ESG data of 1608 Chinese listed companies over 13 years (2009–2021), integrating financial and non-financial determinants traditionally examined in isolation. Empirical findings demonstrate that random forest algorithms significantly outperform multivariate linear regression in capturing nonlinear ESG relationships. Key non-financial determinants include patent portfolios, CSR training initiatives, pollutant emissions, and charitable donations, while financial factors such as current assets and gearing ratios prove influential. Sectoral analysis reveals that manufacturing firms are evaluated through pollutant emissions and technical capabilities, whereas non-manufacturing firms are assessed on business taxes and intangible assets. These insights provide essential tools for multinational corporations to anticipate supply chain sustainability conditions. Full article

Energy is at the center of economic growth and environmental sustainability. Increasing energy efficiency and turning to environmentally friendly technologies are indispensable elements not only in reducing carbon emissions but also in supporting the transition to a green future. This study aims to deeply examine the simultaneous dynamic interactions between energy, environmental technologies, and economic growth by focusing on the environment and analyzing the transformative effects of these factors on environmental sustainability from a broad perspective. The models were estimated via simultaneous equation systems with two-stage and three-stage least squares methods with monthly data for Organization for Economic Cooperation and Development (OECD) countries between 1990 and 2021. As a result of the analyses, the estimation results of the two methods generally support each other. Notably, economic growth causes carbon emissions, and when tax revenues on energy are added to the model, the negative effect of economic growth on carbon emissions turns positive. Another significant result shows that energy efficiency does not reduce carbon emissions. Even an increase in energy efficiency causes an increase in carbon emissions, and the rebound effect is valid. Population and energy density do not have a negative impact on carbon emissions. Full article

The implementation of a carbon tax in the transportation sector aims to reduce carbon emissions and encourage the transition to sustainable mobility amid increasing urbanization. The transportation sector is one of the largest contributors of carbon emissions in Indonesia, requiring effective policies to reduce its environmental impacts. Therefore, this study aims to find a more optimal carbon tax formula that is in accordance with Indonesia’s socio-economic conditions. The approach used includes analysis of transportation emission data, the economic impact of different carbon tax schemes, and tax revenue allocation strategies to support green infrastructure and sustainable transportation. The results of the study indicate that an adaptive carbon tax formula in the transportation sector is able to balance the economic burden, emission reduction targets, social justice, behavioral changes, and revenue allocation for green infrastructure, thus ensuring a just and sustainable transition. A progressive carbon tax, based on vehicle emission levels and fuel types, can encourage the transition to low-emission vehicles without excessively burdening low-income communities. With this approach, carbon tax policy functions not only as a fiscal instrument but also as a transformative strategy in creating an environmentally friendly and equitable transportation system. Full article

The global shift to low-carbon energy systems has significantly increased demand for critical raw materials like lithium, cobalt, nickel, rare earth elements, and copper. These materials are essential for renewable technologies and energy storage. However, their extraction and processing produce significant carbon emissions and face challenges from supply chain vulnerabilities and price volatility. This review examines the complex relationship between carbon pricing mechanisms—such as carbon markets and taxes—and raw material markets. It explores the strategic importance of these materials, recent policy developments, and the transmission of carbon pricing impacts through supply chains. The review also analyzes the systemic risks created by carbon pricing, including regulatory uncertainty, market volatility, and geopolitical tensions. We then discuss financial tools and corporate strategies for managing these risks, such as carbon-linked derivatives and supply chain diversification. Finally, this review identifies key challenges and suggests future research to improve the resilience and sustainability of raw material supply chains. Here, resilience is defined as the capacity to adapt to carbon pricing volatility, geopolitical disruptions, and regulatory shocks, while maintaining operations. The paper concludes that coordinated policies and flexible risk management are urgently needed to support a reliable and sustainable energy transition. Full article

Research on the semantic approach to different land use classes is considered an important aspect of overcoming challenges related to proper land management. This research has direct implications for sustainable land management. The aim of this study is to introduce a new land use class in the Polish cadastre based on land use registration systems that function in other European countries. To achieve this, the existing land use registration systems in selected European countries were analyzed. The criterion for including land in the new class will be its actual use. The proposed new land use class may be a highly promising solution for the clear identification of areas with a special functional nature. By proposing the introduction of this new class, authors highlights the areas that, under the current land use registration system, are not clearly identified within the broadly understood categories of built-up and urbanized land. The research findings may also serve as a practical guideline for local authorities responsible for land administration and property taxation. Moreover, accurate land use classification is essential for sustainable land management, as it enables better planning and resource allocation. Improved clarity in land categorization supports environmental protection and balanced development, contributing to long-term sustainability goals. Full article

