The current stage of Russian economic development is characterized by foreign policy and economic pressure from a number of Western countries. Sanctions restrictions, introduced in 2014 and sharply strengthened after 2022, have affected virtually all sectors of the national economy, including agro-industrial complex - a key sector ensuring the country’s food security. Agro-industrial complex plays a strategic role in ensuring Russia’s independence from food imports. Sustainable and profitable agricultural enterprises not only maintain but also increase domestic production of essential food products, which is especially important given the closure of traditional foreign markets and risk of supply disruptions. Sanctions have led to a sharp increase in the prices of imported resources: seeds, crop protection products, agricultural machinery and spare parts. Furthermore, logistics routes have changed, increasing transportation costs and delivery times. Limited access to foreign technologies and equipment requires farmers to quickly adapt: switching to domestic equivalents, localizing production chains, and implementing digital solutions and innovations. All of these processes require significant investment, which is only possible if enterprises are financially stable and capable of generating profits. In response to the sanctions, the government has stepped up support measures for the agricultural sector: subsidizing loan interest rates, partially compensating for equipment purchase costs and supporting processing plants and exporters. However, the effectiveness of these measures directly depends on the financial literacy and sustainability of the enterprises themselves – only stable enterprises are able to effectively utilize state support for long-term growth. An analysis of the experience of agricultural enterprises in the Republic of Tatarstan allows us to identify effective adaptation strategies, assess the role of regional policy, and outline paths for further development of the industry in the face of ongoing geopolitical instability. An empirical analysis of six leading agricultural enterprises in the Republic of Tatarstan for 2019-2023 revealed that total revenue increased from 13.4 billion to 19.9 billion rubles, while net profit decreased from 6.0 billion rubles in 2020 to 1.7 billion rubles in 2023, indicating a decline in operational efficiency. A panel regression analysis revealed no statistically significant relationship between debt burden and profitability (R2 = 0.0043; p = 0.912), while 45.8% of profit variance was explained by individual enterprise characteristics. These results highlight the need to shift from short-term adaptation to systemic financial sustainability through modernization, digitalization, and equity development.

Unveiling the linkage between low-carbon energy and energy sources diversification.

The initial stages of economic development are generally characterized by rising per capita income alongside structural changes in both production and export activities. These changes often entail the development of new products and the establishment of additional trade partnerships, thereby fostering broader diversification within the economy. This study therefore, examined the effect of consumer goods and industrial products standard on export diversification in South Africa. The study employed Generalized Least Square (GLS) Model which estimated the effect of European Union (EU) product standards and the harmonized EU product standard (EU_ISO). Data used for the analysis were from year 2011 to 2022, and were sourced from WIT-TRAINS, and WDI. The results revealed that the distance and common language were positive and significantly affects countries ceramic (ED_CER) export diversification (P = 0.000; 0.001). However, the effect of distance on ceramic (ED_CER) was stronger than its effect on sugar & confectionary (ED_SUC). This implies that the farther away the countries are from each other, the larger the export basket and that export diversifications are not only driven by standards requirements but by language and distance. The EU standard positively affected both sugar & confectionary and ceramic export diversification (P = 0.941; P = 0.638). This indicates that a one per cent increase in the EU product standard results into 0.9 and 0.6 per cent increase in sugar & confectionary and ceramic export diversification. The result also revealed that the EU standards that are harmonized with ISO standards are positive (P = 0.465) on South Africa’s sugar & confectionary export diversification. The study concludes that South Africa’s export diversification and the harmonization of the EU to international standards acts have beneficial factors even when the overall impact of product standards was positive but insignificant. The study recommends that the development of infrastructure should be given importance as it leads to reduction in transaction cost (distance) of trade.

