In today's era, the world economy needs to move towards a green transformation. Green total factor productivity provides the judgment about a country or region's ability to achieve long-term sustainable development goals. However, many factors considerably affect green total factor productivity that needs to be explored and clarified. This panel study investigates the link between technological input, environmental policies, governmental involvement, manufacturing and logistics industry cooperation, renewable energy consumption, and green total factor productivity in the context of Chinese's manufacturing and logistics industry. Hypotheses are tested through fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) econometric technique. The study used 12 cities data mainly taken from China Urban Statistical Yearbook (2005-2019) and National Economic and Social Development Statistics Bulletin. The results indicate that technological input, environmental policies, governmental involvement, manufacturing and logistics industry cooperation, and renewable energy consumption are significantly linked to green total factor productivity. The result also implies that the factors mentioned above have a crucial role in the transformation process. Moreover, the current research results will help popularize green total factor productivity and provide a new starting point for reducing non-renewable energy consumption and environmental pollution.
This paper empirically examines the effects of energy, natural resources, agriculture, political constraint and regional integration on CO2 emissions in four ASEAN (Association of Southeast Asian Nations) countries of Cambodia, Malaysia, Indonesia and Thailand. We distinguish between renewable and fossil fuel energy consumption to see their individual impacts on CO2 emissions. The study employed a panel data from 1990 to 2019 derived from sources such as World Development Indicators, which were then analysed using Common-Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimates. The findings show that renewable energy consumption has a negative impact on CO2 emissions while fossil fuel energy degrades the environment. The role of natural resources was found to be favourable for environmental quality with the impact of agriculture being found to be detrimental. For regional trade integration, its influence was not significant enough to offset CO2 emission. Furthermore, we discovered that political constraint induces CO2 emission. Based on the result, it is recommended that the selected ASEAN countries promote the use of renewable energy and clean technologies in their manufacturing processes, conserve natural resources, adopt eco-friendly political policies and intensify regional integration to accelerate the achievement of the SDGs.
The ecological footprint has currently become a highly popular environmental performance indicator. It provides the basis for setting goals, identifying options for action, and tracking progress toward stated goals. Because the examination of the existence of convergence is important for the climate change protection of the earth, the convergence of ecological footprint and its subcomponents are a major concern for scholars and policymakers. To this end, this study aims to investigate the stochastic convergence of ecological footprint and its subcomponents. We employ the recently developed Hepsag (2021) unit root test that allows nonlinearity and smooth structural change simultaneously to study stochastic convergence in per-capita ecological footprint over the period 1961-2018 for the most polluting countries. The results provide mixed evidence of the presence of stochastic convergence in conventional unit root tests such as ADF, KPSS and Fourier KPSS. According to the Hepsag (2021) unit root test results for all countries, built-up land footprint converges except Australia, Malaysia, Poland, and Turkey. Carbon footprint converges for Indonesia, Malaysia, Mexico, South Africa, Thailand, Turkey, the UK, and the USA. Cropland footprint converges for Australia, Canada, China, France, Indonesia, Italy, Japan, Korea, Malaysia, Mexico, Poland, South Africa, the UK, and Vietnam. Fishing grounds footprint converges in Brazil, France, Germany, Indonesia, Italy, Mexico, South Africa, and Vietnam. Forest product footprint converges in Australia, Canada, France, Germany, India, Korea, Mexico, Poland, Turkey, and Vietnam. Grazing land footprint converges in Canada, France, India, Indonesia, Japan, Korea, Poland, South Africa, Thailand, and Vietnam. And lastly, the total ecological footprint converges in Canada, France, Korea, Malaysia, Mexico, South Africa, the UK, and the USA.
