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The United Nations' Human Development Index remains a widely used and accepted measure of human development. Although it has been revised over the years to address various critiques, a remaining concern is the way the three dimensions are aggregated into the single index. A deterioration in one dimension can be compensated for by an improvement in another. Since compensability is inextricably linked with trade-offs and intensity of preferences, a non-compensatory (i.e., Condorcet) approach to aggregation is employed in this paper. Although non-compensatory approaches have been employed previously, this paper adds to the literature by undertaking an application of the Condorcet approach to the entire HDI. This approach, which does not use intensities of preferences, ensures that the degree of compensability connected with the aggregation model is at the minimum possible level. To achieve this, country level rankings are then compared to those for the 2020 Human Development Index which aggregates dimensions using a geometric mean. The findings demonstrated substantial changes in rank-order between the HDI and Condorcet approach. This outcome provides empirical evidence which demonstrates that the non-compensatory Condorcet approach can mitigate issues of compensation present within the geometric aggregation technique currently employed by the HDI. These findings have potential implications in aiding the identification and employment of potential policy priorities—specifically, the notion that policy should emphasise the development of a country as opposed to economic growth alone. [ABSTRACT FROM AUTHOR]

Against the background of climate change and scarce non-renewable resources, transforming the fossil-based toward a bio-based economy is considered crucial for sustainable development. Numerous countries have released governmental strategies outlining their bioeconomy visions. This study examines the bioeconomy visions presented in 78 policy documents from 50 countries worldwide, building on earlier vision typologies. Through qualitative content analysis, 227 distinct policy goals were identified and analyzed. Descriptive statistics were used to determine the salience of specific goals, overarching goal categories, and distinct bioeconomy visions: bioresource, biotechnology, and bioecology visions. The results reveal that goals and visions prioritize economic growth, while environmental considerations are less salient. The bioresource vision emerges as the globally dominant perspective, while the bioecology and biotechnology visions have lower salience. These findings deepen our comprehension of current bioeconomy policies and emphasize the need for critical research on bioeconomy visions and their implications for public policy. [ABSTRACT FROM AUTHOR]

Numerous studies conducted by various scholars have aimed to ascertain the impact of monetary policy on economic growth. However, these empirical investigations have not reached a unanimous consensus. Therefore, this study analyzes the effect of monetary policy. To address this objective, this study employed ARDL and error correction model (ECM) based on annual data from 1993 to 2022. Granger causality test was also employed to check the direction of causal effects of one variable on the other variable. All required pre and post estimation tests were performed and verified that the model was statistically viable. The study revealed that, in the short run, deposit interest rate, reserve required amount, and open market operation have positive and statistically significant effects on real GDP growth of Ethiopia; however, money supply has negative and statistically significant effects on real GDP growth of Ethiopia. In the long run, money supply has positive and statistically significant effects on real GDP growth of Ethiopia; however, deposit interest rate and reserve required have negative and statistically significant effects on real GDP growth of Ethiopia. To sum up, in the short run, contractionary monetary policy was promising, and in the long run, expansionary monetary policy was favorable for economic growth. The Granger causality test result shows that there is bidirectional causality between monetary policy and economic growth; except there was a unidirectional relationship between deposit interest rate and economic growth. Ultimately, this research suggests the following policy recommendation: for short-term economic enhancement, it is advisable for the government to opt for a contractionary monetary policy rather than an expansionary one. On the other hand, for long-term economic improvement, an expansionary monetary policy is more favorable than a contractionary one. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration. [ABSTRACT FROM AUTHOR]

This study analyses the impact of GDP per capita, domestic credit, savings, and population on the environment in Pakistan from 1995 to 2019. The country has consistently been ranked eighth, fifth, and eight as an environmentally vulnerable nation from 1998 to 2017, 1999 to 2018, and 2000 to 2019, respectively. Therefore, the study explores the role of environmental awareness as a potential strategy for making peace with nature. Findings of the ARDL bounds testing approach confirm the long-run cointegration among variables of concern. In further assessment, the study determines that increased per capita income is detrimental to environmental quality in the long run. However, in the short run, it shows a favourable impact. On the other hand, domestic credit worsens the environment in the long and short runs. However, savings are positively insignificant in this regard. Furthermore, the total population significantly harms the environment in the long and short run. Fortunately, environmental awareness has emerged as a key solution to environmental degradation in Pakistan. Findings show that an increase in the dissemination of environmental awareness through the Internet, mobile, and landline phones, as well as by increasing education expenditures, mitigates the populations' detrimental impact on the environment and improves environmental quality in the long run. [ABSTRACT FROM AUTHOR]

Significant demand for ecological services and diminishing environmental issues pose severe threats to the existence of humanity. Some scholars believe that the rapid development of financial sectors may add to this problem. Therefore, this study evaluates the impact of disaggregated financial development on the ecological footprint of the Next-11 countries using the panel data from 1995 to 2019. For in-depth empirical analysis, financial development is divided into three categories: banking sector development, insurance market development, and stock market development. Each class comprises four indicators, and the composite index is constructed using principal component analysis. Results of the unit tests indicate that variables are stationary at mix orders some variables are stationary at the level and others are stationary at the 1st difference. By utilizing DCCE and AMG estimations model. The study has confirmed the existence of the Environmental Kuznets Curve (EKC) hypothesis in sampled countries by showing the inverted U-shaped relation between economic growth and ecological footprints. The results also revealed that both stock market development and banking sector development decrease ecological footprints and could help protect the quality of the environment. Furthermore, the findings show that municipal is inseparably linked to environmental adversity in the Next 11 countries. Therefore, to safeguard the ecological footprint in the Next-11 countries, sustainable practices with green financial development accompanied by green urbanization are among the appropriate solutions. [ABSTRACT FROM AUTHOR]

As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei region (BTH) has huge electricity and water consumption, while the local power generation capacity and water resources may not be sustainable long term according to the current power generation ratio. We introduced up-to-date strategic policies in China, carbon peaking and carbon neutrality (dual carbon goals), to assess their impact on environmental protection and economic development. Thus, we constructed a dynamic multi-regional computable general equilibrium model to simulate these changes in BTH. We designed four carbon reduction scenarios to explore the impact of policies including carbon taxes, investment, and renewable energy subsidies individually or combined. The findings reveal that implementing these policies together can increase the proportion of renewable energy in power generation to 17.2% (Beijing), 9.4% (Tianjin), and 33.2% (Hebei) by 2060. Under various policy scenarios, the Tax Scenario shows the largest water withdrawal savings, while the Investment Scenario shows the largest GDP growth by 2060. The combined implementation of these policies may minimize the negative impact on the economy while developing an environmentally friendly region. The results of the Combination Scenario are closest to carbon neutrality, narrowing the gap to 10.71%, 9.98%, and 9.85%, respectively. Conservation (water and electricity) and carbon reduction can provide significant support for carbon neutrality and sustainable development strategies. This study contributes to the evaluation of mitigation policies in BTH and provides a concrete policy option to achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