A significant forum of scholarly and practitioner-based research has developed in recent years that has sought both to theorize upon and empirically measure the competitiveness of regions. However, the disparate and fragmented nature of this work has led to the lack of a substantive theoretical foundation underpinning the various analyses and measurement methodologies employed. The aim of this paper is to place the regional competitiveness discourse within the context of theories of economic growth, and more particularly, those concerning regional economic growth. It is argued that regional competitiveness models are usually implicitly constructed in the lineage of endogenous growth frameworks, whereby deliberate investments in factors such as human capital and knowledge are considered to be key drivers of growth differentials. This leads to the suggestion that regional competitiveness can be usefully defined as the capacity and capability of regions to achieve economic growth relative to other regions at a similar overall stage of economic development, which will usually be within their own nation or continental bloc. The paper further assesses future avenues for theoretical and methodological exploration, highlighting the role of institutions, resilience and, well-being in understanding how the competitiveness of regions influences their long-term evolution.

IntroductionThis study aimed to systematically analyze the spatiotemporal heterogeneity and drivers of the kidney cancer burden across BRICS member countries (Brazil, Russia, India, China, South Africa, Egypt, Ethiopia, Indonesia, Iran, Saudi Arabia, and the United Arab Emirates) from 1990 to 2021. Given the significant global rise in kidney cancer incidence, elucidating its epidemiological characteristics and influencing factors in countries at different stages of economic development is crucial for formulating targeted prevention and control strategies.MethodsThis study innovatively integrated Joinpoint regression and Age-Period-Cohort (APC) modeling using data from the Global Burden of Disease (GBD) 2021 study to quantify trends in kidney cancer incidence and mortality in BRICS nations. The APC model was employed to disentangle the independent effects of age, period, and birth cohort on the disease burden. These findings were subsequently interpreted in the context of national socioeconomic conditions and health policies to identify key drivers.ResultsGlobally, kidney cancer incidence increased by 142.74% from 1990 to 2021. Saudi Arabia experienced the most dramatic increase (877.78%), while Russia reported the highest Age-Standardized Incidence Rate (ASIR) in 2021 (10.10 per 100,000). Global mortality rates increased by 108.22%, led by the United Arab Emirates (700% growth), with Russia exhibiting the highest Age-Standardized Mortality Rate (ASMR) in 2021 (4.07 per 100,000). Furthermore, APC analysis identified critical drivers: the age effect peaked in the older populations (e.g., Russia’s mortality rate reached 42.8 per 100,000 at age 92.5); the period effect showed a surge in risk after 2000 in most nations (Saudi Arabia’s period Rate Ratio [RR]: 1.52); the cohort effect indicated a 6.60-fold elevated risk for China’s 2002 birth cohort compared to the 1952 baseline, contrasting with declining risks in younger Russian cohorts (RR: 0.66). Regional disparities highlighted interactions between economic transitions and health inequities. Specifically, Saudi Arabia’s burden was associated with metabolic disorders, Russia’s decline aligned with tobacco control initiatives, and India’s rural underdiagnosis reflected critical healthcare gaps.DiscussionThe kidney cancer burden in BRICS countries demonstrates significant spatiotemporal heterogeneity, driven by mechanisms related to population aging, the prevalence of metabolic risk factors, and disparities in healthcare accessibility. The findings underscore the necessity of strengthening environmental governance, implementing metabolic health interventions, and optimizing healthcare resource allocation to advance health equity and achieve Sustainable Development Goals. These insights provide a scientific basis for developing cross-regional strategies for cancer control.

