Small and medium scale enterprises (SMEs) act as a promoter of economic development of the developed and under developed nations. Developing countries like Nigeria that, require sustainable economic growth and development must pay attention to the SMEs sectors in order to reduce unemployment, poverty and improve the standard leaving of its society. Unfortunately, in Nigeria, SMEs have underperformed despite that, 90% of the Nigerian businesses are small scales but their contribution to the Nigerian GDP is below 10%. The main reason for this low contribution of SMEs to Nigerian GDP could be attribute to poor funding, lack of management expertise and lack of access to modern technology among others, with proper finance the SMEs can acquire modern technology and employed qualified staff. Thus, this paper focuses on crowdfunding as financial option for Nigerian SMEs. However, the paper is a conceptual framework.
Occupational cancers, including mesothelioma and lung cancer are linked to the use of asbestos. Annually, at least 100,000 global deaths are attributed to asbestos exposure putting a heavy burden on national budgets. Expenses incurred on treatment of asbestos related diseases (ARDs) reduce households and national resource savings, while ARDs culminate in terminal burdens. The objective of this study is to measure the economic burden of ARDs and to assess the economic impact of asbestos consumption. The health and economic burden of asbestos was estimated in macro-global consumption-production model using production function frontier-based and generalized least squared approach for asbestos products and cost tabulation. Production, in metric tons (Mt) was adopted as a dependent variable among explanatory variables, including consumption. Information on treatment cost of asbestos related diseases (mesothelioma, asbestosis and lung cancer) was obtained from costing information and published literatures. Annual total economic burden of asbestos is at USD 11.92 billion. Out of this cost, USD 4.34 billion per annum is the economic burden of managing three common ARDs. The cost of compensation for patients suffering ARDs is USD 4.28 billion. From the remaining USD 3.3 billion, USD 2.93 billion is the value of asbestos consumed in 2003 and USD372.15 million is the loss of earning due to hospital visits and admissions. For every USD 1 spent on consumption of asbestos, global economy has to absorb almost USD 4 due to health consequences of ARDs. Banning of asbestos production and usage in production of goods has far-reaching impacts on household welfare, health and economic development. The insights revealed are expected to inform decision makers the need to ban all forms of asbestos, especially in developing countries where usage is increasing.
This work aims to assess multidimensional energy poverty and energy efficiency for environmental policy measures using data envelopment analysis (DEA), a DEA-Like mathematical composite indicator applied on a dataset based on multiple sets of variables from South Asian economies. The multidimensional energy poverty index (MEPI) is computed to analyze the combining effects and energy poverty in these countries. Simultaneously, South Asia's metropolitan areas' population rose by 130 million between 2001 and 2011 and is projected to expand by approximately 250 million by 2030. The findings reveal that endogenous increasing population shocks account for about 72% of energy use. In contrast, the long-term effects of remittance revenue, economic growth, and urbanization on energy use are approximately 20%, 8.25%, and 0.03%, respectively. This work advocates more coordinated and innovative policies to eliminate energy poverty. It can act as a base for policymakers and government officials to make efficient policies and enforce them properly in the regional power sector. Policies should be designed around a smarter use of biomass for cooking, alternate sources for domestic energy production, increased programs for biomass-based cookstoves, and periodic regional-level energy database development.
Obesity is a worldwide concern as it leads to adverse effects on human health. This study uses a panel of 165 countries and annual data from 2000 to 2014 to examine the obesity Kuznets curve (OKC) hypothesis. By using tests and estimators that are robust to cross-section dependence (CSD), our results support the OKC hypothesis. This indicates that obesity increases at the initial stage of economic development and eventually would decrease once the threshold is reached. In addition, we find that the role of global warming on obesity is not significant. Food production is found to be a contributing factor to obesity. Besides, one-way and two-way causalities are identified between the variables. This study provides important insights particularly about the relationship between (i) economic growth and obesity and (ii) environmental degradation and obesity. Implication of the results and policy recommendations are also provided to policymakers and health personnel in finding solutions to the obesity epidemic around the world.