This paper investigates whether carbon dioxide (CO2) intensity of gross domestic product (GDP) matters for environmental deregulations in Southern European countries over the period of 1990–2018 while controlling economic growth, globalization, and energy consumption. The present study uses the second generation panel based techniques, namely cross-sectional dependency test, cross-sectional unit-root test, Westerlund cointegration test, augmented mean group and common correlated effects mean group estimators, and Dumitrescu–Hurlin causality test to measure the effect of CO2 intensity of GDP, economic growth, globalization, and energy consumption on environmental degradation. The empirical finding of the present study reveals that the CO2 intensity of GDP is an important factor in determining environmental degradation in South European countries, as the outcomes show that a 1% boost in CO2 intensity of GDP is causing a 1.7728% increase in CO2 emissions. Moreover, a 1% increase in economic growth caused a 0.2568% boost in CO2 emissions. The result is crucial for policy decision-making and can perhaps be applied to take decisive policy actions to mitigate environmental issues. [ABSTRACT FROM AUTHOR]

We study the effect of euro adoption on various property crimes for a group of Eurozone countries with data from 1993 to 2019. We hypothesize euro adoption has a positive association with home burglaries and robberies as the euro is relatively more valuable and mobile than pre-euro currencies. We offer a simple theoretical model to motivate the hypothesis. A dynamic panel data model is estimated by generalized method of moments (GMM) to account for endogeneity, measurement error, heteroskedasticity, and serial correlation. Our results indicate some evidence of a positive relationship between euro adoption and property crimes. Other countries considering euro adoption may find the results of our study informative. [ABSTRACT FROM AUTHOR]

This paper puts forth a new pathway to sustainable policy to upscale the transformative power of local complementary currencies. It first reviews the mechanisms by which complementary currencies re-embed monetary circulation within sustainability and biomimetic resilience criteria. It then puts forth a prototype policy pathway whereby private banks swap SDG impact certificates of their complementary currency loans against new reserve assets held at the Central Bank. It finally provides analytical insight on this prototype policy with a a new PK-SFC model comprising 106 accounting and behavioral equations. Simulations show that the prototype policy generates short-lived economic expansion, increases banking stability, and induces structural change through increased systemic capacity for evolution, resilience, and fitness for evolution. We finally discuss the practical implications of our results for sustainability policies. [ABSTRACT FROM AUTHOR]

With the increase in economic growth, the world is facing serious challenges concerning environmental sustainability. Hence, the green economic growth is imperative for sustainable and inclusive development. The objective of this study is to contribute to the existing literature about the factors that influence green economic growth. The study investigates the role of green technology, green energy, foreign direct investment, and globalization on green economic growth in G7 countries. The data of the study is collected from WDI, KOF Swiss Economic Institute, and OECD database and the data period ranges from 1995 to 2020. The existence of cointegration between the variables of the study was tested by Westerlund's (Oxford Bull Econ Stat 69(6):709–748) cointegration test. Due to the presence of cross-sectional dependency, the study employed the cross-sectional autoregressive distributed lag (CS-ARDL) method to estimate the coefficients in the long and short run. The study also used a common correlated effect—mean group (CCEMG) estimator for robustness check. The findings of the study reveal that green energy and FDI positively contribute to green economic growth in the long and short run. The green technology also contributes positively to enhance green economic growth but only in long run. To accelerate green economic growth, G7 countries should incorporate policies promoting green energy and technology, while acquiring more foreign investments to ensure a sustainable development. [ABSTRACT FROM AUTHOR]

Under the influence of market rules, state intervention in development process is obviously necessary, especially in the context of emerging countries with an incomplete and non-mordern market economy toward the global race of sustainability. Applying 2590 enterprises covering 63 provinces and cities in the General Statistics Office, this study aims to evaluate the influence of state on the technical efficiency of enterprises. A fractional regression analysis model is employed purposefully since the technical efficiency of the dependent variable is an estimated randomly variable. The research findings unequivocally indicate a substantial influence of the state on the technical efficiency of livestock product processing companies. Moreover, when studying each specific aspect in isolation to gauge the role of the state, a discernible negative impact is evident on the technical efficiency of these enterprises. Consequently, this study implies that for tangilbe improvements in the technical efficiency of enterprises, the state should adopt a comprehensive approach, simultaneously implementing all aspects that demonstrate its role in the sector. By adopting such a holistic strategy, the state can create a more conducive environment toward development sustainability for improving the technical efficiency of livestock product processing enterprises. [ABSTRACT FROM AUTHOR]

The popularisation of higher education supports UNESCO's aim of developing inclusive and equitable quality education to achieve the fourth Sustainable Development Goal. However, the effect of popularising higher education on economic growth and poverty alleviation remains unexplored. Therefore, this study investigated the effects of higher education and adult education within populations (popularisation of higher education) on economic growth (gross domestic product; GDP) and the poverty line using panel data from 38 countries. OLS and quantile regression were performed using data for the period 1995–2021 extracted from the OECD and World Bank databases. The results showed that the population segments with higher education had a significantly positive impact on GDP growth. Moreover, an increased proportion of the population with higher education, of working age, was found to be a contributing factor to GDP growth. Popularising higher education also played a positive role during the initial stage of social and economic development. This study also highlighted that popularising higher education play a key role to influence a country's educational development and scientific and technological innovation drives the deepening of a country's economy. It suggested that both national and local governments worldwide should pay much attention to the popularisation degree of higher education to greatly improve the innovative ability of talents and scientific and technological innovation in higher education for both the economic growth and poverty alleviation. [ABSTRACT FROM AUTHOR]