Attaining Sustainable Development Goals (SDGs) is important to control the adverse impacts of climate change and achieve sustainable development. Among the 17 SDGs, target 13 emphasizes enhancing urgent actions to combat climate-related changes. This target is also dependent on target 7, which advocates enhancing access to cheap alternative sustainable energy. To accomplish these targets, it is vital to curb the transport CO2 emissions (TCO2) which increased by approximately 80% from 1990 to 2019. Thus, this study assesses the role of transport renewable energy consumption (TRN) in TCO2 by taking into consideration transport fossil fuel consumption (TTF) and road infrastructure (RF) from 1970 to 2019 for the United States (US) with the intention to suggest some suitable mitigation policies. Also, this study assessed the presence of transport environmental Kuznets curve (EKC) to assess the direction of transport-induced growth. The study used the Bayer-Hanck cointegration test which utilizes four different cointegration techniques to decide cointegration along with the Gradual Shift causality test which considers structural shift and fractional integration in time series data. The long-run findings of the Dynamic Ordinary Least Squares (DOLS) test, which counters endogeneity and serial correlation, revealed that the transport renewable energy use mitigates as well as Granger causes TCO2. However, transport fossil fuel usage and road infrastructure enhance TCO2. Surprisingly, the transport EKC is invalid in the case of the US, and increased growth levels are harmful to the environment. The association between TCO2 and economic growth is similar to a U-shaped curve. The Spectral Causality test revealed the growth hypothesis regarding transport fossil fuel use and economic growth connection, which suggests that policymakers should be cautious while decreasing the usage of transport fossil fuels because it may hamper economic progress. These findings call for revisiting growth strategies and increasing green energy utilization in the transport sector to mitigate transport emissions.
We employ the new Method of Moments Quantile Regression approach to expose the role of natural resources, renewable energy, and globalization in testing Environment Kuznets Curve (EKC) in MINT panel covering the years 1995-2018. The outcome validates the EKC curve between economic progress and carbon emissions from the third quantile to the extreme highest quantile. The result also shows that natural resources increase CO2 emissions at the lowest quantile and then turn insignificant from the middle to the highest quantiles due to the potential utilization of resources in a sustainable manner. The renewable energy mitigates CO2 emissions at the lower half quantiles. Still, for upper quantiles, the results are unexpected and imply that the countries' total energy mix depends heavily on fossil fuels. As far as globalization is concerned, the significant results from medium to upper quantiles reveal that as globalization heightens due to foreign direct investment or trade, energy consumption also expands, leading to the worst environment quality. Thus, the present study's consequences deliver guidelines for policymakers to utilize natural resources sustainably and opt technologies based on clean energy, which may offset environmental degeneration.
Green finance can promote economic transformation and technological innovation and play a key role in solving the ecological environment and energy crisis. This paper constructs a comprehensive ecological livable environment evaluation system based on the provincial panel data in China from 2011 to 2019. At the same time, the panel mediation effect and spatial econometric model are used to test the impact of green finance on the ecological and livable environment. The main research conclusions include the following: (1) green finance has significantly improved China's ecological and livable environment; (2) green finance improves the ecological and livable environment by improving the level of technological innovation; (3) the impact of green finance on the ecological livable environment has regional heterogeneity, and green finance in the central provinces has a better effect on the improvement of the ecological livable environment; and (4) the ecological livable environment among Chinese provinces has a significant positive spatial correlation. Among them, green finance has significantly improved the local ecological livable environment but reduced the ecological livable environment of surrounding provinces. Based on the above conclusions, this paper suggests that the government should pay more attention to green finance and technological innovation and coordinate the development of the ecological livable environment among provinces. The research results provide empirical evidence for better developing green finance and improving the ecological livable environment and also provide certain theoretical guidance for China's coordinated regional development and high-quality economic development.
Global economies have recently been concerned about sustainable environmental management by reducing emissions and tackling ecological footprints. The rapid economic expansion and investment in traditional manufacturing further raises environmental degradation. China surpasses other emerging economies in the economic growth race yet has remained the top pollution-emitting economy for the last few decades, necessitating scholarly attention. This study examines the influencing factors of ecological footprints in China from the perspective of COP27. Using the extended dataset from 1988 to 2021, this study uses several time series diagnostic tests and verifies the existence of the long-run association between the study variables. Consequently, the non-linear scattered data leads to non-parametric (method of moment quantile regression) adoption. The empirical results indicate that only economic growth is a significant factor in environmental quality degradation in China. However, improving renewable energy usage, research and development, and foreign direct investment reduces the country's ecological footprint. Hence, the latter variables substantially lead to environmental sustainability. The robustness of the results is confirmed via a robust non-parametric estimator and causality test. Based on the empirical results, this study recommends increased investment in research and development, renewable production, and foreign direct investment enhancement.