The aim of the study is to estimate the nexus between energy insecurity and energy poverty with the role of climate change and other environmental concerns. We used DEA like WP methods and properties of MCDA, a most common form of data envelopment analysis (DEA) to estimate the nexus between constructs. This paper presents a measurement and analysis of G7 countries' energy, economic, social, and environmental performance associated with energy poverty indexes. The study used the multiple, comprehensive, and relevant set of indicators, including energy economics and environmental consideration of energy poverty. The net energy consumption of al G7 economies is equal to 34 percent of the entire world along with the net estimate GDP score of around 50 percent. Using DEA modelling and estimation technique, our research presented valuable insights for readers, theorists and policy makers on energy, environment, energy poverty and climate change mitigation. For this reasons, all these indicators combined in a mathematical composite indicator to measure energy, economic, social, and environmental performance index (EPI). Results show that Canada has the highest EPII score, which shows that Canada's capacity to deal with energy self-sufficiency, economic development, and environmental performance is greater than the other G7 countries. France and Italy rank second and third. Japan comes next with 0.50 EPI scores, while the USA has the lowest average EPI score environment vulnerable even though have higher economic development among the G7 group countries. We suggest a policy framework to strengthen the subject matter of the study.
This paper assesses the Environmental Kuznets curve based on quantile behavior of the relationship between economic growth, forest area, agriculture production, renewable energy, and environmental degradation. The current literature generally used a single indicator to address environmental issues; however single indicator neither measures overall environmental conditions nor does specify that the environment issue is generally diminishing. Our study is the first one that used ecological footprint (EF) as an indicator to test environmental Kuznets curve (EKC) hypothesis for Pakistan by employing recent approach of quantile autoregressive distributed lag (QARDL) initiated by Cho et al. (J Econ 188(1):281-300, 2015). The result of this study validates the EKC hypothesis for Pakistan and shows quantile-dependent relationship, and in that case, using the conventional methods may somewhat lead to biased results. Moreover, the rejection of the null hypothesis of parameter constancy is also confirmed by Wald test. In the long run, the findings of renewable energy consumption and forest area show significant negative effects on ecological footprints, which indicates that by increasing renewable energy usage and forest area, ecological footprints can be minimized. Interestingly, the short-term effects of agricultural production findings on EF show statistically negative results. This illustrates that EF can also be reduced in the agriculture sector by adopting environment-friendly technologies. In order to create efficient policies for environment deterioration, the empirical findings of the current analysis can be used as a guideline for policy implications.
This study measures the energy rebound effects of Chinese energy and coal power use in Chinese energy-intensive industries by using latent class stochastic frontier models like LMDI, and other various econometric estimation approach for coal-supplying regions in China ranging between 1992 and 2018. The findings reveals that China's coal sector's average capacity consumption is 0.81%, with a pattern of first increasing and then decreasing, falling to 0.68% in 2016 specifically. The coal capacity operation rate concerning low as well as depleted regions is generally strong, with limited space for expansion. In 2015 and 2016, the utilization rate of coal production potential in moderate-producing areas fell about 42%. Economic development variables affect the capacity utilization levels of moderate, weak, and depleted generating regions. At the same time, the price volatility cannot induce a practical improvement in the ability utilization rate, which means that China's coal industry is mainly un-marketized. China's energy efficiency increased about 19.98% among 2000 and 2016, while the rapidest expansion pattern has been noted in the eastern province at 39.86%, next to central (11.71%) and western regions (9.59%). The take back impact via the renewable energy and renewable productivity channels is estimated as 12.34% and 25.40%, respectively. Therefore, the take back impact is of significant importance regarding energy preservation, as China's cumulative renewable energy use is equal to China's aggregate energy use. On such findings, recent research also contributed by presenting novel policy implications for key stakeholders.