This study explores the interplay between environmental quality and healthcare spending in five North African countries from 1990 to 2019, considering key socioeconomic variables as determinants. We observe a growing trend in healthcare expenditure, signaling a dedication to improving healthcare systems. Nevertheless, sporadic declines, particularly post-2010 in Libya and Tunisia, highlight the vulnerability of healthcare infrastructure to external shocks, underlining the synergy between healthcare, political stability, and economic development. Simultaneously, the study underscores the potential threat of CO2 emissions to healthcare costs, emphasizing the intrinsic connection between environmental quality and healthcare expenses. Income significantly propels healthcare spending, mirroring the region's pursuit of enhanced living standards and healthcare access. Notably, investments in healthcare infrastructure play a substantial role. Furthermore, the adverse impact of trade openness on healthcare spending stresses the importance of equitable resource allocation and effective healthcare policy implementation. The positive influence of population density underscores the need for tailored healthcare strategies addressing the region's diverse healthcare requirements. Additionally, the U-shaped relationship between healthcare expenditure and CO2 emissions suggests that the studied countries have low pollution levels and have not incurred significant healthcare costs from emissions. However, as they grow economically, environmental conservation becomes crucial to avert harm and resource depletion. While acknowledging limitations like data quality and the need for a more extended time series analysis, a comprehensive approach to healthcare systems, and a holistic view of environmental factors, this study significantly contributes to comprehending the dynamics of healthcare spending, environmental quality, and economic development in North Africa. [ABSTRACT FROM AUTHOR]

The university–industry collaboration is an essential engine of the regional innovation system and can significantly drive regional economic growth. The realization of intellectual collaboration, especially for firms absorbing academic knowledge, is heavily dependent on the transmission of tacit knowledge through face-to-face contact. Though economic geographers have long emphasized the importance of face-to-face contact, its effect is rarely measured directly. This paper contributes to this end by utilizing the mobile signaling data and tries to estimate and explain the marginal effect of face-to-face contact on the co-patenting behavior between firms and universities in Beijing. We conclude that face-to-face contact indeed increases the productivity of university–industry collaboration, specifically in the idea-formation period. In addition, we detect the ambiguity of geographical proximity in explaining university–industry collaboration. For policy consideration, we contend that innovation policy should pay enough attention to reinforcing the university–industry nexus. The removal of interaction barriers between firms and universities is crucial, and it can be achieved either by forming direct contact channels or leveraging the spatial spillover effect of personal interaction. [ABSTRACT FROM AUTHOR]

We consider the robust responses to environmental disasters in stochastic growth economies. The representative agent has imprecise knowledge about environmental disasters and exhibits ambiguity aversion to the jump arrival intensity. In the equilibrium, the optimal abatement expenditure is increasing in the level of ambiguity aversion, which overturns the effect of model uncertainty on capital investment. Because of mitigating future damages, the incremental abatement may enhance long-run economic growth. In addition, welfare gains from abatement technology and the social cost of carbon become more substantial under ambiguous circumstances. Finally, we extend the baseline model by considering emission stock and find the main results still hold in this extension. [ABSTRACT FROM AUTHOR]

Much research demonstrates the positive effects of financial inclusion and digital finance on expansion. Supply chains that can be relied upon are essential to national productivity and economic development. This study uses panel data from 2007 to 2022 covering 27 provinces in China to study the results of widespread access to digital financial services and supply chain management on regional economic growth using the instrumental variable approach (fixed effect model). In contrast to earlier research, this study employs an alternative measure of access to digital financial services utilization and digitalization. The data demonstrates that digital financial inclusion and supply chain management have a major impact on the development of the provincial economies in China. Based on the results of this research, we suggest increasing digital financial inclusion and bolstering human capital development to stimulate economic expansion. This essay makes a theoretical advancement in studying digital technology's widespread adoption of financial services by providing a comprehensive critical review and a fresh angle on the nuts and bolts of digital money and universal banking. Boosting institutional quality and governance are two more paths that authorities can take to stimulate economic expansion in the China area, and the results show how important these measures are for achieving this goal. [ABSTRACT FROM AUTHOR]

This paper investigates the contribution of industrial robots to labor productivity growth and cross-country economic convergence in a sample of 19 developed and 16 emerging countries over the period 1999 to 2019. To answer our research questions, we extend the non-parametric production frontier framework by considering industrial robots as a separate production factor. We find a positive contribution of robotization to labor productivity growth for all countries in our sample. In the period after the financial crisis (2009 to 2019) the contribution of robot capital deepening to productivity growth gained in importance. Over the period 1999 to 2019 we find some evidence of i) unconditional β-convergence (countries with lower initial productivity levels grow faster), ii) a reduction in the dispersion of productivity levels across economies (σ-convergence) and iii) a depolarization (shift from bimodal to unimodal distribution) of the labor productivity distribution in our sample. Accumulation of 'traditional' physical capital is the main driver of β-convergence. Robot capital deepening significantly contributed to economic convergence and the depolarization of the labor productivity distribution, but its effect on the entire shift of the labor productivity distribution is modest and dominated by other drivers of productivity growth such as 'traditional' physical capital deepening and technological change. [ABSTRACT FROM AUTHOR]

China has changed its focus from traditional high-speed economic growth to high-quality economic development (HQED) and the implementation of environmentally friendly practices. This transition can have parallel or unparallel impacts on energy insecurity (EIS). In this regards, HQED, inter Alia, is crucial in mitigating EIS and combating the energy crisis. Our study explores the impact of economic growth (EG) and HQED on EIS using the provincial panel data of China for the period 2011–2017. From the perspective of comparative analysis, the results reveal that HQED reduces EIS while EG increases it. The robustness checks indicate that industrial structure (IS) has a negative impact on EIS, whereas industrial structure upgrading (ISU) and green innovation (GI) have a positive influence. This implies that IS contributes to an increase in EIS, whereas ISU and GI result in a decrease in EIS. In addition, the analysis reveals that digital financial inclusion (DFI) exhibits a significant positive relation with EIS, albeit occasionally a negative but insignificant link. The policy implication is that the government should stimulate policies to promote HQED which reduces the EIS. [ABSTRACT FROM AUTHOR]