This study investigates the dynamic relationship between environmental tax revenue and economic development in the European Union from 2013 to 2022. The findings reveal that these taxes significantly contribute to economic development in the long run, although short-run effects vary by tax type and country. The PMG model results indicate that energy tax revenues increase GDP per capita by 0.038, transport tax revenues by 0.041, and resource tax revenues by 0.018, all of which are statistically significant. Pollution tax revenues have an effect of 0.002 in the long run but are not statistically significant. In the short run, none of the tax variables show significant effects, although pollution tax revenues have a transitional impact of 0.196. The error correction term of −1.321 confirms a strong long-run adjustment, reinforcing the gradual economic benefits of environmental taxation. The results underscore the importance of resource and pollution taxes, which exhibit robust positive impacts, particularly in resource-rich and pollution-intensive economies. Energy and transport taxes also influence economic performance; however, their effectiveness depends on the structural and sectoral differences among countries. This study provides valuable insights for policymakers by highlighting the necessity of designing tailored environmental taxation policies that align with national conditions and long-term sustainability goals. Additionally, this study adopts a systems thinking perspective to capture the interconnectedness between environmental fiscal instruments and macroeconomic sustainability, offering a holistic interpretation of policy impacts. Full article

This study highlights the pivotal role of women in corporate governance and their potential influence on achieving sustainable goals, particularly in the context of emerging countries. Using the two-step System-Generalized Method of Moments (GMM) with the dynamic short panel data of 351 nonfinancial listed companies in Vietnam from 2010 to 2022, this research examines the dynamics between earnings management and tax avoidance, focusing on the moderating role of women on the board of directors. The results confirm that both accrual-based and real earnings management are positively associated with corporate tax avoidance. However, there is a significant negative relationship between female representation on the board and tax avoidance, as well as a significant moderation of the relationship between earnings management and tax avoidance. This study reinforces that female leadership contributes to reducing earnings management and tax avoidance through improved monitoring and governance of corporate ethical activities, emphasizing the importance of strategically empowering women in leadership roles. The implications of this study are given to minimize harmful financial practices and align corporate strategies with ethical practices. Full article

As global trade and container transportation continue to grow, port collection and distribution systems face increasing challenges, including congestion, inefficiency, and environmental impact. Traditional ground-based transportation methods often exacerbate these issues, especially under uncertain demand conditions. This study aims to optimize freight flow allocation in port collection and distribution networks by integrating traditional and innovative transportation modes, including underground container logistics systems, under demand uncertainty. A stochastic optimization model is developed, incorporating transportation, environmental, carbon tax and subsidy, and congestion costs while satisfying various constraints, such as capacity limits, time constraints, and low-carbon transport requirements. The model is solved using a hybrid algorithm combining an improved Genetic Algorithm and Simulated Annealing (GA-SA) with Deep Q-Learning (DQN). Numerical experiments and case studies, particularly focusing on A Port, demonstrate that the proposed approach significantly reduces total operational costs, congestion, and environmental impacts while enhancing system robustness under uncertain demand conditions. The findings highlight the potential of underground logistics systems to improve port logistics efficiency, providing valuable insights for future port management strategies and the integration of sustainable transportation modes. Full article

This study explores the drivers and evolution of the shadow economy in Bosnia and Herzegovina—a transitional, post-conflict country facing persistent institutional fragility. Using the Multiple Indicators and Multiple Causes (MIMIC) model, an extension of Structural Equation Modeling, the paper estimates the size and dynamics of the shadow economy from 1996 to 2022. The model integrates macroeconomic indicators (employment rate, GDP per capita, tax revenues) and institutional variables (rule of law, control of corruption), with data primarily sourced from the World Bank. The results show that institutional quality, tax burden, and labor market conditions are significant determinants of the informal sector. The model demonstrates strong statistical validity (CFI = 0.986, RMSEA = 0.05), supported by robustness checks including unit root tests, structural break analysis, and the exclusion of controversial benchmarking methods. The shadow economy responds markedly to major shocks such as the 2008 global financial crisis and the 2014 floods. Findings provide valuable policy insights: strengthening institutions, simplifying tax systems, and encouraging formal labor market participation can significantly reduce informality. The study supports evidence-based reforms to enhance transparency, resilience, and sustainable development in Bosnia and Herzegovina. Full article

Green development stands as an imperative pathway for China’s growth model. Enhancing green economic efficiency is crucial to maintaining sustainable development in the Yellow River Basin. The hierarchical governance structure of China’s economic development system inherently links competition among governments to potential impacts on the basin’s green economic efficiency, yet research in this area remains scarce. This study utilizes a panel data structured dataset containing both temporal and cross-sectional dimensions from nine provinces in the Yellow River Basin to investigate how tax competition among local governments affects green economic efficiency. The empirical results demonstrate that tax competition hinders green economic efficiency in the Yellow River Basin, exhibiting spatial heterogeneity in its inhibitory effect. Specifically, the inhibitory effect on the middle reaches is approximately twice as significant as that observed on the upper reaches, while the inhibitory effect on the lower reaches is found to be facilitative. In addition, the upgrading of industrial structure and industrial agglomeration triggered by tax competition partially alleviate the inhibitory effect on green economic efficiency. Therefore, policymakers can promote the sustainable development of the Yellow River Basin by optimizing the tax system, implementing regional differentiation strategies, optimizing industrial layout, and promoting the development of green clusters. Full article