Advances in financial inclusions have contributed to economic growth and poverty alleviation, addressing environmental implications and implementing measures to mitigate climate change. Financial inclusions force advanced countries to progress their policies in a manner that does not hinder developing countries' current and future development. Consequently, this research examined the asymmetric effects of information and communication technology (ICT), financial inclusion, consumption of primary energy, employment to population ratio, and human development index on CO2 emissions in oil-producing countries (UAE, Nigeria, Russia, Saudi Arabia, Norway, Kazakhstan, Kuwait, Iraq, USA, and Canada). The study utilizes annual panel data spanning from 1990 to 2021. In addition, this study investigates the validity of the Environmental Kuznets Curve (EKC) trend on the entire sample, taking into account the effects of energy consumption and population to investigate the impact of financial inclusion on environmental degradation. The study used quantile regression, FMOLS, and FE-OLS techniques. Preliminary outcomes revealed that the data did not follow a normal distribution, emphasizing the need to use quantile regression (QR). This technique can effectively detect outliers, data non-normality, and structural changes. The outcomes from the quantile regression analysis indicate that ICT consistently reduces CO2 emissions in all quantiles (ranging from the 1st to the 9th quantile). In the same way, financial inclusion, and employment to population ratio constrains CO2 emissions across each quantile. On the other side, primary energy consumption and Human development index were found to increase CO2 emissions in each quantile (1st to 9th). The findings of this research have implications for both the academic and policy domains. By unraveling the intricate interplay between financial inclusion, ICT, and environmental degradation in oil-producing nations, the study contributes to a nuanced understanding of sustainable development challenges. Ultimately, the research aims to guide the formulation of targeted policies that leverage financial inclusion and technology to foster environmentally responsible economic growth in oil-dependent economies.
Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010-2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions.
The spatial effects of agricultural market integration on industrial agglomeration are an important field of regional economic. This paper collected the data of agricultural market integration and industrial agglomeration in 31 provinces in China from 2010 to 2019, analyzed the spatial effects of the two by constructing a dynamic spatial Dubin model, and explored its long-term and short-term effects of the spatial effects. The results show the following: (1) the primary terms of agricultural market integration were negative and the secondary terms were positive. The impact of agricultural market integration on local industrial agglomeration had a "U-shaped" characteristic. Whether in the short-term or long-term, there was a significant direct effect of "suppression to promotion." (2) The agricultural market integration had a spatial spillover effect on industrial agglomeration in the neighboring areas. This effect had an "inverted U-shaped" characteristic. Whether in the short-term or long-term, there was a prominent spatial spillover effect of "promotion to suppression." (3) For direct effects, the short-term direct effects of agricultural market integration on industrial agglomeration were - 0.0452 and 0.0077, and the long-term direct effects were - 0.2430 and 0.0419. For spatial spillover effects, the short-term spatial spillover effects were 0.0983 and - 0.0179, and the long-term spatial spillover effects were 0.4554 and - 0.0827. The long-term effects were greater than the short-term effects. This paper provides empirical evidence for the effects of agricultural market integration on industrial agglomeration in different regions, and exploring the development of agricultural agglomeration in the long-term.
Numerous studies have demonstrated that the development of low-carbon economy and industrial restructuring cannot occur in a coordinated manner. However, academic literature does not provide further explanations for this phenomenon. In this paper, we introduce a novel decomposition method to reassess the relationship between industrial restructuring and low-carbon economy, which yields similar findings. Next, we construct a straightforward theoretical model to investigate two fundamental reasons that interrelate with this issue: excessively high proportion of secondary sector and excessive carbon intensity of tertiary sector. Finally, we implement a rigorous causal identification using three-dimensional panel data at the provincial, industrial, and yearly levels by undergoing multiple robustness tests and mitigating endogeneity issues. Our heterogeneity tests suggest that the impact of industrial restructuring is greater in high-polluting industries, the Eastern region, and non-digital pilot regions. Overall, our theoretical and empirical analysis serves as a vital reference for other developing and developed countries to attain harmonious development between low-carbon economy and industrial restructuring.
The COVID-19 pandemic has emerged as a significant event of the current century, introducing substantial transformations in economic and social activities worldwide. The primary objective of this study is to investigate the relationship between daily COVID-19 cases and Pakistan stock market (PSX) return volatility. To assess the relationship between daily COVID-19 cases and the PSX return volatility, we collected secondary data from the World Health Organization (WHO) and the PSX website, specifically focusing on the PSX 100 index, spanning from March 15, 2020, to March 31, 2021. We used the GARCH family models for measuring the volatility and the COVID-19 impact on the stock market performance. Our E-GARCH findings show that there is long-term persistence in the return volatility of the stock market of Pakistan in the period of the COVID-19 timeline because ARCH alpha (ω1) and GARCH beta (ω2) are significant. Moreover, is asymmetrical effect is found in the stock market of Pakistan during the COVID-19 period due to Gamma (ѱ) being significant for PSX. Our DCC-GARCH results show that the COVID-19 active cases have a long-term spillover impact on the Pakistan stock market. Therefore, the need of strong planning and alternative platform should be needed in the distress period to promote the stock market and investor should advised to make diversified international portfolio by investing in high and low volatility stock market to save their income. This study advocated the implications for investors to invest in low volatility stock especially during the period of pandemics to protect their return on investment. Moreover, policy makers and the regulators can make effective policies to maintain financial stability during pandemics that is very important for the country's economic development.