Air pollution is a danger to economies throughout the European Union. Industry, population expansion, a building boom owing to housing and infrastructure development, increasing vehicle traffic, crowded streets, a lack of availability of clean fuel, and ineffective control programs are the primary causes. Toxic air is a double-edged sword for a country's health since it affects just a tiny fraction of Europe's population. The financial burden and healthcare expenses for people rise when health expenditures rise. The present research looks at how dangerous air levels, healthcare costs, and the expansion of the European Union's economy are all connected. The findings are based on data collected over 29 years and account for the abovementioned variables. The results of the unit root test have the significant probability values of all variables: health expenditures (HE), gross domestic product (GDP), nitrous oxides (NOX), and carbon dioxides (CO2) emissions at both level and first difference. We used the Johansen, Kao, and Pedroni cointegration tests to test the null hypothesis of no cointegration to see that sample variables had a long-term association. The PMG-ARDL test was used to get these findings. The results confirmed the significant probability values of dependent variables in long- and short-run results that GDP has a positive and significant effect on health expenditure, while NOX and CO2 emissions have a negative and significant impact on (HE), in the European Union. To verify the results, we applied the robustness test, fully modified OLS (FMOLD), and dynamic OLS (DOLS); the robustness test results validated the PMG-ARDL test results. Environmental pollution (CO2, NOX) has a significant and negative impact on healthcare expenditures and a significant effect on GDP (HE) in the EU region. The findings of this research have implications for a wide range of parties, including those who would examine the link between factors in a study meant to improve air quality, distribute health resources, or develop strategies for economic development. [ABSTRACT FROM AUTHOR]

Given the increasing investment by Belt and Road Initiative (BRI) participants in the renewable energy industry, it is imperative to ascertain how much this investment contributes to economic growth. The objective of this study is to ascertain the extent to which renewable energy contributes to economic growth within the Belt and Road Initiative compared to non-renewable energy sources. Prior studies have yet to incorporate oil prices as a variable in the production function, among other output aspects. This study integrates the inclusion of real oil prices as a variable within the production function alongside capital, labor, renewable energy consumption, and non-renewable energy consumption. A cohort including 49 Belt and Road Initiative participants was formed, encompassing data from 1990 to 2019. The data has undergone an initial examination to assess cross-sectional dependence, slope heterogeneity, and structural break(s), and are verified. Hence, third-generation panel data analysis has been utilized. The continuously updated fully modified estimator and continuously updated biased corrected estimator provide evidence supporting the notion that renewable energy plays a substantial role in fostering economic growth within nations participating in the Belt and Road Initiative. Furthermore, this contribution is found to be more pronounced when compared to the impact of non-renewable energy sources. The study's findings inform policy recommendations at both the BRI and national level. [ABSTRACT FROM AUTHOR]

In recent years, there has been a persistent intensification of the global greenhouse effect. Balancing carbon emission reduction with economic growth poses an unprecedented global challenge. To better comprehend the relationship between economic growth and carbon emissions, this study first utilized the Tapio decoupling index to compare the decoupling relationship (the USA, Japan, and Germany) and three developing countries (China, India, and Russia) from 2000–2020. Additionally, the logarithmic mean Divisia index (LMDI) method was employed to investigate the factors influencing changes in carbon emissions. Our findings indicate that (1) the USA and Germany basically achieved strong decoupling; China, India, and Russia mainly showed weak decoupling; and Japan showed recessive decoupling. (2) Economic growth predominantly contributed to increased carbon emissions, with a lesser impact from population growth. A significant reduction in energy intensity restrained carbon emissions growth, as did energy structure replacement in most countries, excluding Japan. Based on this, a decoupling effort index was formulated. It has shown that the decoupling efforts made by developing countries are weaker than those of developed countries, primarily attributed to a lesser degree of decoupling between energy intensity and structure. This paper offers valuable insights for developing countries undergoing a low-carbon economic transformation. They should counterbalance carbon emission escalation resulting from economic growth through technological and energy structure improvements. [ABSTRACT FROM AUTHOR]

In the current era, the symbiotic relationship between artificial intelligence, religious freedom, and economic growth remains a topic of paramount importance. This study embarks on an in-depth exploration of these dynamics across 26 countries from 2000 to 2021. Utilizing the panel vector auto-regression model, the findings underscore a significant positive correlation between artificial intelligence, religious freedom, and economic growth. The forecast-error variance decomposition highlights the growing importance of both variables. It projects their increasing relevance in future economic landscapes. Furthermore, the study reaffirms the indomitable role of traditional growth drivers, specifically labor and capital inputs. The Toda-Yamamoto Granger causality analysis bolsters the validity and reliability of these findings. In summary, this research strengthens established economic paradigms and reveals new interactions, offering important implications for academics, policymakers, and stakeholders. [ABSTRACT FROM AUTHOR]

Innovation is a key driver of long-term economic growth and has significantly improved living standards. Corporate innovation efforts are at the forefront of this process. We propose a two-period career concern model to better understand the factors that influence a corporation's decision to undertake risky innovation. In this model, a corporation's manager is influenced by the company's corporate governance structure and the level of competition in the product market. Our research shows that strong corporate governance positively impacts a manager's decision to innovate due to career concerns. However, we also found that firms in industries with low competition benefit more from good governance than those in highly competitive industries. This conclusion is supported by our analysis of a panel data set from the 1990s, which contains information on time-varying patent citations in the US. [ABSTRACT FROM AUTHOR]

Economic agglomeration has played a key function in China's economic transformation. Meanwhile, structural adjustment and external pressure to reduce carbon emission necessitate a deeper investigation into its relationship with carbon productivity. This paper measures economic agglomeration and carbon productivity of 281 cities in China in 2003–2017. With the purpose of exploring the spatial effect of economic agglomeration on carbon productivity, a spatial Durbin model is constructed. In addition, the mediation effect model is also adopted for examining the transmission mechanism of economic scale and technological progress on economic agglomeration as well as carbon productivity. A heterogeneity test is also carried out to uncover the varying effects of economic agglomeration on carbon productivity. The empirical results suggest that economic agglomeration raises carbon productivity not only in the local cities but also in the neighbouring ones. The impact of economic agglomeration on carbon productivity becomes more potent as the level of economic agglomeration increases. For cities with low level of economic agglomeration, the effect is mainly achieved through the expansion of economic scale, but for cities with high level of economic agglomeration, the effect is mainly achieved through technological progress. Therefore, we suggest encouraging carbon productivity improvement through technology effect in cities with high economic agglomeration level, while enhancing carbon productivity through scale effect in cities with low economic agglomeration level. [ABSTRACT FROM AUTHOR]

The Dutch disease literature reveals several gaps between empirical evidence and theoretical predictions. To bridge such gaps, I develop a model that accounts for uneven spillovers of technological progress from the resource sector to other domestic sectors. I then employ a dynamic panel approach to align the theory with the data. I find that the real exchange rate appreciation resulting from a resource boom (i.e., the spending channel) is more pronounced in resource-poor countries than in resource-rich countries. Additionally, the resource movement channel exhibits differences between resource-rich and resource-poor countries. In resource-rich countries, a resource boom reduces the growth rate in the manufacturing sector more than in the service sector, leading to a decrease in relative sectoral output and a slowdown in economic growth. On the other hand, in resource-poor countries, a resource boom accelerates the growth of the manufacturing sector and decelerates the growth of the service sector, resulting in an increase in relative sectoral output and economic growth. [ABSTRACT FROM AUTHOR]

