There has been a lot of talk about AI in recent years, but mostly from two perspectives. First, there is significant interest in the issue of the relationship between AI and the political environment, which raises numerous questions regarding the temptation of dictatorships, as well as the far from innocent methods used to conduct electoral campaigns. The second major area of interest in AI research is related to the labour market, specifically how it is influenced and changed in real time, implicitly considering the situation of jobs lost or newly created. There is one aspect that influences both the labour market and a country's political choices, and that is demography. Obviously, it is not the only factor and cannot be analysed without considering its determinants: the economy, legislation, healthcare systems, etc. Since countries do not have the same population nor the same birth rates, it is important to try to understand "something" about the effects that new technology will bring to this area of interest, because from this we can make certain forecasts about the development of some countries, the decline of others, and – under certain conditions – even about changes to the borders of some countries. At this moment, it seems that governments (no matter their economic development level) are not fully aware of the changes that AI will bring regarding interpersonal relationships. If they are only interested in the political aspect, they will see that the demographic future of their own countries could also be influenced by AI devices, which become so integrated into the life of the average person and can completely change their outlook on life visions for having children, at least. As a result of these changes of children visions, however, it is possible that we will see countries seeking, including, unification with countries that are demographically stronger, because the population decline as an effect of AI will impact public budgets so much that they will become unsustainable, forcing the governments to search for a form of "saving the passive" through unification with other countries.

Abstract We consider in this paper the impact of democracy and education on pollution over the period 2002–2021 for a panel of 42 countries using the PMG-ARDL estimation technique. We consider different levels of economic development, of income and democracy. Our results show that a higher level of school enrollment (EDU) increases the level of pollution. Also improvement in the political life of developing countries can have less pollution. We also show that democratic low-income countries pollute more than democratic high-income countries. However, countries pollute more as they became more autocratic and when they are endowed with higher levels of schooling. More findings in our study show that democracy in developing countries yields better educational outcomes that in turn, improve pollution. Our results report that, above a certain level of education, the benefits in terms of awareness are wiped out by the pollution stemming from the boom in economic activity and growth in developing countries. However, the costs in terms of pollution are sponged by the environmental awareness stemming from the educational outcomes for developed countries. More findings in our study show that countries tend to benefit less from a democratic environment as they move to higher income levels. Our estimation show the existence of a bidirectional causal relationship between our variables of interest.

After the carbon neutrality goal was proposed, the question of how to achieve low-carbon and green development has become the focus of ASEAN countries. The digital economy will play an important role in promoting carbon emission reduction in ASEAN countries. This paper measures the digital economy index of ASEAN countries and explores the impact of the digital economy on carbon emission intensity across 10 ASEAN countries from 2011 to 2020. The results show that the digital economy can reduce the intensity of carbon emissions in ASEAN countries. In addition, the impact of the digital economy on carbon emission intensity will vary depending on the level of economic development, resource endowment, and government financial support capacity. The mechanism analysis shows that the digital economy can ultimately reduce the intensity of carbon emissions by promoting industrial structure upgrading, stimulating technological innovation, and promoting the transformation of energy consumption structure. Based on the above conclusions, specific recommendations are proposed for the digital economy to realize carbon reduction in ASEAN countries.

ABSTRACT This paper reveals the cultural factors behind the disparities in the development of non‐cash payment across different countries from the perspective of religious beliefs, using cross‐country survey data provided by the World Bank. Our findings indicate that religious beliefs as culture exert a significant influence on the use of non‐cash payments. Specifically, a higher proportion of Protestant population significantly promotes the adoption of non‐cash payments compared to other religions. These results remain robust even after controlling for a comprehensive set of factors, including economic development level, infrastructure, related institutions, and social structure. Furthermore, estimates using the local number of donated Bibles in 1900 as an IV remain consistent with our baseline OLS estimates. We also identify social trust as a primary mechanism through which Protestantism encourages the use of non‐cash payment, while the development of government credit information systems can, to some extent, mitigate the negative influence of religion on non‐cash payment adoption.