Pollution in the environment is today the biggest issue facing the globe and the main factor in the development of many fatal diseases. The main objective of the study to investigate green investments, economic growth and financial development on environmental pollution in the G-7 countries. This study used annual penal data from 1997 to 2021. The panel NARDL (Non-linear autoregressive distributed lag) results affirm that the positive change of green investment and negative shock in green investment have a significant and positive association with environment pollution in G-7 nations. Our findings provide more evidence for the long-term asymmetry between financial development and environmental performance. However, the findings confirm that a positive modification in financial development has a positive and significant effect on environment pollution. Whereas negative shock in financial development is negative and insignificant relationship with environment pollution. Moreover, the outcomes of the study reveal that both positive shock in gross domestic product growth and negative shock of economic growth have a significant and positive link with environment pollution in G-7 countries. According to the findings, by lowering carbon dioxide emissions, green investments reduced environmental pollution in the G-7 nations over the long and short term. Moreover, it is an innovative research effort that provides light on the connection between green investments, financial development, and the environment while making mention to the EKC in G-7 countries. After all these, our recommendation is to increases green investment expenditures to reduce environmental pollution in the G-7 nations based on our findings. Additionally, one important way for the nation to achieve its sustainable development goals is to improve advancements in the financial sector.
This study explores the comprehensive effects of green finance (GF) on the low-carbon transition of the energy system (LTES) by analyzing panel data from 281 cities in China from 2006 to 2021. It is found that GF significantly reduces overall energy consumption and exhibits a U-shaped association with energy efficiency, while its relationship with the energy consumption structure is inverted U-shaped. After accounting for endogeneity in the robustness tests, these findings remain consistent and are therefore deemed reliable. A mechanistic analysis reveals that GF promotes industrial upgrading, technological progress, and economic agglomeration, collectively facilitating the LTES. The impact of GF on LTES shows considerable variation among regions, influenced by their levels of economic growth, extents of marketization, and governmental environmental preferences. Our findings provide new evidence for the relationship between GF and LTES, offering a scientific basis for formulating GF policies to accelerate this transformation.
Climate change and tourism's interaction and vulnerability have been among the most hotly debated topics recently. In this context, the study focuses on how CO2 emissions, the primary cause of global warming and climate change, respond to changes in tourism development. In order to do so, the impact of tourism development on CO2 emissions in the most visited countries is investigated. A panel data from 2000 to 2017 for top 70 tourist countries are analysed using a spatial econometric method to investigate the spatial effect of tourism on environmental pollution. The direct, indirect, and overall impact of tourism on CO2 emissions are estimated using the most appropriate generalized nested spatial econometric (GNS) method. The findings reveal that tourism has a positive direct effect and a negative indirect effect; both are significant at the 1% level. The negative indirect effect of tourism is greater than its direct positive effect, implying an overall significantly negative impact. Further, the outcome of financial development and CO2 emissions have an inverted U-shaped and U-shaped relationship in direct and indirect impacts. Population density, trade openness, and economic growth significantly influence environmental pollution. In addition, education expenditure and infrastructure play a significant moderating role among tourism and environmental pollution. The results have important policy implications as they establish an inverted-U-shaped relationship among tourism and CO2 emissions and indicate that while a country's emissions initially rise with the tourism industry's growth, it begins declining after a limit.
This study was carried out to investigate the effect of economic globalization on economic growth in OIC countries. Furthermore, the study examined the effect of complementary policies on the growth effect of globalization. It also investigated whether the growth effect of globalization depends on the income level of countries. Utilizing the generalized method of moments (GMM) estimator within the framework of a dynamic panel data approach, we provide evidence which suggests that economic globalization has statistically significant impact on economic growth in OIC countries. The results indicate that this positive effect is increased in the countries with better-educated workers and well-developed financial systems. Our finding shows that the effect of economic globalization also depends on the country's level of income. High and middle-income countries benefit from globalization whereas low-income countries do not gain from it. In fact, the countries should receive the appropriate income level to be benefited from globalization. Economic globalization not only directly promotes growth but also indirectly does so via complementary reforms.