In recent years, environmental concerns have emerged as significant obstacles to economic advancement, leading to a critical examination of the complex relationship between environmental sustainability and economic expansion. With the economy expanding swiftly and environmental hazards intensifying, immediate action must be taken to address these problems. This necessitates innovative policies and practices that foster sustainable economic growth while minimizing environmental impact. To solve these issues, this study proposed an extensive analytical framework employing machine learning techniques, particularly artificial neural networks (ANNs), to investigate the Environmental Kuznets Curve (EKC) hypothesis. According to the EKC hypothesis, environmental degradation worsens before economic growth occurs. This study examines GDP per capita and key environmental indicators to measure economic development, using data from Anhui Province, China, from 2012 to 2019. The analysis provides empirical support for the theory and establishes a modeling framework that seamlessly integrates ML methodologies with EKC analysis, systematically examining and assessing the EKC's reliability for Anhui Province. The intricate interplay between Anhui Province's environment and economy, utilizing industrial waste gas, wastewater, and solid waste as critical indicators, evaluates environmental quality. At the same time, per capita GDP is the economic growth parameter. The findings indicate that the EKC does not adhere to an unchanging law but instead displays variations in distribution characteristics. The experimental results of the proposed ANN model demonstrate an impressive accuracy rate of 87%, outperforming five alternative models, including RF, KNN, DT, and LR. This superior model performance underscores the effectiveness of the ANN-based approach in capturing the intricate dynamics linking economic development and environmental pollution. [ABSTRACT FROM AUTHOR]

The outcome of economic growth is visualised as the well-being of citizens or human well-being (HWB). However, it has been a great challenge to measure HWB. Though there are known reasons for considering GDP and its growth as a measure of overall development and progress of nations, yet mostly it is being used as a gospel indicator to compare nations and design appropriate policies. This paper is an effort to develop a comprehensive adjusted GDP to measure HWB through secondary data for thirty years (1990–91 to 2019–20) in India. We make thirty-five adjustments to net national income (NNI) to compute the adjusted national income (ANI) index based on the system analysis approach. The empirical findings show that the gap between NNI and ANI has been growing over time, and the ANI index shows an increasing trend. Through the analysis it is suggested that economic growth should be focused only if it improves HWB (full or partial). The paper attempts to make intervention into policy shift for improving HWB vis-à-vis happiness of people. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings. [ABSTRACT FROM AUTHOR]

This research proposes an analysis of the spread of COVID-19 during the three waves at the provincial level in Italy. Specifically, this study examines the distribution of COVID-19 cases across Italian provinces to determine the potential existence of territorial clusters, which are measured by spatial autocorrelation among the provinces. Furthermore, this study examines whether a convergence process occurred in the contagion of the virus among the provinces, thereby estimating its relative speed. To this end, the β-convergence model—commonly applied in economic growth models—is employed in this study to consider the demographic and environmental variables present in each province. The initial level and growth of infections observed in a certain province are then related to the level of infections and their growth rate in all other Italian provinces. This econometric estimation is conducted for the first, second, and third waves of the pandemic between March 2020 and June 2021, using covariates such as population density, aging index, average temperature, pollution levels, and the duration of the waves. The hypothesis of COVID-19 convergence, verified in all three waves, recorded a rather different average speed, with an influence exerted by demographic and environmental variables. Additionally, the econometric analysis is integrated, considering spatial effects using the Spatial Autoregressive (SAR) and Spatial Error (SEM) models, after verifying the existence of autocorrelation of the residuals for the first and third waves. The results obtained in this second estimation only partially confirm the influence of demographic and environmental variables for the first and third waves. In the first wave—in addition to identifying any spillover effects among provinces—the effects are decomposed into direct, indirect, and total effects. [ABSTRACT FROM AUTHOR]

The effect of a difference in regions and economic levels, coupled with variations in natural resource rents, total import and export, and economic growth, has been ignored in studies that investigated the link between natural resource rents, trade openness, and economic growth across African countries. To overcome these deficiencies, this study aims to examine the impact of total natural resource rents and trade openness in terms of total import and export on economic growth across regions and the economic levels of African countries. Recent econometric models (CS-DL), variance decomposition, and impulse response were employed for the panel of 48 African countries from 1980 to 2018. Findings revealed total natural resource rent has a long-term significant negative effect on economic growth across regions and economic levels. Trade openness in terms of total export has a significant positive effect on growth at the panel of 48 countries, while the effect of both total import and export is mixed across regions and economic levels. A bi-directional causations relationship between natural resource rents, trade openness, and growth in the panel of involved countries, some subpanels. It was noted that trade openness counted higher variations of GDP than resource rents within 10 years. Empirical results of this study awaken up regional and government policymakers to reflect on negative effects and neutral links noticed between variables across economic levels and regions for reasonably sustainable developments across Africa. [ABSTRACT FROM AUTHOR]

Using a panel of 17 Latin American countries for the period 2002–18, we study the impact of economic variables on government approval. Our empirical analysis shows that the one economic variable that appears consistently in all estimates is economic growth. More specifically, we show that for each point of additional growth, the approval rating increases between 1.1 and 1.9 percentage points. Other variables, such as inflation, government spending, and the composition of spending, are significant in only some of the specifications used, while growth is remarkably robust in all of them. Among non-economic variables, the lack of solid institutions also appears consistently as significant as well as the lagged value of government approval ratings. These results suggest that a program focused on growth has a positive influence on the popularity of the government. This conclusion is particularly relevant in a region where populism has been remarkably persistent over time and where the norm has been to run large budget deficits to gain popular support, with consequences on inflation and the external accounts. [ABSTRACT FROM AUTHOR]

Having previously analyzed the relationship between tourism and economic growth from distinct perspectives, this paper attempts to fill the void existing in scientific research on the relationship between tourism and economic development, by analyzing the relationship between these variables using a sample of 123 countries between 1995 and 2019. The Dumistrescu and Hurlin adaptation of the Granger causality test was used. This study takes a critical look at causal analysis with heterogeneous panels, given the substantial differences found between the results of the causal analysis with the complete panel as compared to the analysis of homogeneous country groups, in terms of their dynamics of tourism specialization and economic development. On the one hand, a one-way causal relationship exists from tourism to development in countries having low levels of tourism specialization and development. On the other hand, a one-way causal relationship exists by which development contributes to tourism in countries with high levels of development and tourism specialization. [ABSTRACT FROM AUTHOR]