To boost the stability of economic and financial aspects along with the apprehensions for sustainability, it is important to promote the development of clean energy stocks around the globe. In the current research, the researchers have examined the impact of oil prices, coal prices, natural gas prices, and gold prices on clean energy stock using the autoregressive distribution lag (ARDL) approach from the year 2011 to the year 2020. The result of daily data analysis specifies that in the long as well as in the short run, gold prices, oil prices, and coal prices have a positive and significant effect on clean energy stock. On the other side, natural gas prices in the long as well as in the short run have a negative and significant effect on clean energy stock. So, the empirical analysis of our study is of interest to investors at an institutional level who aim at detecting the risk associated with the clean energy market through proper financial modeling. Besides, this study opens up a new domain to sustain financial as well as economic prospects by protecting the environment through clean energy stock as the investment in clean energy stocks results in producing a substantial effect on the economy and the environment as well.
For the purpose of this study, the role of technological innovation is examined. Few studies have examined empirically and theoretically the relationship between technological innovation and ecological footprint in conjunction with other factors, such as the human capital index and renewable energy sources, such as biofuels and nuclear power. This study examines the impact of technological innovation on G-7 countries' ecological footprints from 1990 to 2020. A cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model is used in the study. The results of the study show that technological innovation minimizes the ecological footprint. A lower ecological footprint is also associated with increased usage of human capital and renewable energy. Depletion of the natural environment is a short-term and long-term consequence of increased GDP growth. Our results confirm that ecologically sustainable technology enhances the quality of the environment. Consistent panel causality results were achieved. In the context of the G-7 countries, our study's results could support the idea that there are new policy ideas that could help achieve the Sustainable Development Goals (SDG 3, 4, 7, 8, 9, and 13).
There are many advantages of geothermal energy as an environmentally friendly resource; however, there are quite a several challenges that need to be overcome to completely harness sustainable and renewable energy that is also natural. The primary aim of this study is to examine what influence geothermal energy will have on land use changes among the considered 27 states in the European Union from the time being 1990 to 2021. The study adopts the auto-regressive distributed lag (ARDL); the findings show that geothermal energy growth could be leveraged to achieve remarkable growth in land use change among the 13 European developing economies than among the 14 EU developed economies. On the other hand, results from analysis further show that a remarkable decrease in land use change could be better attained among the 14 EU developed economies that among the 13 EU developing economies as a result of institutional quality. Furthermore, the result suggests that through economic growth, there could be a remarkable increase in land use change among the 14 EU developed economies than among the 13 EU developing economies. It was further revealed by the study that the level of land use change among the 27 EU nations could be remarkably increased, boosting the level of geothermal energy production that will assist in attaining the aims behind the 2030 energy union. This will eventually help in curbing the incidence of climate change and pollution in the environment; the projected calculations are observed to be valid, as confirmed through the chosen three estimators for this research. The chosen estimators are the pooled mean group, mean group, and dynamic fixed effect. The regulations and governors in 27 European Union countries should give priority to using geothermal in their renewable energy mix to reduce the incidence of changes in land structures. Also, an increased level of efficiency and effectiveness should be made to the generation of geothermal energy by state actors and investors to prompt sustainability and attainability with no further depreciation in agricultural and forest natural states.
OECD countries have encountered the challenges of improving the environmental sustainability while maintaining economic growth by not impairing employment. This study attempts to reexamine the environmental Kuznets curve (EKC) hypothesis by using ecological footprint as an indicator of environmental degradation. Besides, our study aims to test the validity of environmental Phillips curve (EPC) and role of clean energy on ecological footprint. Our data cover a panel of 36 OECD countries from 1995 to 2015. We adopt the second-generation panel unit root and cointegration test to account for the presence of cross-section dependence (CSD). Moreover, the long-run relationship is estimated using Common Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) that are robust to CSD. Our findings reveal that the EKC hypothesis is not valid while EPC is confirmed in OECD countries. Though there is a trade-off between unemployment and environmental degradation in OECD countries, the development of new technologies, especially in the clean energy sector, could be a key factor contributing to sustainable growth and better environmental quality. Thus, it is recommended that OECD countries should focus on the development of innovative green technologies and strengthen the initiatives that promote renewable energy consumption.