Maintaining a stable exchange rate is a challenging task for the world, especially for developing economies. This study examines the impact of asymmetric exchange rates on trade flows in selected Asian countries and finds that the effects of increased exchange rate volatility on exports and imports differ among Pakistan, Malaysia, Japan, and Korea. The quarterly data from the period 1980 to 2018 is collected from the International Financial Statistics (IFS) database maintained by the International Monetary Fund (IMF). We employ both linear and non-linear Autoregressive Distributed Lag (ARDL) models for estimation. The non-linear models yielded more significant findings, while the linear models did not indicate any significant effects of exchange rate volatility on trade flows. The results of the study suggest that in the case of Pakistan, both the linear and non-linear models indicate that increased exchange rate volatility adversely affects exports and imports, while decreased volatility enhances both. This implies that stabilizing the exchange rate would be beneficial for Pakistan's trade. In contrast, the linear model applied to Malaysia shows no long-run effects of exchange rate volatility on exports. However, the result suggests that decreased volatility stimulates Malaysia's exports. Therefore, in the case of Malaysia, stabilizing the exchange rate could contribute to boosting exports. We also found that increased exchange rate volatility boosts exports of Japan. On the other hand, decreased volatility hurts exports of Japan. As for the long-run effects of exchange rate volatility on imports, we found that increased volatility boosts imports of Korea. The study provides various policy implications regarding the impact of exchange rate volatility on trade flows in developing economies. The study highlights the importance of country-specific considerations in understanding the impact of exchange rate volatility on trade flows, and has important policy implications for promoting trade and economic growth in these nations. It emphasizes the need to model exchange rate volatility separately for developed and developing countries and to continue research and analysis to identify ways to mitigate its negative effects on the economy.
The energy profile of India is dominated by fossil fuels, which create concerns over resource and environmental sustainability as fossil fuels are non-renewable and high carbon emitting. This scenario has necessitated the call for more renewables to replace fossil fuels to address resource and environmental sustainability concerns. This study, therefore, investigates the possibility of switching the fossil fuels of oil, coal, and natural gas for renewable energy in India. Using annual Indian data spanning more than four decades, a transcendental logarithmic production function based on a second-order Taylor Series approximation is estimated with the ridge regression technique. To achieve robustness, two equations with gross domestic product and adjusted net savings as regressands are estimated to proxy economic growth and sustainable development, respectively. The empirical results show substantial substitution possibilities between the fuels for both gross domestic product and adjusted net savings equations. The empirical findings show that India has the capacity to satisfy its energy needs through renewables to pursue not only economic growth but sustainable development. To actualize this potential, the Indian government should promote investment in renewables as this also promotes economic growth and development.
Extensive theoretical and empirical evidence supports the crucial role of savings in driving a nation's economic growth and development. However, previous studies have not considered their potential environmental implications. This study aims to explore the influence of savings and remittances on the Developing-8 countries (D-8) from 1989 to 2019, using the panel autoregressive distributed (ARDL) model. The findings reveal that national savings and remittances, in the long run, help mitigate environmental degradation in the D-8 countries but energy use and population growth stimulate carbon dioxide (CO2) emissions. In contrast, economic growth does not significantly affect these countries' environmental quality in the long run. However, none of the explanatory variables have any significant relationship with CO2 emissions in the short run. Therefore, policymakers in the D-8 countries are strongly encouraged to prioritize the enhancement of national savings across the three economic agents to maximize the positive effects of savings on environmental quality. Government savings can be increased by reducing deficits and borrowings, while corporate savings can be encouraged by implementing investment tax credits and promoting research and development. Additionally, governments can embark on public enlightenment campaigns on financial education and provide incentives to encourage household savings.