This study examines the dynamic relationship between the share of nuclear energy, growth in CO2 emissions, and GDP growth for the wealthiest countries of the two continents, Europe and Asia, from 1965 to 2021. The results from the SVAR model show a significant positive relationship between GDP growth and the growth of CO2 emissions in all countries. However, the values of the coefficients vary in the case of different countries of both continents. Further, it has been observed that the relationship between the growth of nuclear energy and the growth in CO2 emissions is more complex and varies from country to country. The results indicate that there is a strong negative relationship between nuclear energy and CO2 emissions in France, Russia, the United Kingdom, and India. At the same time, there is no significant relationship between Germany, Italy, and China. Finally, the result shows that there is an insignificant relationship between the growth in the share of nuclear energy and the GDP growth rate. From the policy perspective, this study suggests that alternative energy sources like nuclear energy can be leveraged to obtain a clean environment. [ABSTRACT FROM AUTHOR]

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China. [ABSTRACT FROM AUTHOR]

Understanding the impact mechanisms of territorial space composition and landscape pattern changes on carbon storage is critical to balance the development and utilization of territorial space and the conservation of the ecosystem. Thus, taking the Fujian Delta urban agglomeration (FDUA) of China as an example, this paper analyzed the impact of the transference in territorial space composition and the change in the coupling coordination degree (CCD) of landscape patterns on carbon storage based on the urban–rural gradient and grid scales. Results illustrated that the areas of agricultural, green, and blue spaces continued to decline, while the intensity of economic space expansion increased from 20.86 to 42.45% during 2000–2020. The grids with CCD change of landscape patterns declined mainly (accounting for 64.31%) in the first decade and rose mainly (accounting for 76.79%) in the second decade. The carbon loss of each under rural gradient was gradually serious. The percentage of grids with moderate and significant decrease in carbon storage escalated from 27.83 to 70.21%. Additionally, grids experiencing high carbon loss moved from the northeast coast to the southwest inland. The response of carbon storage change showed that the expansion of agricultural space occupied by economic space played a crucial role in the carbon loss in each urban–rural gradient. The carbon loss caused by supplementing agricultural space with green space increased from the urban to the field. Enhancing the CCD of landscape patterns can boost carbon storage, and the scattering expansion of economic space needs to be avoided. This paper provides a novel perspective to explore the spatial response of carbon storage change to the territorial space composition and landscape pattern evolution, which is important to optimize the territorial space pattern and improve the regional carbon sink capacity. [ABSTRACT FROM AUTHOR]

The growing interest in the Management of Eco-Friendly Supply Chains warrants this study. Green supply chain management (GSCM) is an approach to supply chain management (SCM) that takes into account environmental factors. Therefore, GSCM is vital in shaping the cumulative environmental effect of businesses engaged in supply chain operations. In addition, GSCM may help improve the effectiveness of sustainability initiatives. Manufacturing companies, particularly in developing nations like India, are trying to adjust essential procedures and supply chains because of the rising need to be ecologically sustainable. However, such efforts must be deployed strategically to be ecologically sustainable and economically successful. As a result, this study focuses on the relationship between green supply chain management and education that affect environmental sustainability and economic performance. As a further step toward more sustainable development, the mediating function of education is sustainable economic growth and environmental health. The data was collected by distributing a well-crafted questionnaire to manufacturing facilities in India. We employed PLS-SEM to analyze and interpret the data test hypotheses based on data from 415 replies. The findings point to cost and profit as the primary metrics of corporate success. Disposal of trash, usage of resources, and release of greenhouse gases are alternative measures of environmental sustainability. Distributed online links and in-person interviews with employees at companies throughout India who use GSCM procedures provided the basis for the study's primary data set. The data was gathered with the use of an organized survey form. The findings of tests conducted on the hypotheses were considered. According to this research, cost, profit, waste, resource, and GHG emission impacts vary depending on which GSCM techniques are implemented. Green supply chain management strategies significantly affect price, trash disposal, resource utilization, and GHG emissions. There was no discernible trend between GSCM methods and financial success. In addition to discussing the unique elements of sustainable supply chains and the limits of current research, this article also discusses how a company's bottom line will benefit monetarily from establishing a sustainable supply chain. This should inspire more study in this area. Our investigation revealed patterns and voids, and we used that information to outline a thorough plan for future GSCM studies. The research helps manufacturing company management improve their sustainable policies while providing policymakers with pointers. [ABSTRACT FROM AUTHOR]

Resource-based cities are important strategic bases for securing resources in China and have made great contributions to the country's economic development. Long-term extensive resource development has made resource-based cities an important region constraining China from achieving comprehensive low-carbon development. Therefore, it is of great significance to explore the low-carbon transition path of resource-based cities for their energy greening, industrial transformation, and high-quality economic development. This study compiled the CO2 emission inventory of resource-based cities in China from 2005 to 2017, explored the contribution to CO2 emissions from three perspectives (driver, industry, and city), and predicted the peak of CO2 emissions in resource-based cities. The results show that resource-based cities contribute 18.4% of the country's GDP and emit 44.4% of the country's CO2 and that economic growth and CO2 emissions have not yet been decoupled. The per capita CO2 emissions and emission intensity of resource-based cities are 1.8 times and 2.4 times higher than the national average, respectively. Economic growth and energy intensity are the biggest drivers and main inhibitors of CO2 emissions growth. Industrial restructuring has become the biggest inhibitor of CO2 emissions growth. Based on the different resource endowments, industrial structures, and socio-economic development levels of resource-based cities, we propose differentiated low-carbon transition pathways. This study can provide references for cities to develop differentiated low-carbon development paths under the "double carbon" target. [ABSTRACT FROM AUTHOR]

This paper analyses how short-term fluctuations in economic growth affect inequality in developing countries. Using a sample of 71 countries, we find that, on average, growth upswings are associated with reductions in inequality. This reduction is, however, largely undone by growth slowdowns. A mediation analysis framework helps identify unemployment, especially youth unemployment, as the main channel through which fluctuations in growth affect the dynamics of inequality. These findings suggest that both the quality of jobs created, and labor market policies are important to ensure that growth outcomes are conducive to inequality reduction. [ABSTRACT FROM AUTHOR]

