Private management of African protected areas improves wildlife and tourism outcomes but with security concerns in conflict regions.

Protected areas can conserve wildlife and benefit people when managed effectively. African governments increasingly delegate the management of protected areas to private, nongovernmental organizations, hoping that private organizations' significant resources and technical capacities actualize protected areas' potential. Does private sector management improve outcomes compared to a counterfactual of government management? We leverage the transfer of management authority from governments to African Parks (AP)-the largest private manager of protected areas in Africa-to show that private management significantly improves wildlife outcomes via reduced elephant poaching and increased bird abundances. Our results also suggest that AP's management augments tourism, while the effect on rural wealth is inconclusive. However, AP's management increases the risk of armed groups targeting civilians, which could be an unintended outcome of AP's improved monitoring and enforcement systems. These findings reveal an intricate interplay between conservation, economic development, and security under privately managed protected areas in Africa.

Does government environmental attention drive green total factor productivity? Evidence from China.

Based on city-level panel data spanning 2008 to 2021, this study investigates the impact of government environmental attention (GEA) on green total factor productivity (GTFP). The findings suggest that increased GEA substantially enhances the growth of GTFP. After conducting robustness and endogeneity tests, the study's results consistently show reliability and robustness. Further analysis elucidates several mechanisms through which GEA influences GTFP, including fostering green technology innovation, optimizing resource allocation, and promoting upgrades in industrial structure. Heterogeneity analyses reveal that the impact of GEA on GTFP is notably pronounced in eastern cities, as well as in cities characterized by low resource dependency, mature industrial development, and high market competition. Conversely, the influence of GEA on GTFP is less discernible in cities prioritizing economic development goals, possibly due to differing policy orientations and resource allocation strategies. This study offers a novel perspective on understanding how GEA shape green development and provides empirical support for policy formulation.

Spatio-temporal evolution and prediction of carbon balance in the Yellow River Basin and zoning for low-carbon economic development.

Studying the carbon effect of land use in watersheds is important for mitigating global warming, promoting coordinated emission reduction in different regions within the watersheds, and realizing high-quality development of the watersheds. Although a number of scholars have carried out relevant studies in the past, they mainly focused on carbon emissions, rarely involved the carbon balance formed by carbon sources and sinks, and lacked relevant studies on the development of low-carbon economy sub-region. Based on this, this study takes the Yellow River Basin as an example, explores the spatial and temporal evolution of carbon emissions from land use in counties in the Yellow River Basin from 1980 to 2020, and predicts the spatial pattern of carbon income and expenditure from land use under natural conditions in 2030 and 2060 using the PLUS model; and then superimposes on the main functional area planning, divides 735 counties in the Yellow River Basin into six low-carbon economic development subregions, and analyzes their economic development The model of their economic development is analyzed. The results show that: (1) the spatial and temporal differentiation of land use carbon balance in the Yellow River Basin has changed greatly over the past 40 years, (2) the spatial distribution pattern of land use carbon balance in the natural context in 2030 and 2060 is more similar to that in 1990, (3) the carbon emission reduction potentials and pattern optimization of the different low-carbon economic development subregions differ greatly, and they have different low-carbon economic development patterns. The results of this study provide a theoretical basis for scientifically and rationally formulating economic policies for low-carbon development in the counties of the Yellow River Basin, and also provide an important reference for related studies in other similar basins or regions in the world.

Evolution and driving factors of inequality in CO2 emissions from agricultural energy consumption in China.

The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China's agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya-Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China's agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

Determinants of financial inclusion gaps in Pakistan and implications for achieving SDGs.

This study investigates the determinants of gender disparities in financial inclusion in Pakistan using Global Findex 2021 survey data. We aim to quantify gender gaps in financial access and use, and to analyze the socio-economic factors influencing these disparities. Grounded in Sen's capability approach and behavioral economics, we employ logistic regression to examine how gender influences the ownership and usage of financial products. Our results reveal significant gender gaps: only 13% of Pakistani women have financial accounts compared to 34% of men, with similar disparities in digital finance. Socio-economic variables like education, income, and employment are found to influence financial inclusion differently for men and women. While generally supportive of financial inclusion, these factors have a weaker effect for women, suggesting deeper societal barriers. This study adds to the global financial inclusion discourse by providing a comprehensive analysis of gender disparities in Pakistan. Our findings highlight the need for gender-sensitive policies that address these disparities to achieve Sustainable Development Goals related to gender equality and economic empowerment.