The current stage of economic development is characterized by rapid transformations, intensified competition, and the comprehensive digitalization of business processes. Under these conditions, marketing research has acquired strategic importance as a key tool for making managerial decisions based on objective data. Accordingly, there is a growing need to implement innovative approaches that ensure the fast acquisition, accurate processing, and deep interpretation of market information. Traditional data collection methods — such as surveys, focus groups, and expert evaluations — are increasingly giving way to digital technologies that integrate Big Data, Artificial Intelligence (AI), Machine Learning, automated online surveys, and neuromarketing tools. The aim of the study is to systematize and scientifically substantiate innovative marketing research tools that can enhance the efficiency of analytical processes and the quality of managerial decision-making. The scientific novelty lies in identifying the transformation trends of marketing analytics in the digital economy and determining the synergy between traditional and innovative data analysis methods. Particular attention is paid to the use of artificial intelligence technologies for predicting consumer behavior, the implementation of automated data collection systems to minimize human error, and the role of neuromarketing in shaping emotionally driven strategies for influencing target audiences. The research results confirm that digital tools significantly improve forecasting accuracy, reduce data processing time, and increase business adaptability in uncertain environments. However, the effective use of these technologies requires an integrated approach — the combination of multiple data sources, ensuring information security, improving marketers’ digital literacy, and developing flexible analytical systems. The conclusions highlight that innovative marketing research tools are becoming a critical factor in the competitiveness of enterprises in the era of digital transformation. Further scientific development in this field should focus on creating adaptive data analysis models that combine the technological capabilities of artificial intelligence with the practical needs of marketing management.

ABSTRACTAlthough the growth in developing countries have always been accompanied by large‐scale land expropriation, whether there is a standard relationship between the scale of land expropriation and the stage of economic development remains unclear. This paper aims to explore the practice of land expropriation in China, and while there are polarized views around its role in economic growth, inter‐provincial differences also mean that it is an excellent sample for clarifying the relationship. By exploring the growth coalition consisting of local bureaucracies, central government and peasants within the land‐centered development model, the possible inverted U‐shaped trend of land expropriation scale with economic development is theoretically analyzed, from which hypotheses on the Land‐expropriation Kuznets Curve (LKC) are proposed. Further, using Chinese provincial panel data, the results not only show the invert‐U shaped relationship between economic development and land expropriation and its regional heterogeneity, but also identify four determinants of dependence on land expropriation: internal demands of local bureaucracies to advance urban infrastructure, real estate and manufacturing sectors, horizontal competition among local bureaucracies, vertical supervision by the central government, and external forces from peasants. These conditions combine to expand the scale of land expropriation in the less developed period, leading to the phenomenon of land expropriation dependence. However, with the transformation of China's economic growth and development model, changes in above‐mentioned various conditions have made it possible to reduce land expropriation dependence, and the reduction typically occurs when GDP per capita exceeds 50,000 RMB. This paper provides a new perspective for understanding China's land‐centered development story based on the Growth Machine Theory and generates policy implications for the land management practices in other developing countries.

Abstract Since the 2010s, the proportion of processing trade in total trade in China has been declining year by year. Meanwhile, given the different stages of economic development across regions in China, the situation of processing trade might vary by region. This paper analyzes the realities of processing trade in different regions of China based on the regional input–output tables of 28 provinces, cities, and autonomous regions, measuring the Vertical Specialization (VS) index. The analysis reveals that the VS index levels in the eastern regions are higher compared to the central and western regions. From 2012 to 2017, the VS index in the eastern regions showed a declining trend, while in the central and western regions, many areas experienced an increase. Second, decreasing reliance on import inputs from processing exports was observed in the results of a newly proposed indicator. At last, the analysis of the VS index and per capita GDP shows that although the VS index rises with increases in per capita GDP, once per capita GDP surpasses a certain level, the VS index may shift from increasing to decreasing.