China Overseas Economic and Trade Cooperation Zone (COCZs) which as a platform for China's foreign investment and trade has a potential impact on CO2 emissions, while strengthening bilateral investment and trade between China and the host countries. Since most of the COCZs are located in countries along the "Belt and Road," the purpose of this paper is to investigate the impact of COCZs on CO2 emissions of the countries along the "Belt and Road" and the mechanism of this impact. We constructed a panel data of 63 countries along the "Belt and Road" from 2000 to 2020, and conducted an empirical study using the difference-in-difference (DID) model. Our research result show that COCZs can significantly increase the CO2 emissions of the countries along the "Belt and Road." Then, we conduct a series of robustness tests and endogeneity test on the estimation results of the baseline model, and the results of the tests all support the conclusion reached by the baseline model. Our heterogeneity analysis reveals that the effect of COCZs on CO2 emissions is more significant in Asian countries with lower national income or industrialization and higher country risk. Finally, we analyzed industrial value added and energy depletion as possible impact mechanisms, the results of mechanism model shows that COCZs can increase the industrial value added and then significantly increase CO2 emissions, but energy depletion was not an efficient mechanism. Our paper provides a new insight into the impact of bilateral economic and trade cooperation zones on CO2 emissions in host countries.
This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994-2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which affect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.
This paper empirically analyses the impact of gender disparity in access to education and under 5 mortality on economic growth in selected sub-Saharan African (SSA) countries from the period 2005 - 2020. The study engaged a panel data of 17 selected SSA countries sourced from the World Development Indicators (WDI) and the United Nations Institute for Statistics (UNIS) and applied the instrumental variable generalised method of moments analytical approach. The result shows that the interaction between gender parity in access to education and primary school enrolment has a significant impact on economic growth. The study concludes that policies to promote gender parity in access to education would be of paramount importance to increase economic growth towards the actualisation of sustainable development goal related to inclusive and equitable quality education and the promotion of lifelong learning opportunities (SDG4) in SSA countries.
Over the past decade, financial development has been a prominent debate for stakeholders and policymakers alike. Financial development are prerequisites for innovation and CO2 emissions, followed by the Paris Climate Summit (COP21). In the wake of the global economic recession, financial development continues to address CO2 emissions efforts. However, scant attention is paid to the role of financial development in innovation and CO2 emissions relationship, especially in the context of developing countries. The current study explores the relationship between innovation and CO2 emissions through moderating role of financial development, especially in the context of developing countries. Utilizing a dynamic panel threshold approach, the current study utilizes data from 26 countries between 1990 and 2014. Our findings reveal that innovation positively impacts the reduction of carbon emissions when the stock market value-to-private credit ratio is below 1.71, while an opposite effect is observed when the ratio exceeds this threshold. We believe that the findings broaden the debate on financial development in developing countries. The results revealed that developing countries should allocate their domestic resources to financial development and poverty reduction, rather than solely addressing environmental concerns. In addition, a more sustainable balance between innovation and CO2 emissions could benefit through financial development and the impact may be the result in terms of achieving sustainable development.
Foreign direct investment (FDI) can boost economic growth and provide job opportunities. FDI inflows in ASEAN+3 countries have dropped markedly, which may affect economic development in the region. Many previous studies have investigated a multitude of factors that can influence FDI, such as market size, inflation, trade openness, corruption, and inflation. Previous studies did not, however, consider environmental degradation as a potential factor. Besides corruption and inflation, imposing stringent environmental regulations, such as carbon pricing and taxes to reduce environmental degradation, might deter foreign investors from the country. This is due to heightened costs for foreign investors, which may cause FDI inflows to drop. To shed some light on the reality of this situation, this study examines whether environmental degradation can significantly affect foreign direct investment in the region. This study includes environmental degradation as a potential factor and employs the panel ARDL approach to analyse data from 1995 to 2019. Results show that environmental degradation, infrastructure, and corruption can affect the inflow of FDI in the long run. In the short run, inflation can affect FDI. The findings of this study can be utilized by policymakers in formulating the right policies to attract more investors. An increase in infrastructure facilities should be considered to attract more foreign investment. It is also vital for governments to reduce corruption and inflation to attract more FDI inflows. Environmental incentives should also be introduced to ensure that attempts to reduce environmental degradation do not affect FDI inflows.
Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.
INTRODUCTION: Biomedical research has traditionally been the domain of developed countries. We aim to study the effects of the increased focus on biomedical and medical research on level 1-4 publications in several industrialised and newly industrialised countries endowed with petroleum and gas resources.