Digital Tools for Boosting the Impact of Fiscal Decentralization in Africa's Local Economies.

Background: Fiscal decentralization offers potential for stimulating local economic development in Africa, empowering subnational governments to control revenue and spending. However, challenges such as urbanization, poverty, inequality, insufficient infrastructure, and governance issues hinder the successful implementation of the core tenets of fiscal decentralization. This paper explores the role of digital technologies in promoting greater fiscal decentralization and revenue enhancement, as a strategic response to these local economic development challenges in Africa. Method: Through a systematic literature review, this study explores the role of fiscal decentralization in driving local economic development, with a focus on leveraging digital technologies to boost revenue generation and strengthen governance and institutional capacity at the subnational level. Results: The research underscores the importance of investing in digital infrastructure, skill development, and regulatory frameworks, while addressing data privacy and security concerns. Conclusion: By emphasizing the transformative impact of digital technologies fiscal decentralization and property taxation, this paper contributes to the existing literature and highlights avenues for promoting local economic development across Africa.

[Economic index - predictor of premature aging.]

It is widely known that in economically developed countries there is an increase in the proportion of older people. However, the problem of the influence of territorial features of economic development on the rate of population aging is not sufficiently covered. The goal was to study the impact of economic development indicators (EDI) on the processes of premature aging of the population. The materials were statistical collections of the Ministry of Health of Russia and Russian Statistics Service for 2011-2019. The highest incidence was characteristic of cataracts and glaucoma. A direct correlation has been established between the EDI and the age-specific incidence index (ASII) of cataracts (r=0,31; p=0,00436). A group of regions with a high level of economic development was characterized by a higher value of ASII, which, as a rule, corresponds to the later development of the disease.

The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence.

Background: The coordination of health service supply and regional economy is an integral path to promote China's prosperity. Methods: Based on the coupling mechanism of health service supply and regional economy, we sampled the data from 30 provinces in China from 2009 to 2021 in this study and constructed the evaluation index system. Additionally, we calculated the coupling coordination degree (HED) of the two through the coupling coordination degree model. We further used the kernel density estimation, Moran's I index, and spatial ß convergence model to assess the dynamic evolution trends, spatial aggregation effect, and spatial convergence characteristics of coupling coordination. Conclusion: (1) HED in China showed a rising trend during the study period but with large regional differences, forming a gradient distribution pattern of "high in the east and low in the west." (2) The results of Kernel density estimation show that HED has formed a gradient differentiation phenomenon within each region in China. (3) HED has modeled spatial clustering characteristics during the study period, with high-value clusters mainly appearing in the eastern region and low-value clusters appearing in the northwestern region. (4) There are absolute ß-convergence and conditional ß-convergence trends in HED in China and the three major regions during the study period, but there is an obvious regional heterogeneity in the control factors. The research provides a reference for accurately implementing policies according to different levels of health service supply and economic development, in addition to narrowing the regional differences of the coupling coordination between the regional economy and health service supply.

Spatio-temporal evolution and influencing factors of high quality economic development: Case study of Guangdong-Hong Kong-Macao Greater Bay Area.

With the increase in global economic integration, high-quality economic development (HQED) has become a common goal of all countries. Based on these five development concepts, this paper uses the Gini coefficient, trend surface analysis, geographically weighted regression (GWR), the entropy weighting method, and standard deviation ellipse analysis to study the spatio-temporal pattern and driving mechanism of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This paper examines the spatial and temporal patterns and driving mechanisms of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) based on five development concepts. The study revealed that (1) HQED is on the rise overall, but at the same time, it highlights the uneven development of multiple dimensions, especially in terms of significant differences in innovation, openness, and sharing. (2) HQED shows a clear center-periphery structure, with Guangzhou, Shenzhen, and Hong Kong as the core high-value areas; the growth rate of HQED capacity in the internal areas is significantly greater than that in the external areas, and HQED is prominent in the cities around Guangzhou, Shenzhen, and Hong Kong. (3) Factors such as agglomeration level, human capital, foreign investment, infrastructure development, financial and environmental protection expenditures, and financial inputs, and scientific, and technological inputs have a significant positive effect on HQED, and their interactions are further strengthened. This study reveals the importance of the realization of HQED in the GBA and the promotion of the overall development of the region.