Since the early 2000s accelerated industrialization, urban population growth, and increased energy consumption have led the People’s Republic of China (PRC) to become the world’s largest source of greenhouse gas (GHG) emissions, which continue to rise. This has created a necessity for transitioning to a low-carbon economic development model, especially under international pressure and the country’s ambitious goal of achieving carbon neutrality by 2060. A distinctive feature of China’s current climate policy is its focus not on absolute emission reductions, but rather on reducing emissions per unit of gross domestic product (GDP), i.e., lowering the carbon intensity of the economy. The aim of this study is to analyze the evolution of China’s climate policy and assess the effectiveness of market-based GHG emission regulation tools, such as emissions trading systems and carbon credit mechanisms, in the context of reducing the economy’s carbon intensity. The research is based on an analysis of government documents, data on carbon market functioning, and scientific literature. Comparative analysis and statistical modeling were employed to evaluate emission dynamics and the effectiveness of climate policy instruments. The analysis shows that in recent years there has been a decline in the ambition of climate policy; however, carbon markets demonstrate positive results, although they face several challenges and limitations: insufficient data transparency, low allowances prices and liquidity, potential carbon leakage, and a shortage of carbon credits. The concluding part of the study emphasizes that the reduction in carbon intensity may be related not only to state efforts, but also to the Kuznets curve, according to which GHG emissions begin to decline after reaching a certain level of economic development. To achieve the long-term goal of carbon neutrality in the PRC, further improvement of climate policy is necessary, including replacing targets for reducing emission intensity with limits on absolute emission volumes, as well as strengthening control within ETSs and carbon crediting mechanisms.

The problems of industrial agglomerations have been widely studied due to its important role in regional economic development. However, in the era of digital economy, due to its characteristic of ignoring geographical and spatial limitations, this phenomenon fundamentally challenges the traditional industrial agglomeration model. The relevance of this study is determined by the lack of research on the impact of the digital economy on the agglomeration of traditional manufacturing industries, especially in terms of regional heterogeneity and mechanism. Based on panel data of 31 provincial administrative regions in China from 2012 to 2022, this study uses an empirical model to analyze the impact of the digital economy on the level of industrial agglomeration in various provinces in China and deeply explores its mechanism and regional heterogeneity. The research results show that the development of the digital economy has significantly inhibited the agglomeration of traditional industries. Further, this inhibitory effect is weakened in regions with higher levels of economic development. As a key interaction term, the per capita GDP level directly affects the impact of the digital economy on industrial agglomeration. Further mechanism test results confirm that the digital economy can jointly affect industrial agglomeration through direct and indirect paths. As a key mediating variable, the digital economy can weaken industrial agglomeration through the “deindustrialization” path.

The deepening processes of globalization and industrialization have given rise to widespread disparities in regional economic development across countries worldwide. As a result, differences in resource endowments, industrial structures, and policy support among regions have led to significant disparities in economic growth rates and development levels. This study investigates the factors behind regional economic disparities and how economic development and population mobility influence each other, highlighting how variations in industrialization, resource distribution, and market-driven economic clustering contribute to the expansion of regional gaps. Through a literature review and comprehensive analysis, the study compares representative regions such as the United States and the European Union to identify the key factors driving regional economic differences and the economic feedback effects of population migration. The results show that differences in industrialization speed, unequal fiscal and financial resource distribution, and market agglomeration effects are the main reasons for the expansion of regional economic disparities. Thus, developed regions, with well-established infrastructure and public services, attract large population inflows, as opposed to less-developed regions, experiencing persistent outflows of capital and talent. At the same time, moderate migration supports resource allocation and industrial change, while excessive inflow strains housing, transport, education, and the environment.

In this paper we develop and test the hypothesis that natural disasters influence global sourcing complexity. Employing rich data from 128 nations between 1997 and 2014, our findings suggest that the occurrence of natural catastrophes drives firms to purchase the same intermediate goods from multiple suppliers and nations, and as consequence natural disasters foster global sourcing complexity. The paper further explores the boundary conditions of various forms of natural disasters, the level of economic development, long-term orientation culture, and banking crisis of a particular country on the relationship between natural disasters and global sourcing complexity. Thus, our study adds to and extends the global sourcing literature in the context of natural disasters and holds managerial relevance regarding managers’ response to natural disasters.

Accelerating urban low-carbon transition is vital for high-quality economic growth and sustainable development. The energy industry, a key driver of socioeconomic progress, is the main source of carbon emissions and is crucial for decarbonization. Optimizing its structure is essential for urban low-carbon transformation. Based on the panel data of 284 prefecture-level cities in China from 2003 to 2022, this study decomposes the optimization of the energy industry structure into basic structure optimization and spatial structure optimization, uses green total factor productivity (GTFP) to measure the level of urban low-carbon transformation, and uses the super-efficiency SBM model to calculate it, deeply explores whether and how the optimization of the energy industry structure affects the low-carbon transformation of cities and analyzes the mechanism effect of the level of green technology innovation in it. The results show that both the optimization of the energy industry basic structure and the optimization of the energy industry spatial structure can promote the low-carbon transformation of the city, and the results are still valid after the endogenous test and robustness test. The level of urban green innovation will play a positive moderating effect on the optimization of the energy industry structure on its low-carbon transformation and development. The relationship between energy industry structure optimization and urban low-carbon transformation is obviously heterogeneous in different regions, not only in different geographical locations, but also in different levels of economic development.