Topicality. Post-war development of Ukraine today is mainly aimed at restoring critical infrastructure and improving the well-being of the population. Today, 225 projects with a total value of more than 500 mln. euros are being implemented. However, no funds are actually allocated for the restoration of natural assets. At the same time, the international experience of countries with post-war recovery, such as Vietnam, Rwanda, Bosnia and Herzegovina, Lebanon proves that it is the capitalization of natural resources through various state, joint and international programs of an ecological and economic direction that contributes to long-term economic growth, attracting project financing and improving the well-being of the population. In Ukraine, there are currently international initiatives to support development in accordance with EU standards, which are focused on resource efficiency, sustainable use of water bodies, and the development of sustainable entrepreneurship. The implementation of international initiatives requires a review of the institutional framework to meet the requirements for the implementation of project initiatives. Thus, despite the international experience of post-war recovery based on the capitalization of natural resources, imbalances persist, such as the concentration of investments on infrastructure recovery without the integration of natural capital, which threatens the loss of strategic opportunities in the resort economy. Aim and tasks. The purpose of the article is to identify patterns of changes in natural resource management models based on a comparison of international and Ukrainian approaches to financing and managing natural assets, identify contradictions and imbalances in the capitalization of natural resources, conduct a retrospective analysis of natural resource management models, and substantiate ways to capitalize natural resource assets in the post-war period for the rehabilitation of the country's economy. Materials and Methods. The determination of the theoretical basis of the study was carried out by analyzing the institutional framework, generalizing it, and substantiating the conceptual provisions of natural resource capitalization, using methods of comparative analysis and generalization. Research results. The article analyzes changes in institutional support and models of natural resource management and their capitalization into natural healing assets at the stages of the state's economic development. The main trends and disparities are identified, and, based on international experience; changes are presented in the activities of the main authorities in order to exercise clearer control over the extraction, use and restoration of assets. Conclusion. The analysis of natural resource management models and their capitalization proves numerous institutional problems and disparities. Historically, the management of natural therapeutic resources was dispersed between different departments and forms of ownership, which led to inconsistency and inefficiency. Given the above, it is necessary to update approaches to natural resource management and their capitalization without creating new bodies, using the mechanisms of already existing provisions of central government bodies, integrating medical, geological, sanitary and digital components according to the European model in the context of post-war recovery and economic growth.

BackgroundAlthough some studies have reported correlations between economic factors and suicide rates, there is a lack of systematic analysis from a global data perspective.MethodsThe most recent suicide rates (from 2017 to 2019) were obtained from the World Health Organization (WHO). The economic variables were obtained from the World Bank (WB) website. Software was used to match the suicide rates and the related variables from the database, country by country. Statistical methods were used to analyze the correlations between them.ResultsEconomic indicators, such as national income level, GDP per capita, GNI per capita, and the Gini index, are negatively correlated with suicide rates. However, this correlation was not consistent across all countries, and the direction of the association varied depending on the income levels of the countries. GDP per capita, GNI per capita, and the consumer price index were negatively correlated with suicide rates in the low-income group. A statistically significant correlation between the consumer price index and the Gini index was found in the lower-middle- and upper-middle-income groups, respectively. GDP per capita, GNI per capita, and the consumer price index showed positive correlations, but the Gini index had a negative correlation with suicide rate in the high-income group.ConclusionThe correlations between economic indicators and suicide rates vary by national income level, playing different roles at different stages of economic development. Differentiated and targeted monitoring of economic indicators has practical implications for suicide prevention.

Eye injury poses a significant challenge to the global burden of blindness. Using the Global Burden of Disease (GBD) database, this study aims to comprehensively assess the latest global burden of eye injury and examine its relationship with the Socio-Demographic Index (SDI). Observational study. Population-based data on eye injury from the GBD 2021 database, covering the period 1990-2021. Primary outcomes included incidence, prevalence and years lived with disability (YLDs) due to eye injury. Secondary outcomes included temporal trends analysed using joinpoint regression, age-period-cohort effects, health inequality indices (Slope Index of Inequality (SII) and Concentration Index) and decomposition analysis of contributing factors. From 1990 to 2021, global eye injury incidence (in thousands) increased from 33 702.80 (95% uncertainty interval (UI): 27 271.41 to 44 086.12) to 39 996.91 cases (95% UI: 32 341.74 to 52 215.74), while age-standardised incidence rates (ASIR) declined from 622.73 to 503.26 per 100 000 population (average annual percent change (AAPC): -0.63, 95% confidence interval (CI) -0.81 to -0.46, p<0.001). High SDI regions showed the highest ASIR (775.56 per 100 000) compared with low SDI regions (368.26 per 100 000) in 2021. Males bore a greater burden, particularly in high-middle SDI regions (ASIR: 989.98 vs 317.09 per 100 000 for females). Age-period-cohort analysis revealed young adults (20-24 years) had the highest risk across all regions, while high SDI regions uniquely showed accelerating rates among the elderly (>75 years). Health inequality between SDI regions narrowed (SII decreased from 3.10 to 2.21 per 100 000), with population growth contributing 207.93% to increased incidence. The burden of eye injury exhibits distinct patterns across development levels, requiring tailored interventions: occupational safety for young adults in developing regions and fall prevention for the elderly in developed areas. Prevention strategies should align with regional economic development stages, emphasising workplace safety in industrialising regions while maintaining robust healthcare accessibility.