Under the new development model, the digital economy has become a new engine to promote the green development of the economy and achieve the goal of "double carbon." Based on panel data from 30 Chinese provinces and cities from 2011 to 2021, the impact of the digital economy on carbon emissions was empirically studied by constructing a panel model and a mediation model. The results show that firstly, the effect of the digital economy on carbon emissions is a non-linear inverted "U" shaped relationship, and this conclusion still holds after a series of robustness tests; secondly, the results of the benchmark regression show that economic agglomeration is an essential mechanism through which the digital economy affects carbon emissions and that the digital economy can indirectly suppress carbon emissions through economic agglomeration. Finally, the results of the heterogeneity analysis show that the impact of the digital economy on carbon emissions varies according to the level of regional development, and its effect on carbon emissions is mainly in the eastern region, while its impact on the central and western regions is weaker, indicating that the impact effect is primarily in developed regions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the development strategy of the digital economy according to local conditions to promote a more significant carbon emission reduction effect of the digital economy.
In this study, we explore the dynamics between innovation, institutional quality, and foreign-aid flows in middle-income countries. Using an appropriate econometric model, we investigate the links between these variables in 79 middle-income countries (MICs) over 2005-2020. The results from our study show that foreign aid, institutional quality, and innovation have strong endogenous relationships. The short-run outcomes show that innovation Granger-causes institutional quality; foreign aid Granger-causes innovation; and quality of institutions Granger-causes foreign aid. The long-run outcomes indicate that institutional quality and innovation significantly affect the flow of foreign aid to the MICs. These results indicate that policy-makers in both foreign aid donor and recipient countries should pursue appropriate policies on foreign aid, quality of institutions, and innovation. For instance, in the short run, planners and evaluators in donor countries can direct their aid to MICs that have persistent challenges in improving their institutions and enhancing their innovative capabilities. In the long run, recipient countries ought to recognize that their institutional quality and innovation have a considerable impact on the inflows of foreign aid to their countries.
This study investigates the energy security and income roles in testing environmental Kuznets curve (EKC) for developing countries from 1990 to 2019. The panel quantile regression approaches are employed to examine the relationship between the variables, considering that income and energy security effects on carbon emissions may vary across distributions. Findings revealed that the EKC hypothesis was inconsistent at low and high quantiles when estimating energy availability, affordability, and acceptability. The validity of inverted U-shaped EKC is supported at high quantiles for energy affordability and accessibility in developing countries. However, given the energy accessibility and acceptability, the EKC hypothesis becomes invalid in developing countries. Notably, developing countries have yet to progress toward achieving energy security as a switch component to low carbon emissions. This study contributes to the literature by revealing the effect of availability, accessibility, affordability, and acceptability of energy security on carbon dioxide emissions (CO2). Thus, it suggests implications for improving environmental quality in developing countries by enhancing energy security. Diversifying energy sources with nuclear, renewable, and developing technologies reduces dependence risks on a single source while improving efficiency through technology and demand management lowers carbon emissions and strengthens energy security. Beyond energy security, this study emphasises sustainable urban planning to promote compact development, effective transportation, and green infrastructure to reduce energy use and improve environmental sustainability, ultimately reducing carbon emissions.
Climate change repercussions such as temperature shifts and more severe weather occurrences are felt globally. It contributes to larger-scale challenges, such as climate change and biodiversity loss in food production. As a result, the purpose of this research is to develop strategies to grow the economy without harming the environment. Therefore, we revisit the environmental Kuznets curve (EKC) hypothesis, considering the impact of climate policy uncertainty along with other control variables. We investigated yearly panel data from 47 Belt and Road Initiative (BRI) nations from 1998 to 2021. Pooled regression, fixed effect, and the generalized method of moment (GMM) findings all confirmed the presence of inverted U-shaped EKC in BRI counties. Findings from this paper provide policymakers with actionable ideas, outlining a framework for bringing trade and climate agendas into harmony in BRI countries. The best way to promote economic growth and reduce carbon dioxide emissions is to push for trade and climate policies to be coordinated. Moreover, improving institutional quality is essential for strong environmental governance, as it facilitates the adoption of environmentally friendly industrialization techniques and the efficient administration of climate policy uncertainties.
The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.