As a fundamental driver of worldwide economic expansion, the digital economy significantly influences decisions regarding cross-border investment. The implementation of the Regional Comprehensive Economic Partnership (RCEP) creates conducive conditions for advancing the digital economy within its member countries. To identify the impact of host countries digital economic development on China's outward foreign direct investment (OFDI), this study constructs a comprehensive indicator system for national digital economic development within the RCEP framework. Principal component analysis is employed to measure the digital economic development levels of RCEP member states, with empirical research conducted using a fixed-effects model. The analysis identifies the host country's digital economic capacity as a key driver stimulating China's OFDI flows. Among sub-indicators, digital infrastructure and institutional and technological innovation environments exert particularly strong promotional effects. The impact of the digital economy on China's outward foreign direct investment varies significantly according to the economic development levels of the host countries.

Background: Peripheral artery disease (PAD) significantly contributes to cardiovascular morbidity. Smoking, a key modifiable risk factor, accelerates PAD progression and increases risks of cardiovascular events, limb loss, and reduced quality of life. Yet, the global burden of smoking-related PAD remains understudied. Methods: Smoking-related lower extremity PAD data were sourced from the GBD 2021 study. Age-standardized death rates (ASDR) and disability-adjusted life years (DALY) from 1990–2021 were analyzed for the U.S. and compared to high socio-demographic index (SDI) countries with comparable economic development and education levels. Annual percentage change (APC), average APC difference (AAPCD), and 95% confidence intervals (CI) assessed relative burden changes. Significance was set at p<0.05. Results: In the U.S., smoking-related PAD ASDR dropped from 0.51 (95% CI: 0.38–0.65) in 1990 to 0.37 (95% CI: 0.27–0.48) in 2021. It rose from 1990–1995 (APC: 3.51; 95% CI: 2.71–4.39; p<0.01), then declined in 1995–2002 (APC: -0.80; 95% CI: -1.36 to -0.28; p<0.01), 2002–2009 (APC: -4.66; 95% CI: -5.47 to -4.17; p<0.01), and slowed in 2009–2021 (APC: -0.73; 95% CI: -0.96 to -0.44; p<0.01). In high SDI countries, ASDR declined from 0.49 (95% CI: 0.38–0.63) to 0.26 (95% CI: 0.19–0.34), with consistent reductions and no 2010–2019 deceleration as seen in the U.S. (Figure 1: Left Panel). Overall ASDR decline was greater in high SDI countries (AAPCD: -1.25; 95% CI: -1.54 to -0.96; p<0.01). U.S. DALY rate fell from 13.90 (95% CI: 10.23–18.33) in 1990 to 10.51 (95% CI: 7.62–13.94) in 2021. It rose from 1990–1995 (APC: 2.16; 95% CI: 1.47–3.00; p<0.01), declined in 1995–2002 (APC: -1.08; 95% CI: -1.59 to -0.60; p<0.01) and 2002–2009 (APC: -3.70; 95% CI: -4.62 to -3.26; p<0.01), then slowed in 2009–2021 (APC: -0.32; 95% CI: -0.55 to -0.06; p=0.02). High SDI countries saw DALY rates drop from 12.42 (95% CI: 9.27–16.34) to 7.14 (95% CI: 5.22–9.63) with consistent declines (Figure 1: Right Panel). Their overall reduction exceeded that of the U.S. (AAPCD: -1.08; 95% CI: -1.31 to -0.85; p<0.01). Conclusions: Mortality and disease burden from smoking-related PAD declined in both the U.S. and high SDI countries from 1990 to 2021. However, in the past decade, the rate of decline in the U.S. has slowed compared to high SDI countries. Our study highlights the need for stricter smoking control programs, the development of effective PAD screening guidelines, and prompt public health action.