We provide estimates of the effects that income inequality has on economic growth in China. Our empirical analysis is at the county level. Using data provided by the China Health and Nutrition Survey, we construct measures of inequality and the growth rates of household incomes per capita for 72 Chinese counties during the period 1989–2015. System-GMM estimates of panel models show that the within-county effect of inequality on economic growth is significantly decreasing in initial average income. For the relatively low levels of initial average incomes that were prevalent in China during the 1980s and 1990s, our model estimates imply that the increase in inequality that occurred in China during the 1980s and 1990s had a significant positive effect on economic growth. However, for current levels of average income, our panel model predicts that inequality has a negative effect on economic growth: a 1 percentage point increase in the Gini would reduce the per annum growth rate by around 1 percentage point. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei region is not only an important economic center in China, but also one of the major regions contributing to China's carbon emissions. Revealing the spatial distribution between carbon emissions and economic growth is essential for the formulation of low-carbon development policies. Following the principle from macro to micro, this paper investigates the spatial evolution trend and distribution characteristics between carbon emissions and economic growth in the Beijing-Tianjin-Hebei region from 2005 to 2020 by applying imbalance index model, the rank-scale rule, and decoupling index model. The results show that the imbalance index of carbon emissions decreased between 0.0601 and 0.0533 in a fluctuating way, indicating that the imbalance of spatial distribution of carbon emissions decreases. The imbalance index of economic growth increased between 0.0738 and 0.0851, indicating that economic growth has become more disequilibrated, and the spatial evolution of carbon emissions is not coordinated with economic growth. The Zipf dimension of carbon emissions declined from 1.1806 in 2005 to 0.9594 in 2020, and carbon emissions declined in big cities and increased in cities of the middle order. The Zipf dimension of economic growth increased from 1.1384 in 2005 to 1.2388 in 2020, and the economic growth monopoly in big cities increased. The decoupling coefficient of carbon emissions to economic growth declined, and the driving effect of economic growth on carbon emissions diminished. It is recommended that the Beijing-Tianjin-Hebei region should coordinate the allocation of factors and coordinate industrial adjustment. Hebei should accelerate industrial upgrading and establish a diversified industrial system. [ABSTRACT FROM AUTHOR]

The value of environmental safeguarding is rising in both private and public spheres. What is meant by the term "green supply chain management" (GSCM)? It is minimizing the negative effects of a company's operations on the natural world. Particularly in the research and academic disciplines of the expanding economy of the China region, the concept of the intersection of green supply chain management and sustainable development is dissected at a foundational level. However, there has been little attention paid to how GSCM, GHC, environmental performance, and economic performance all relate to one another. This study fills that void in the literature by giving hard data to encourage businesses in the China area to adopt GHC (green human capital) and SCM (sustainable supply chain management) in order to significantly improve their environmental and economic outcomes. To better understand the interplay between these ideas, we constructed a conceptual framework. The information was gathered using a survey consisting of questionnaires. Manufacturing companies from ten (10) different areas in China provided the 470 responses. The information was analyzed using structural equation modeling (SEM). Research shows that green human capital and green supply chain management have a beneficial influence on economic performance but no discernible effect on environmental outcomes. The results also demonstrate that green supply chain management is an effective act as a mediator between environmental performance and economic performance, with a beneficial effect on both. An initial conclusion may be made that bettering the green human capital stock was more important for China's green economy's growth than bettering the human capital structure. Research like this helps fill out the picture of the green economy and informs policy decisions at the national level. [ABSTRACT FROM AUTHOR]

This paper investigated the dynamic and causal relationship among energy intensity, economic growth, urbanization, energy consumption, FDI, and PM2.5 in 1995–2019 period for China, India, Germany, Canada, USA and United Kingdom countries through Panel Fourier Bootstrapping ARDL (PFBARDL) model and Panel Fourier causality test. According to PFBARDL results, the evidence of cointegration between the variables was detected. In the PFBARDL model, the error correction coefficient is determined as -0.169. Results showed that there is a bidirectional causality between economic growth and PM2.5 release, between fdi and PM2.5 release, between energy intensity and PM2.5 release. Rising economic growth, energy consumption structure, and urbanization will have an adverse effect on PM2.5 concentrations. Policy makers must carefully balance the connection between mitigation of PM2.5 and diminishing energy consumption, and increasing economic growth, urbanization, and energy intensity for determining policies to control PM2.5 concentrations. Thus, in order to reduce PM2.5, the governments must explore a new economic pattern to decouple the linkage between PM2.5 and economic growth. [ABSTRACT FROM AUTHOR]

Large-scale internal migration and unprecedented urbanization have dramatically promoted economic growth in China, resulting in a rapid surge in carbon emissions in urban areas. However, few studies have investigated the causal effect of mass internal migration on carbon emissions or examined the effects of autonomous mitigation mechanisms, such as population agglomeration and technological innovation. This study identifies the causal effect of internal migration on prefectural-level cities' carbon emissions in China by employing an instrumental variable and further investigates the buffering effect of population agglomeration and technological innovation using mediating effect models. The results show that mass internal migration has a substantial impact on increasing carbon emissions in prefectural-level cities. If the proportion of inflowed migrants rises by 1% point, prefectural-level cities' carbon emissions per capita will increase by 1.9%. A series of robustness tests confirms the result. Population migration also promotes population agglomeration and technological innovation in urban areas. Two autonomous mechanisms buffer 11.9% and 5.4% of prefectural-level cities' incremental carbon emissions per capita caused by population migration, respectively. This study highlights the crucial role of population agglomeration and technological innovation in mitigating carbon emissions in cities experiencing significant migrant inflows and provides several implications for formulating relevant policies. [ABSTRACT FROM AUTHOR]

Liquefied petroleum gas (LPG) is one of the energy resources that deserve to be qualified as a transition fuel for developing countries that cannot abandon their dependence on non-renewable energy use and adopt renewable alternatives. The current study examines how environmental degradation is affected by financial development, LPG use, and economic growth in the BRICS-T countries (Brazil, Russia, India, China, South Africa, and Turkiye) in the period of 1993–2018. For this purpose, four models were tested with Pedroni, Kao, PMG Panel ARDL cointegration and Dumitrescu-Hurlin causality methods. The results show that LPG consumption has a positive effect on the ecological footprint and an adverse influence on the CO2 emission of BRICS - T countries. The financial institutions exhibited to have a positive and significant impact on ecology. Economic growth displayed negative effects on environmental degradation and a positive influence on CO2. Additionally, there is significant evidence for the validity of the EKC hypothesis. Unidirectional causality exists between ecological footprint, LPG, financial market, and economic growth. The financial institution index shows bidirectional causality with the ecological footprint. There is also unidirectional causality between ecological footprint, LPG, financial market, and economic growth. Furthermore, the financial institutions' index shows a bidirectional causality with the ecological footprint. Also, economic development and financial institution index have a bidirectional relationship with CO2 emissions. On the other hand, the financial market index showed unidirectional causality with CO2 emissions. In short, our study highlights the need for a comprehensive and integrated approach to sustainable development in BRICS - T countries. Policymakers must balance economic growth with environmental protection and consider the potential trade-offs between policy options to promote sustainable and inclusive development. [ABSTRACT FROM AUTHOR]