The main objective of this study is to investigate the influence of the globalisation (Trans-Pacific Partnership (TPP) agreement in particular) on air pollution in Malaysia. To achieve this goal, the Autoregressive Distributed Lag (ARDL) model, Johansen cointegration test and fully modified ordinary least square (FMOLS) methods are utilised. CO2 emission is used as an indicator of pollution while GDP per capita and urbanisation serve as its other determinants. In addition, this study uses Malaysia's total trade with 10 TPP members as an indicator of globalisation and analyse its effect on CO2 emission in Malaysia. The outcome of this research shows that the variables are cointegrated. Additionally, GDP per capita, urbanisation and trade between Malaysia and its 10 TPP partners have a positive impact on CO2 emissions in general. Based on the outcome of this research, important policy implications are provided for the investigated country.
This study aims to determine an interactive environmental model for economic growth that would be supported by the "sustainability principles" across the globe. The study examines the relationship between environmental pollutants (i.e., carbon dioxide emission, sulfur dioxide emission, mono-nitrogen oxide, and nitrous oxide emission); population growth; energy use; trade openness; per capita food production; and it's resulting impact on the real per capita GDP and sectoral growth (i.e., share of agriculture, industry, and services in GDP) in a panel of 34 high-income OECD, high-income non-OECD, and Europe and Central Asian countries, for the period of 1995-2014. The results of the panel fixed effect regression show that per capita GDP are influenced by sulfur dioxide emission, population growth, and per capita food production variability, while energy and trade openness significantly increases per capita income of the region. The results of the panel Seemingly Unrelated Regression (SUR) show that carbon dioxide emission significantly decreases the share of agriculture and industry in GDP, while it further supports the share of services sector to GDP. Both the sulfur dioxide and mono-nitrogen oxide emission decreases the share of services in GDP; nitrous oxide decreases the share of industry in GDP; while mono-nitrogen oxide supports the industrial activities. The following key growth-specific results has been obtained from the panel SUR estimation, i.e., (i) Both the food production per capita and trade openness significantly associated with the increasing share of agriculture, (ii) food production and energy use significantly increases the service sectors' productivity; (iii) food production decreases the industrial activities; (iv) trade openness decreases the share of services to GDP while it supports the industrial share to GDP; and finally, (v) energy demand decreases along with the increase agricultural share in the region. The results emphasize the need for an interactive environmental model that facilitates the process of sustainable development across the globe.
In this paper, we revisit the environmental Kuznets curve (EKC) hypothesis by using estimations that account for cross-sectional dependency (CSD) and asymmetry effect in 76 countries for the period 1971-2014. Our results lend moderate support to the EKC hypothesis. The country-specific results unfold that a total of 16 out of 76 countries support the EKC hypothesis using CCEMG estimator. Results from AMG reveal that the EKC hypothesis holds in 24 out of 76 countries. It is worth highlighting that 11 countries (Australia, China, Congo Dem. Rep., Costa Rica, Gabon, Hong Kong, India, Korea, Myanmar, Turkey, and Uruguay) exhibit an inverted U-shaped curve regardless of whether CCEMG or AMG is used. The asymmetry analysis using PMG is also able to support the EKC hypothesis. We conclude that the EKC hypothesis does not fit all countries. Policy implication and recommendation in designing appropriate energy and economic policies are provided.
The contemporary debate on globalization and gender equality has a strong impact on economic growth. The present study analyzes the impacts of globalization and gender parity on economic growth in the Organization of Islamic Cooperation (OIC) 47 member countries for the period (1991-2017), using System GMM panel data technique. The results of system GMM have also been empirically estimated by making two groups (viz., low-income and high-income OIC member countries from the World Bank data classification, 2019) to examine the robustness of globalization and gender parity on economic growth. The results reveal that there is a negative impact of globalization on economic growth in the overall sample of OIC countries. When estimated by decomposing low-income countries and high-income countries, globalization has a significantly positive impact on economic growth in the case of high-income OIC countries, whereas globalization slashes GDP in the case of low-income OIC countries. The study finds that there is a positive impact of gender parity (ratio of female to male labor force work participation) on economic growth. Moreover, foreign remittances, government expenditures, capital formation, and human capital are also becoming the causes of a significant increase in economic growth in OIC member countries.
It is well documented that carbon emissions can be reduced by replacing conventional energy resources with renewable energy resources; thereby, the role of green technology is essential as it protect natural environment. Given that, the United Nations' agenda of "green is clean" may be achievable by adoption of green technologies. The objective of the study is to examine the link between information and communication technology (ICT), economic growth, energy consumption, and carbon dioxide (CO2) emissions in the context of South Korean economy, by using a novel Morlet wavelet approach. The study applies continuous wavelet power spectrum, the wavelet coherency, and the partial and the multiple wavelet coherency to the year during 1973-2016. The outcomes reveal that the connections among the stated variables progress over frequency and time domain. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages. From the time-domain sight, the results display robust but not consistent associations among the considered variables. From an economic point sight, the wavelet method displays that ICT helps to reduce environmental degradation in a medium and long run in the South Korean economy. This emphasizes the significance of having organized strategies by the policymakers to cope up with 2 to 3 years of the occurrence of the huge environmental degradation in South Korea.