Industrial parks as critical carriers of China’s industrial development, they face significant pressure for low-carbon transformation. Current research on carbon emissions primarily focuses on national or sectoral levels, leaving a gap in understanding the driving factors and the carbon emissions–economic development mechanism at the industrial park level, which hinders precise emission reduction strategies. This study examines 44 industrial parks in the Yangtze River Delta, analyzes the temporal evolution of carbon emissions and assesses the economic development levels of the industrial parks based on the TOPSIS model. The Tapio decoupling model is adopted to analyze the decoupling status between carbon emissions and economic development, while the LMDI decomposition method is used to explore the driving factors. Empirical findings reveal that carbon emissions in these parks exhibit fluctuating growth, the decoupling state between carbon emissions and economic development is predominantly weak, transitioning to strong decoupling by 2023, key factors driving carbon emissions include per capita industrial development levels and industrial land scale effects. The combined application of the Tapio decoupling model and LMDI decomposition demonstrates universality in analyzing carbon emission drivers in industrial parks, providing theoretical and practical insights for carbon reduction in industrial parks.

ABSTRACT Climate change and energy security are two fundamental vulnerability areas that interact with each other and hold critical importance for sustainable development goals. This research aims to fill the research gap by investigating the effects of climate change vulnerability (CCV) on the energy vulnerability (EV) relationship, which has not been adequately addressed in the literature, using a large panel dataset covering 74 countries and employing various methodological approaches (MMQR, PLFC, DID). The results of the MMQR model indicate that CCV increases EV across all quantiles. According to the results of the PLFC model, it is revealed that CCV on EV varies depending on the economic development level of countries. This effect is higher in low‐income countries. The study also employs the DID model to examine the impact of China's foreign energy investments on countries' EV. According to this model, China's fossil‐based energy investments, particularly those in the energy sector, increase the EV of countries. While economic development reduces EV across all quantiles, financial development reduces it in the lower and medium quantiles (25% and 50%); urbanization reduces it in the medium and higher quantiles (50% and 75%). All results show that the interaction between EV and CCV is a multidimensional and dynamic process. Accordingly, policymakers should develop integrated strategies that consider environment and energy policies, economic development, investment type, and environmental risks. Lastly, policymakers should consider energy investments from China not only as a tool for their country's economic growth, but also in terms of energy security and sustainability.

This paper is an attempt to explore the complex international jurisprudential system that informs the policies related to subsidy and trade law in the area of agriculture, mainly looking at how it is used to differentiate between the aspects of agriculture and farmers in India and EU member states. The study uses the comparative approach to observe the way in which the agreements such as WTO-agreements to Agriculture (AoA) and subsidies and countervailing measures (SCM) help to trigger the policy of Agriculture and trade relations. The study further uses new feature extraction techniques for generating low-dimensionality agricultural datasets to derive potent factors that determine agricultural competitiveness and farmer welfare across the two economies. Results indicate considerable differences between developed EU countries and poor India in subsidy schemes according to their different existing legal frameworks, leading to disparate consequences for their agricultural sectors. An investigation indicates that while farmers in the EU enjoy developed support mechanisms defined as minimally trade distorting, Indian farmers suffer from more risks now under the current international trade norms. Agriculture remains a very important lifeline security for many of these farmers. The last part of the research recommends reforms in the policy for a better international agricultural trade creation concerning the efficiency side of the economy, considering rural development and food security across different levels of economic development.

Competition law aims to promote fair market practices and prevent monopolistic behaviour, while political economy explores the relationship between economic systems and political institutions. Together, these disciplines shape the regulatory frameworks that oversee national markets and economic policies, encouraging competition and tackling issues such as inequality and market inefficiencies. In developing countries, the influence of political economy tends to be more significant than in developed nations, which usually benefit from more stable democratic institutions and stronger legal systems. Among ASEAN member states (AMS), there is notable variation in levels of economic development, policies, political structures, and legal frameworks. Consequently, each AMS’s unique political and legal history has influenced its approach to economic management and competition law, leading to distinct priorities and concerns. These political economy factors similarly impact the process of regional competition law integration among ASEAN countries. This paper explores how political economy shaped the enactment and enforcement of competition law in selected AMS: Malaysia, Vietnam, Thailand, and Indonesia. It analyses the underlying reasons for their specific reservations, exemptions, and priorities within their competition law. Using qualitative legal research and comparative analysis, the study reviews relevant political economy structures, statutes, regulations, and policies in the chosen AMS to assess their significance and influence on competition law administration. The findings indicate that ASEAN’s regional competition law alignment and integration must recognise each AMS’s broader internal political economy, which is vital for developing competitive markets within ASEAN.

Analysis on spatial pattern evolution and policy of CO2 emissions from economic sectors in China from 2005 to 2020.