Hindrance or facilitator? The economic consequences of national demonstration eco-industrial parks in China.

Many countries attach great importance to the green, low-carbon, and circular development of industrial parks. China is one of them and has entered an exploration journey of national demonstration eco-industrial parks (NDEIPs). However, the impact of the transformation of industrial parks into NDEIPs on local economic development still remains a mystery. To address this issue, we develop an empirical study using a combination of the multi-period difference-in-differences method and the propensity score matching method based on the panel data for 266 cities in China from 2001 to 2021. The results show that industrial parks becoming NDEIPs promotes cities' economic development. This conclusion still holds after a series of robustness tests, such as the reverse causality test and the placebo test. Moreover, the park heterogeneity tests show that the economic consequences vary according to differences in levels, industry types, life cycle phases, and the degree of foreign firm agglomeration. The city heterogeneity tests show that the economic consequences differ based on administrative levels, innovation capabilities, technology industrialization, and environmental friendliness. The spatial heterogeneity tests show that the economic consequences differ according to geographical location and whether situated in the Yangtze River Economic Belt. The policy upgrading heterogeneity tests show that the economic consequences differ during the process of policy upgrading and transformation. In addition, the mechanism tests reveal that green innovation, human capital level, and firm attractiveness mediate the relationship between industrial parks becoming NDEIPs and cities' economic development. This study provides a new perspective for understanding the economic effects of the transformation of industrial parks into NDEIPs, and provides a reference for the government on how to maximize these economic effects.

Scale or effectiveness? The nonlinear impact of talent agglomeration on high-quality economic development in China.

Talent agglomeration serves as a vital pathway for achieving high-quality economic development. This paper, based on provincial panel data from China spanning 2011-2020, first analyses the impact of talent agglomeration on high-quality economic development from two dimensions: the talent agglomeration scale and effectiveness. Second, with innovation activity as a threshold variable, this paper explores the nonlinear impact of the talent agglomeration scale and effectiveness on economic efficiency improvement and economic structure optimization. This study finds that (1) the main driving force for high-quality economic development within the sample period comes from the talent agglomeration scale, while the promoting role of talent agglomeration effectiveness has not yet passed significant tests. (2) Under different levels of innovation activity, the talent agglomeration scale has a diminishing marginal utility impact on economic efficiency improvement and economic structure optimization; talent agglomeration effectiveness also has different nonlinear effects on economic efficiency improvement and economic structure optimization.

Equitable infrastructure: Achieving resilient systems and restorative justice through policy and research innovation.

Recent major investments in infrastructure in the United States and globally present a crucial opportunity to embed equity within the heart of resilient infrastructure decision-making. Yet there is a notable absence of frameworks within the engineering and scientific fields for integrating equity into planning, design, and maintenance of infrastructure. Additionally, whole-of-government approaches to infrastructure, including the Justice40 Initiative, mimic elements of process management that support exploitative rather than exploratory innovation. These and other policies risk creating innovation traps that limit analytical and engineering advances necessary to prioritize equity in decision-making, identification and disruption of mechanisms that cause or contribute to inequities, and remediation of historic harms. Here, we propose a three-tiered framework toward equitable and resilient infrastructure through restorative justice, incremental policy innovation, and exploratory research innovation. This framework aims to ensure equitable access and benefits of infrastructure, minimize risk disparities, and embrace restorative justice to repair historical and systemic inequities. We outline incremental policy innovation and exploratory research action items to address and mitigate risk disparities, emphasizing the need for community-engaged research and the development of equity metrics. Among other action items, we recommend a certification system-referred to as Social, Environmental, and Economic Development (SEED)-to train infrastructure engineers and planners and ensure attentiveness to gaps that exist within and dynamically interact across each tier of the proposed framework. Through the framework and proposed actions, we advocate for a transformative vision for equitable infrastructure that emphasizes the interconnectedness of social, environmental, and technical dimensions in infrastructure planning, design, and maintenance.