The world faces immense pressure regarding the negative impacts of increased greenhouse gas emissions, climate change, global warming, droughts, and many other environmental problems. Australia is also facing the same issues and requires urgent attention. In this research, we have examined the effect of hydrogen firms on Australia's greenhouse gas emissions. We employed the monthly data from January 2002 to December 2021 for econometric estimations. Through quantile regression, it is noted that the expansion of hydrogen firms contributes to environmental pollution instead of controlling the emissions. Most hydrogen energy still emits carbon dioxide, which contributes to climate change. Around the world, carbon-containing fossil fuels produce more than 95% of hydrogen energy. However, as a policy suggestion, it is recommended that green hydrogen produced by electrolysis of water using renewable energy sources will succeed in achieving the Sustainable Development Goals (SDGs).
To tackle the growing menace of environmental degradation, the idea of green entrepreneurship has gained popularity, which is the process of creating new goods and technologies to solve environmental problems. Like traditional entrepreneurs, green entrepreneurs also need financial backing from financial institutions. However, no empirical evidence was found regarding the relationship between formal credit and green entrepreneurship. This analysis is an effort to plug this vacuum into the literature by analyzing the impact of formal credit on green entrepreneurship in high, middle, and low-income economies from 2011 to 2021. The study has employed various econometric techniques such as fixed-effects, random-effects, 2SLS, and GMM. The results show that formal credit substantially develops green entrepreneurship in high, middle, low-income, and full samples. Besides formal credit, GDP, environmental pressure, trade openness, technological development, and human capital are crucial in green entrepreneurship development in all samples. Policymakers may collaborate with financial institutions to create and provide specialized financial products and services catering to green entrepreneurs.
Africa faces significant economic and environmental challenges, including waste generation, food insecurity, and energy inefficiency, jeopardizing future generations. To address this, Africa has adopted the 10-year Sustainable Consumption and Production Framework for Africa (10-YFP), evident through national and local projects focusing on sustainable food and agriculture, technology transfer in water irrigation, and related initiatives. The Belt and Road Initiative (BRI) presents an opportunity for promoting green cooperation and sustainable development in Africa, though its impact on ethical production and consumption remains unexplored. This study evaluates the BRI's role in achieving Africa's Twelve Sustainable Development Goals (SDGs) and catalyzing responsible consumption and production. Through interviews and focus group discussions (FGDs) involving 42 participants from 19 African countries, thematic patterns emerged using the thematic inductive method. Findings indicate that BRI initiatives effectively integrate advanced technologies to enhance sustainable agriculture and industrial production. Notably, BRI investments in countries like Morocco, Algeria, Ethiopia, Kenya, and Zambia are fostering renewable energy projects to provide electricity to underserved communities. A stronger alignment between national sustainable development plans and the green BRI is essential to maximize the benefits without compromising BRI principles of inclusivity, coordination, coherence, and capacity building. This research fosters dialogue among academics, educators, government officials, business leaders, and investors about the transformative potential of China's BRI in African nations. By shedding light on the positive strides made by BRI programs, this study underscores the need for strategic synergy between international cooperation efforts and localized sustainability agendas, ultimately propelling Africa toward its long-term development goals.
Energy is one of the prime factors in influencing the sustainable development of a country. Different energy sources play important roles in driving the income growth of different economic sectors such as industrial, agricultural, and services. Fossil fuels, however, have come under strong criticism for actively accelerating climate change. As such, it is imperative to investigate the contributions of various energy sources toward sustainable growth. With Malaysia as the test-bed, the present study analyzes the impact of energy prices on economic stability using the novel wavelet-based analysis. Specifically, the study analyzed the impact of crude oil, natural gas, and gasoline prices on the economic (brown) and green growth from 1995 to 2020. The results show that in continuous wavelet transform, the cone of influence of all five factors exhibits strong short-run variance and fluctuations from 2005 to 2013. However, the intensity of brown growth is more influential than green growth. Similarly, in wavelet coherence graphs, the downward right arrows indicate positively significant associations between crude oil prices, natural gas prices, and gasoline prices with brown and green growth. Additionally, wavelet-based Granger causality reveals a bidirectional causal relationship between all variables. The results thus strongly suggest that energy prices predominantly affect the economic (brown) and green growth progression of the Malaysian economy. The study concludes with some suggested implications to augment the country's sustainable growth.