The importance of fostering a thriving green economy is emphasized as a key strategy for mitigating the threats posed by climate change. This study aims to assess the influence of social inclusion and green finance on the sustainable growth of 31 Organization for Economic Co-operation and Development (OECD) nations between 2010 and 2021. The results obtained using the fully modified OLS (FMOLS) methodology indicate that social factors such as poverty reduction and social inclusion do not impact the green economic prosperity of OECD countries with an industry-focused economic structure. Furthermore, the expansion of green finance markets and the attraction of foreign direct investment with an environmental focus can contribute to the advancement of green development in OECD countries. As a recommendation, it is advisable for OECD nations to place greater emphasis on developing the green digital finance market, exploring blockchain-based green finance solutions, fostering green foreign direct investment, and promoting early warning economic systems. [ABSTRACT FROM AUTHOR]

A significant portion of the human diet is comprised of fruits, which are consumed globally either raw or after being processed. A huge amount of waste and by-products such as skins, seeds, cores, rags, rinds, pomace, etc. are being generated in our homes and agro-processing industries every day. According to previous statistics, nearly half of the fruits are lost or discarded during the entire processing chain. The concern arises when those wastes and by-products damage the environment and simultaneously cause economic losses. There is a lot of potential in these by-products for reuse in a variety of applications, including the isolation of valuable bioactive ingredients and their application in developing healthy and functional foods. The development of novel techniques for the transformation of these materials into marketable commodities may offer a workable solution to this waste issue while also promoting sustainable economic growth from the bio-economic viewpoint. This approach can manage waste as well as add value to enterprises. The goal of this study is twofold based on this scenario. The first is to present a brief overview of the most significant bioactive substances found in those by-products. The second is to review the current status of their valorization including the trends and techniques, safety assessments, sensory attributes, and challenges. Moreover, specific attention is drawn to the future perspective, and some solutions are discussed in this report. [ABSTRACT FROM AUTHOR]

Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO2 emissions, economic growth, electricity consumption, and trade openness in Serbia. Initially, an Autoregressive Distributed Lag (ARDL) model is used to characterize the Environmental Kuznets Curve (EKC) using data from the period from 1995 to 2019, followed by the construction of a bootstrap logistic regression model to predict environmental quality in Serbia. Long-term estimates of the model confirm an inverted U-shaped relationship, where all three variables exert a statistically significant influence on CO2 emissions. In the short run, however, a causal relationship is only observed between electricity consumption and CO2 emissions. The logistic regression results show that all three factors significantly influence environmental quality. The study proposes policy recommendations for Serbia, such as promoting sustainable economic growth, implementing long-term programs to reduce CO2 emissions, reviewing trade policies to prioritize sustainable practices, and investing in renewable energy sources to reduce emissions. [ABSTRACT FROM AUTHOR]

Bilateral debt swap is an innovative global financing mechanism designed to support heavily indebted countries (HICs). It is a debt-restructuring process involving donor countries forgiving debt owed by HICs in exchange for commitments to undertake projects on environment and socio-economic development. It is a unique approach designed to help heavily indebted countries get back on their feet. Effective debt swap financing can lead to both economic growth and environment sustainability, but they are challenging to implement. This study examines the impact of bilateral debt swap financing on economic growth and environment sustainability. For the purpose, we have used debt swap index developed with Kaiser–Meyer–Olkin (KMO) methodology. KMO widely used approach of Principle Component Analysis (PCA) to solve the problem of "over-identification" and make strong correlation among endogenous variables of interest. In order to validate the nexus empirically between bilateral debt swap financing with economic growth and environment sustainability, we have employed the Two-Step System Generalized Method of Moments (SYS-GMM) approach in 25 countries for the period of 2002 to 2021. This modern econometric method addresses endogeneity issues and controls for unobserved heterogeneity in panel data. At the same time, the technique addresses the simultaneity problem, reverse causality, and remove selection bias. Findings of the study shows that effective bilateral debt swap financing can boost economic growth and environment sustainability by investing domestic resources for targeted activities along with reduced debt burden. Empirical results reveal that 1% change in debt swap financing can lead to a maximum of 0.23% growth in the economy and 0.28% improvement in environment sustainability. However, it is important to note that in most empirical specifications, results are inconclusive. One possible reason for this is often ineffective debt swap practices coupled with inadequate monitoring and evaluation in HICs. Policymakers should focus on enhancing debt swap policies to promote economic growth and environment sustainability. [ABSTRACT FROM AUTHOR]

This study examines the environmental Kuznets curve (EKC) theory and its possible relevance in the context of China and the complex and one-of-a-kind interaction between financial innovation, environmental deterioration, and China. China's fast industrialization and consequent economic expansion have been accompanied by significant environmental difficulties, despite the country's status as the world's second largest economy. The research takes a secondary data approach to its investigation of this topic, drawing on a large dataset that spans many decades to ensure a thorough examination of the dynamic interaction between financial innovation and numerous environmental variables. The primary objective of this research is to determine whether or not recent developments in financial technology have contributed to the current trends of environmental degradation in China. In keeping with the central tenet of the EKC hypothesis, this study uses cutting-edge econometric techniques to investigate the existence of nonlinear correlations and inflection points. In addition, the research analyzes how policy interventions and regulatory measures have shaped the tendencies spotted. In elucidating the usefulness of financial innovation as a tool for promoting environmental betterment, this study's findings substantially contribute to the current discussion around sustainable development and economic policy. This research also carefully assesses the applicability of the EKC theory in China, providing insights that may be used to inform future environmental policy decisions. Ultimately, the success of measures to promote sustained economic growth and the preservation of the environment in China depends on an in-depth understanding of these delicate relationships. In addition, the lessons learned from this study have the potential to serve as a guide for economies facing similar difficulties. [ABSTRACT FROM AUTHOR]