This research article aims to investigate the moderating role of financial development in Environmental Kuznets Curve (EKC) in the context of Malaysia for the period 1970-2016. As the time series variables are integrated of different order therefore, Auto-Regressive Distributed Lag (ARDL) model has been employed to estimate the long-run equilibrium relationship among the variables. The results indicate that EKC does exist for Malaysia and financial development has negative impact on carbon emission. Moreover, financial development is found to have significant moderating impact on income environment relation. More financial development brings early turning point of the EKC. The results recommend that financial development can be used as one of the policy measures to reduce the environmental cost of economic growth in Malaysia.
Every country intends to enhance national production by achieving sustainable development. The purpose of this study is to examine whether there exists any long-run association among environmental deterioration measured by territorial emissions in CO2, demographic factors (total population, population density, and urban population) and some other variables, namely, energy use, per capita income, energy intensity, and industrial value added for the 16 countries from the Middle East and North African (MENA) over 1990-2018. We implemented the generalized method of moments (GMM), fully modified ordinary least square (FMOLS), robust least square estimators, and panel Granger causality techniques for estimation. The empirical estimates reveal that there exists a long run cointegration among the series. Results also exhibit that energy use, per capita income, energy intensity, industrial value added, population density, total population, and urban population have positive effects on CO2 emissions. Furthermore, in each panel, there is bi-directional causality between population density and CO2 emissions, total population and CO2 emissions, and urban population and CO2 emissions. These findings suggest that the policymakers need not exclusively to focus on the transformation of rural labor from an agricultural-based model to urban regions with powerful, dominant industry and services sectors but also related to the changing of rural establishments into urban spaces is required. These changes in demographics involve changes in the demand for additional transportation services, food, shelter, clothing, and other necessities.
Matched MeSH terms: Economic Development/statistics & numerical data
As the negative repercussions of environmental devastation, such as global warming and climate change, become more apparent, environmental consciousness is growing across the world, forcing nations to take steps to mitigate the damage. Thus, the current study assesses the effect of green investments, institutional quality, and political stability on air quality in the G-20 countries for the period 2004-2020. The stationarity of the variables was examined with the Pesaran (J Appl Econ 22:265-312, 2007) CADF, the long-term relationship between the variables by Westerlund (Oxf Bull Econ Stat 69(6):709-748, 2007), the long-run relationship coefficients with the MMQR method proposed by Machado and Silva (Econ 213(1):145-173, 2019), and the causality relationship between the variables by Dumitrescu and Hurlin (Econ Model 29(4):1450-1460, 2012) panel causality. The study findings revealed that green finance investments, institutional quality and political stability increased the air quality, while total output and energy consumption decreased air quality. The panel causality reveals a unidirectional causality from green finance investments, total output, energy consumption and political stability to air quality, and a bidirectional causality between institutional quality and air quality. According to these findings, it has been found that in the long term, green finance investments, total output, energy consumption, political stability, and institutional quality affect air quality. Based on these results, policies implications were proposed.
This study employs dynamic panel data for 34 Sub Saharan Africa (SSA) countries for the period 1984-2016 to estimate the effects of renewable energy on environmental quality measured by three indicators, namely, per capita CO2 emissions, energy intensity (EI) and Aggregate National Savings (ANS). The study leveraged a battery of second-generation econometric tests and estimation and causality methods to obtain the coefficients between the regressed and the regressors. Results reveal that use of renewable energy reduces CO2 emissions and energy intensity while it enhances ANS. Economic growth still seems to be expensive for the region as it stimulates CO2 emissions. However, it has a positive effect on ANS. As expected, fossil fuels exacerbate CO2 emissions and energy intensity. FDI is found to be detrimental for the environment of SSA region with its positive significant coefficient on CO2 emissions. Financial development is reported to reduce CO2 emissions. Some causal links between variables are also noted.
The purpose of this study was to examine the impact of aging on economic growth. The study used dynamic growth model and employed Autoregressive Distributed Lag (ARDL) approach for the period of 1980 to 2011. Three proxies for aging are used namely fertility rate, life expectancy and old dependency ratio. However, only fertility rate is detected to have a long run cointegration. The major finding of this study showed that a reduction of fertility rate lead to higher economic growth. This implied that even though Malaysia will face aging society by 2020, the economic growth is still stable and can increase by investing more on human capital.