ABSTRACT Substantial investments are often required to adapt our infrastructure to a changing climate. To decide whether these investments are worthwhile (i.e. cost-effective) or not, cost–benefit analyses have been proposed and applied. The results of these analyses have been found to be strongly influenced (or even completely governed) by the adopted discount rates. Nonetheless, the discount rates used in these cost–benefit analyses are often arbitrarily assumed and are inconsistent with the divergent socio-economic assumptions embedded in the different climate change scenarios. This study addresses this gap and proposes a method for deriving scenario-dependent optimal discount rates that account for the contrasting socio-economic characteristics portrayed by the different climate change scenarios. The proposed method is based on the classical Ramsey discounting model, which is widely recognized as a sound basis for social discounting. The proposed method is applied, considering three different climate change scenarios (i.e. SSP1-SSP3), on ten selected countries that represent the different stages of economic development (four developed countries including Australia, the United States, France, and Sweden; four developing countries including China, Kuwait, Egypt, and South Africa; and two countries representing economies in transition, namely Russia and Albania). For all the considered countries, the optimal discount rate in SSP3 is lower than that in SSP2 and SSP1, respectively. These different discount rates reflect the different socio-economic characteristics defining each SSP scenario. Furthermore, an illustrative example is presented to highlight the effect of using the derived scenario-dependent discount rates on the results of cost–benefit analyses in comparison to using discount rates that are commonly adopted in literature. It can be concluded that adopting commonly recommended discount rates can lead to suboptimal climate change adaptation decisions.

There is a diversity of patterns and mobilizing factors in marriage and family in Vietnam and some East Asian societies with some similarities in sociocultural context. This article provides an overview of evolving marriage in several countries in Southeast Asia (i.e. Vietnam) and East Asia (i.e. Japan, Korea, Taiwan and China). These societies share some similarities in socio-cultural ideology (i.e. Confucianism and familialism) while undergoing different stages of modernization and economic development. This article calculates the number and rates of marriage and divorce as well as transnational marriage and divorce by using national statistics from Vietnam Gender Equality Survey 2024, the Vietnam General Statistic Office, the Vietnam Ministry of Justice, the Ministry of the Interior of Taiwan, Statistics Korea, the Ministry of Health, Labor and Welfare of Japan, Statistics of Japan, and the National Bureau of Statistics of China in the period 2001–2023 in order to show contradictory persistence and changes in marriage and their social, cultural and economic context.

At the present stage of social and economic development and in the context of sanctions policy and geopolitical tensions, the level of competition in the global higher education market is increasing many times. In order to increase Russian universities attractiveness for foreign students, it is necessary to create the most favorable conditions for studying and living. To achieve this goal, universities should apply various methods of social adaptation and cultural, educational, and educational involvement of foreign students in various processes. The results of sociological monitoring of the specifics of working with international students, conducted through an electronic questionnaire survey among specialists working with international students in 21 branches of the Financial University Under the Government of the Russian Federation (N = 128 people) located in various regions of the country, have been presented. According to the monitoring results, it has been revealed that working with international students in university environment requires the use of a system-building approach in the context of digital and cultural changes. For effective implementation of this activity, it is necessary to attract qualified specialists in the spheres of migration and visa documentation and social and psychological adaptation, as well as educational process organization. At the same time, the work should include the following aspects: forming an inclusive environment for teaching foreign citizens, implementing digital support, creating a mentoring and psychological support system, and developing practical skills.