METHODS: We identified all level 1-4 publications from 01/01/1994 to 31/12/2013 via PubMed using advanced options. The population and GDP (current US$) data from 1994-2013 were obtained through data provided by the World Bank and the raw data was normalised based on these two indicators.
RESULTS: From 1994-2013, Saudi Arabia and Malaysia were responsible for the highest absolute number of level 1 to 4 biomedical and medical research publications with 2551 and 1951 publications respectively. When normalised to population, Kuwait and Qatar had the highest publication rates, with 7.84 and 3.99 publications per 100,000 inhabitants respectively in a five yearly average. Kuwait produced the largest number of publications per billion (current US$) of GDP, at 2.92 publications, followed by Malaysia at 2.82 publications in a five yearly average.
CONCLUSION: The population size of a country as well as GDP can influence the number of level 1-4 publications in some countries. More importantly, effective government policy which stimulates research as well as a culture which actively promotes research as shown by Malaysia have proven to have a larger influence on the amount of level 1-4 biomedical and medical publications.
Given the economic growth and energy consumption patterns, most countries are striving to solve the problems of CO2 emissions reduction to achieve sustainable development. This paper employs an improved DEA model to measure energy and environmental efficiency for some selected countries in central and western Europe. In addition, the DEA window evaluation technique is applied to measure cross-sectional efficiency using two inputs (energy consumption, labor force), a desirable output (gross domestic product), and an undesirable output (CO2 emission) for the period from 2010 to 2014. The study finds that the UK ranks the highest position in term of energy and environmental efficiency. This shows that the UK has more effective policies regarding energy efficiency, consumption, production, import and energy intensity measures for sustainable economic growth as well as environmental protection. Ireland is the second-best country after the United Kingdom. The efficiency scores of the two countries are 0.99 and 0.89 respectively. On the empirical outcomes, this study suggests effective reforms in energy sector for countries with less energy efficiency that are still facing the problem of environmental degradation.
Greenhouse gasses have adverse effects on global warming and air pollution and need to be optimized by minimizing the contributing factors. This work analyzes the effects of economic growth and energy resources (renewable and nonrenewable) on the emissions of greenhouse gasses (GHG). A 2000-2016 panel data from 25 developing Asian countries is analyzed through a robust Random Effect (RE) approach and Hausman Taylor Regression (HTR). Findings show a positive correlation between economic growth and energy consumption, while a 1% increase in renewable energy consumption results in a 0.193% decrease in carbon emissions. Economic growth and renewable energy are positively correlated in both the short and long term, which implies a valid feedback hypothesis. The findings indicate the significant contribution of nonrenewable energy resources to greenhouse gas emissions and the positive impact of renewable resources on greenhouse gas emissions' control. Furthermore, this study highlights the potential of developing Asian economies to preserve the environment through more robust regional environmental policies and renewable energy resources. In light of this study's findings, policymakers in Asian developing economies should develop policies on Renewable Energy infrastructure (RE) to improve GDP and reduce greenhouse gas emissions.
The triple components of energy consumption, carbon dioxide emissions, and economic expansion are important to achieving sustained economic activity and sound ecological advancement. This study aims to estimate the impact of wide-ranging parameters on environmental circumstances in South Asian countries. This analysis required two approaches: 1)quantile autoregressive distributed lag (QARDL) as an econometric model, and 2) data envelopment analysis (DEA) non-parametric comparable composite index to examine concurrently South Asian nations' data for the 2000-2018 period. The underscored category of the parameters were grouped into four key indices, namely financial, fiscal, human, and energy. The DEA's mathematical composite findings reveal varied circumstances regarding environmental self-maintenance in South Asian nations. India and Pakistan are doing quite well; Afghanistan is abysmal. In addition, the QARDL approach findings reveal that energy use and fiscal indicators abate pollution. Furthermore, the correlation between fiscal decentralization and ecological attributes is strengthened by the excellent level of institutions and human capital progress. There is a unidirectional impact emanating from fiscal devolution, gross domestic product, human capital, eco-innovation, and institutional excellence on carbon dioxide pollution, although different from the other correlations obtained.