"Two Mountains concept" leading the green transformation of China's economic society.

The rapid urbanization are serious threats to global sustainable development, making the green transformation of socio-economy and industry a must for global efforts. The theory of ecological and economic harmonization in ecological economics has gained attention. However the Two Mountains concept, i.e., "Lucid waters and lush mountains are invaluable assets", has been mostly neglected as a practical demonstration of the theory. In this study an equal weights method is used to construct an index system for testing the effectiveness of the ongoing practices and demonstrations of the Two Mountains concept, and whether it can achieve the expected green transformation objectives. A total of 421 pilot cases and 208 surrounding non-pilot cases in China from 2010 to 2020 are selected for analysis. The results indicate that: (1) From 2010 to 2020, overall 98.33% of pilots show positive improvement in comprehensive effectiveness; (2) Strong evidence indicate that the positive externality of the demonstrations extends to their surrounding region, mainly manifested in the impact of industrial structure change, inspiring collaboration between cities; (3) Such ambitious green transformation has a significant impact on landscape characteristics, which emphasizes the role of landscape management and monitoring. Therefore, this study proposes an industrial integration framework to enhance the transformation of ecosystem service values, to facilitate transition to a green economy in various regions globally. It provides significant managerial insights and practical expertise. The demonstration of China's Two Mountains concept can offer reliable empirical cases to enrich the theory of ecological economics and global sustainable development.

Managing urban agglomeration processes in Russia in the context of agglomerative and socio-economic development.

Studies on urban agglomeration typically focus on the management of urban agglomerations as special types of spatial organization. The problem of finding an adequate management model which accounts for the level of spatial connectivity and socio-economic development of a given territory remains in the background. This article identifies urban agglomeration management models in Russia which account for the agglomerative and socio-economic development of a given territory. A methodology for assessing urban agglomeration processes is presented which, unlike existing methodologies, includes an assessment of agglomeration maturity and an assessment of the socio-economic development of urban agglomerations. This methodology is based on conceptual platforms within spatial development theory; new economic geography; and agglomeration theory and cluster development. The methodology was tested on the data of Chelyabinsk Region agglomerations. The study determined that the Chelyabinsk and Gorniy Ural agglomerations are socio-economically developed and highly agglomerated, while the Magnitogorsk agglomeration shows high socio-economic development and low agglomeration. The conurbations are underdeveloped in both areas. The paper gives several recommendations on methods for choosing urban agglomeration management models. The developed methodology can be used to assess agglomerations across Russia and to choose the most adequate management model for a territory depending on its agglomerative and socio-economic development.

The influence of AI on the economic growth of different regions in China.

High-quality development plays a crucial role in China's economic progress in the new era. It represents a new concept of advancement and mirrors the increasing aspirations of the populace for an improved standard of living. In this context, the role of artificial intelligence (AI) in promoting sustainable development cannot be overemphasized. This paper explores how AI technologies can drive the transition to a green, low-carbon and circular economy. We have established an index system to measure the development level of the artificial intelligence industry and the high-quality development of the economy, which is relevant to the current state of the artificial intelligence industry and the advancement of the economy. Panel data from 2008 to 2017 has been utilized for this purpose. Global principal component analysis method and entropy value method are employed in the evaluation. Through in-depth analysis of the application of artificial intelligence and environmental protection in various provinces and cities, we clarify that artificial intelligence promotes innovation, saves resources, and is conducive to the development of green economy in the new era.

The spatial spillover effects of clean energy consumption and production on sustainable economic development in China.

The massive consumption of fossil energy has resulted in high CO2 emissions, posing a formidable challenge to global sustainable economic development (SED). As countries endeavor to shift from fossil to clean energy sources to achieve SED, research on the impact of clean energy is scarce, and quantitative analysis is lacking. This study measured China's SED and used a spatial econometric model to examine the impact of clean energy consumption and production on SED across 30 provinces in China from 2008 to 2020. Results show that (1) China's SED exhibits significant positive spatial autocorrelation characteristics, forming a "point-to-area" development pattern. (2) Clean energy consumption, production, and consumption structure all contribute to the promotion of SED in the region and have positive spatial spillover effects. (3) A considerable regional disparity exists in the spatial impact of clean energy on SED. The eastern and central regions have significant positive spatial spillover effects, whereas the western region is opposite. Notably, the estimated coefficient of the spatial Durbin model is relatively small, reflecting China's ongoing transition to clean energy and its limited role in promoting economic sustainability. Joint efforts and differentiated policies are essential to develop clean energy and sustainable economic.