In today’s world business-ecosystems gain status of digital superpowers that can control a considerable part of economic and social processes, get extra profit and value and influence global competitive market. At present we can observe smoothing of traditional industry borders in favor of business-integration, which offer various services to customers within the frames of seamless experience. Economic importance of ecosystem can be identified by study of its entrepreneurial model that is chosen for attracting and inclusion of new participants. It is evident that the largest economic ecosystems of the world and Russian business-ecosystems follow the mixed model combining elements of transparency and exclusiveness. Companies in Russia that use the ecosystem approach to organization of their work are not so highly developed as international leaders. However, some of them such as “Yandex’, ‘Mail.ru’, ‘1C’, ‘TBank’, and ‘Wildberries’, according to the consulting group BCG, were included in top 100 of technological companies of developing countries in 2020, which can testify to their potential on the way to reaching technological leadership. Business-ecosystem is a model of organization functioning, which consolidates different technologies, goods and services on the basis of common cloud platform under the common brand and is meant for complex and effective interaction with customers. Analysis of different approaches and concepts of home and overseas academicians can allow us to draw a conclusion that at the current stage of economic development there are no unified definitions and standards in the field of assessment of business-ecosystem work. The author of the article proposes methodology of estimating the impact of finance indicators of ecosystem work on its properties as a tool of analyzing and managing business-ecosystems in general.

BackgroundThe impact of population health on economic growth has been widely discussed, but the extent of its influence remains inconclusive. One possible reason is the heterogeneity of health's impact on economic growth across different stages of economic development. This paper, from the perspective of changes in economic structure, attempts to study the long-term and marginal effects of health on economic growth.MethodsBy deriving from the Cobb–Douglas production function, this study constructs an empirical model to analyze the impact of health on economic growth, considering economic structure. Instrumental variable methods are employed to address potential endogeneity issues. Panel data at the country level are constructed using data from the World Bank database, Penn World Tables, and the World Health Organization, covering the period from 1980 to 2015.ResultsIt reveals a positive long-term relationship between health and economic growth, particularly in post-demographic transition nations. The marginal impact of health on economic growth varies depending on the economic structure, the economic benefit of health promotion is notably pronounced in countries with a larger share of the primary sector. As countries reach higher levels of economic development, the marginal effect of health tends to decrease. Furthermore, health changes affect labor force distribution across industries, with varying impacts.ConclusionsThe findings suggest that developing nations, having undergone demographic transition, experience greater returns on health investments compared to developed counterparts. This research offers novel insights into the diverse effects of health on economic growth, emphasizing the importance of economic structure in understanding these dynamics.

Achieving carbon peak before 2030 and carbon neutrality in 2060 is the solemn commitment of the Chinese government to the international community. It is important to scientifically identify the key influencing factors and accurately predict carbon peak value and time for achieving the dual carbon targets in China. On the basis of the economic and energy consumption data from 1980 to 2022， a STIRPAT extended multivariate-nonlinear model was built， which was fitted by a ridge regression to examine the relationships between carbon emissions of energy consumption and seven influencing factors， including population， GDP per capita， energy intensity， secondary industry proportion， fossil energy proportion， electrification rate， and urbanization rate. Based on the proposed STIRPAT extended model， predictions of carbon emissions of energy consumption were made for the period from 2023-2035 under three different scenarios. The results showed that： ① There were five factors that increased the carbon emissions including population， urbanization rate， secondary industry proportion， GDP per capita， and electrification rate. The degree of influence decreased in turn. Fossil energy proportion and energy intensity were the two factors that restrained the carbon emissions. The influencing degree of fossil energy proportion was the biggest， and that of energy intensity was the smallest. ② During different stages of economic development， the roles and contributions of the seven factors changed significantly. In particular， the effects of energy intensity， secondary industry proportion， and fossil energy proportion resulted in the turning changes， which reflected the periodical characteristics of carbon emissions in different stages. ③ Carbon emissions of energy consumption will achieve a peak during 2028-2032 in China. The peak was 11.66-12.75 billion tons. Under the baseline scenario， the peak was 12.04 billion tons， which will be fulfilled in 2030. The peak of the low-carbon scenario was 11.66 billion tons in 2028， which was 3.16% lower than that of the baseline scenario. The peak of the high-carbon scenario was 12.75 billion tons in 2032， which was 5.90% higher than that of the baseline scenario. Based on the research results， reasonable suggestions such as accelerating renewable energy development， increasing the electrification rate， optimizing the economic structure， and improving energy efficiency are put forward to ensure that China will achieve its carbon peak target before 2030.