This study explores the transformative role of digital economy development on digital service trade exports, using China as a case study, to elucidate trends and lessons that may be applicable to other nations seeking to leverage digital advancements for economic growth in an increasingly interconnected global market. Analyzing panel data from 105 global economies between 2013 and 2021 with a trade gravity model, supplemented by robustness and heterogeneity tests, we demonstrate that the development level of the digital economy in trading nations significantly enhances China’s digital service trade exports, particularly impacting middle- and high-income countries. The sectors most affected include intellectual property and cultural services. Our findings reveal a notable positive correlation between digital economy indices and digital service export volumes, suggesting that advancements in digital infrastructure, market dynamics, and governance in partner countries facilitate this increase. Geographical distance and economic systems also play crucial roles, influencing trade costs and compatibility, respectively. These insights guide targeted policy recommendations to enhance digital service trade, emphasizing the need for strategic international cooperation and infrastructure investment to harness digital globalization’s full potential.

The rapid popularization of digital technology is profoundly altering the employment landscape; especially in rural areas, the digital economy has opened up unprecedented channels to narrow the gender gap in non-agricultural employment. This study utilizes data from the China Family Panel Studies (CFPS) from 2014 to 2020, employing a two-way fixed effects model to systematically examine the impact of digital literacy on the non-agricultural employment transition of rural women. The findings demonstrate that integrating social learning theory with digital empowerment theory establishes a dual-pathway analytical framework for examining psychological capital and information environments. Through skill development and resource optimization, digital literacy significantly enhances rural women’s employment participation and occupational re-adaptability, with these effects varying across regions and generations. Furthermore, the study reveals how household economic resources and regional development levels exert differential influences on these outcomes by affecting the acquisition and application of digital skills. These findings expand theoretical understanding of non-agricultural employment mechanisms in the digital era and offer practical policy insights. They also provide evidence-based strategies for enhancing women’s employment quality, advancing gender equality, and promoting rural revitalization, offering valuable guidance for developing countries navigating employment challenges through digital transformation.

Gout represents the most common form of inflammatory arthritis, exerting a substantial impact on patient quality of life and productivity. In recent years, the age distribution of gout has shifted, with an increasing incidence among younger individuals. Accurate statistics regarding the incidence, prevalence, and disability-adjusted life years (DALYs) associated with gout in this population are critical for effective resource allocation in prevention and treatment strategies. In the current study, data from the 2021 Global Burden of Disease (GBD) database were used to analyze the burden of gout among young people aged 15–44 years in 204 countries and territories from 1990 to 2021, with projections extending over the next 25 years. Data on prevalence, incidence, and DALYs were collected and stratified by geographical location, gender, and economic development level. Decomposition analysis and predictive modeling were employed to evaluate trends and the impact of critical indicators. In 2021, 8,516,229 young individuals were affected by gout globally, with 1,975,165 new cases and DALYs totaling 283,725 person-years. Since 1990, the age-standardized prevalence rate, age-standardized incidence rate, and age-standardized DALYs rate increased by 10.4%, 9.4%, and 10.2%, respectively, all showing positive correlation with the sociodemographic index (r = 0.319, 0.272, 0.320, P < 0.001). It is projected that by 2046, global figures in young people will reach approximately 9,229,870 total cases, 2,202,802 new cases, and 307,441 DALYs. Males are anticipated to account for 7,460,349 affected individuals, 1,762,412 new cases, and 245,542 DALYs, whereas females will represent 1,769,521 affected individuals, 440,390 new cases, and 61,899 DALYs. The global disease burden of gout among young people increased significantly from 1990 to 2021, and it is expected to continue rising over the next 25 years. Comprehensive epidemiological data remain essential for guiding gout prevention and management, as well as shaping effective health policies.

Abstract The developed world has been gradually moving towards a lower level of working hours and higher incomes during the post-war era. This is reflected in countries’ increasing levels of labor productivity (Gross Domestic Product per hour worked). Although time spent at work and earnings are critical in fertility decisions, the potential fallout of the outlined evolution on fertility rates has remained relatively unexplored. Employing quantile regression analysis for the period 1970–2010 at varying levels of economic development, we find a non-linear (convex) relationship between labor productivity and fertility. The effect of productivity increases with economic advances, which, as we show, highlights the crucial role of female labor force participation. It peaks at the fertility distribution where individuals of older reproductive ages (30–49) work, on average, longer hours. These findings indicate that rising labor productivity may have contributed to the fertility rebound observed in the early 21st century.