Health and Economic Growth: Reconciling the Micro and Macro Evidence.

Economists use micro-based and macro-based approaches to assess the macroeconomic return to population health. The macro-based approach tends to yield estimates that are either negative and close to zero or positive and an order of magnitude larger than the range of estimates derived from the micro-based approach. This presents a micro-macro puzzle regarding the macroeconomic return to health. We reconcile the two approaches by controlling for the indirect effects of health on income per capita, which macro-based approaches usually include but micro-based approaches deliberately omit when isolating the direct income effects of health. Our results show that the macroeconomic return to health lies in the range of plausible microeconomic estimates, demonstrating that both approaches are in fact consistent with one another.

Exploring the nexus between economic and environmental issues in the tourism sector at the country level. A replicable framework.

In recent years, the tourism activities take experienced a steady growth in demand, yet it causes ecological damages, such as waste production and carbon dioxide emissions. This paper provides a theoretical framework for testing the interactions among sustainable development and economic growth in the tourism context and demonstrates that sustainability depends on both environmental impacts and some relationships among different factors. In particular, considering some of the key indicators proposed by Agenda 2030 and integrated in the Sustainable Development Goals (SDGs), the authors focused on the direct influence of tourism to Gross Domestic Product (TGDP), Environmental Performance Indicator (EPI) score, and Carbon Footprint (CF) as indicators that were used together with GDP and Municipal Solid Waste (MSW) to test five hypotheses and analyze their interactions for a sample country. The results reveal the statistical significance among these indicators in the light of Sustainable Development Goals n. 8, n. 12, and n. 13. Finally, Municipal Solid Waste, the first visible human effect due to tourism, presents a strong interaction with Carbon Footprint.

Spatial effect of biomass energy consumption on carbon emissions reduction: the role of globalization.

As globalization proceeds, increasing biomass energy consumption is an important pathway to replace fossil fuels for tackling climate change by reducing emissions. This study explores the spatial spillover effect in biomass energy carbon reduction, which is frequently ignored when investigating environmental factors. It uncovers whether globalization and its dimensions can strengthen the spatial effect of biomass energy carbon reduction. Besides, we reveal whether biomass energy consumption can promote CO2 emissions reduction while ensuring economic progress. Results show that (1) owing to the spillover effect, biomass energy consumption plays a significant role in direct and indirect enhancing carbon emissions reduction, with their feedback effects of - 0.003 or 3.3% of the direct effect. (2) Increasing overall, social and political globalization enhances biomass energy consumption's carbon reduction effect. (3) In countries with higher economic development, overall, economic and political globalization has a better promotion in the spatial effect of biomass energy carbon reduction. (4) Developing biomass energy can support the environment quality while enhancing economic growth.

Mechanism research on digital inclusive finance promoting high-quality economic development: Evidence from China.

This article aims to precisely evaluate the catalytic impact of digital inclusive finance on economic growth, enhance the implementation of policies pertaining to digital inclusive finance, and foster high-quality economic development. Based on China's provincial panel data and the digital inclusive finance index from 2011 to 2021, this research investigates the influence of digital inclusive finance on high-quality economic development and the associated underlying mechanisms. The findings suggest that digital inclusive finance exerts a notable spatial impact on high-quality economic development. Moreover, there is heterogeneity in the spatial effects between different dimensions of digital inclusive finance and high-quality economic development. Through the threshold model and intermediary effect model, it is found that the Internet penetration rate has a dual-threshold effect on the impact of digital inclusive finance on promoting high-quality economic development. Specifically, digital inclusive finance contributes to elevating the level of high-quality economic development through its role in promoting the transformation of consumption structure. The findings of this study offer valuable insights for countries aiming to attain high-quality economic development through the enhancement of digital inclusive finance.