This paper investigates approaches to mitigating staff shortage in maintenance of real estate properties of the urban economy. The role of the institute for vocational guidance of citizens is considered. Reasons for staff shortage on the labor market are discussed, including in the fields of the severely afflicted professions, including qualified workers, middle-ranking workers, and high university degree specialists corresponding to the present stage of economic development. The statement about the prestige of professions in the sphere of housing and communal services is proved to be unreasonable. The multidisciplinary nature of such an activity as derived from the use of buildings is discussed. The methods of vocational guidance to children, pupils, students, and adults as one of the priority areas of state policy are characterized. Best practices of vocational guidance, i.e., federal and regional projects and events contributing to the elimination of current staff shortage of workers in maintenance of real estate properties of the urban economy, are presented. In this paper, the authors set tasks for the professional community concerning prospects for the upcoming development of vocational guidance taking into account the technological, global, and social challenges.

Global warming is very serious because for the first time the average annual temperature has crossed the threshold of 1.5 ° C. One of the causes of the increase in temperature is the presence of greenhouse gases (GHG) and carbon dioxide (CO2) is one of these gases. ASEAN is a regional organization whose member countries are mostly middle income countries and also has high economic growth because they are in the stage of economic development where according to the environmental kuznet curve (EKC) hypothesis this will increase environmental degradation. In addition, ASEAN has a high level of CO2 emissions. This study aims to analyze the factors that influence carbon dioxide emissions in ASEAN from 2014 to 2023. The variables used are CO2 emissions as the dependent variable, then GDP, FDI, Population, and Industrial Rate as the dependent variables, then analyzed using the panel data regression method. The results of the study showed that GDP and Population have a significant positive effect on CO2 emissions while FDI and Industrial Rate produce negative coefficients but do not have a significant effect on CO2 emissions.

In this paper, we examine the role of entrepreneurial ecosystems in driving economic growth across 107 economies from 2011 to 2023. Our objective is to develop and validate a composite index that captures the efficiency of national entrepreneurship systems and assesses its impact on economic growth. To achieve this, we construct six entrepreneurial sub-indexes and a composite Global Entrepreneurship Monitor Index (GEMI) using a two-step approach: first, we apply an output-oriented slacks-based measure (SBM) data envelopment analysis (DEA); second, we use ordinary least squares (OLS) and fixed effects panel regressions to estimate the relationship between GEMI and GDP growth. We also conduct multiple robustness checks using GDP per capita and alternative model specifications. We find that GEMI has a robust positive impact on economic growth, consistent with the Entrepreneurship Ecosystem Theory (EET), which emphasizes the critical role of a well-rounded entrepreneurial environment. Our additional analyses reveal key patterns across income levels, regions, and stages of economic development, indicating that high-income countries benefit the most, middle-income countries experience moderate gains, and low-income countries face significant barriers. We observe that GEMI plays a more transformative role in developed economies, where synergies between financial systems, governance, and open markets amplify its effects compared to emerging economies. Regional variations reveal stronger gains in Europe and Latin America, while Sub-Saharan Africa and MENA regions remain constrained by weak infrastructure and governance. Results remain consistent across robustness checks using GDP per capita and alternative estimation techniques. Our findings offer practical implications for policymakers, international development institutions, and researchers aiming to foster entrepreneurship-led growth. We emphasize the importance of strengthening regulatory frameworks, expanding access to finance, and investing in education and infrastructure to unlock the transformative potential of entrepreneurship.