Are economic growth and environmental pollution a dilemma?

Exploring the impact of renewable energy, green taxes and trade openness on carbon neutrality: New insights from BRICS countries

The world faces two significant challenges: promoting sustainable economic growth and reaching carbon neutrality. In BRICS countries, these challenges are shaped by renewable energy, green taxes, and trade openness. These countries were selected for their strategic location and the abundance of relevant data collected over the period of 1990-2021, providing a distinctive window into the energy and economic dynamics of the area. The link between renewable energy consumption, green taxes, trade openness, and natural resources and their effects on carbon emissions in BRICS countries is examined in this study using the Fully Modified Ordinary Least Square Method (FMOLS) estimator and the Drisc Kraay estimator for the robustness test. The findings indicate that using renewable energy and green taxes primarily contribute to reducing emissions, particularly at higher emissions levels. The study reveals that various factors, namely financial globalization, trade openness, efficient resource management, and population growth, substantially impact carbon neutrality. Population growth positively impacts carbon neutrality, while using renewable energy sources mitigates it. Furthermore, the empirical findings show a statistically significant positive association between financial globalization, efficient resource management, and carbon neutrality in BRICS nations. Therefore, it is necessary to implement an integrated ecological governance strategy to control and direct financial resources towards sustainable development and green energy.

Unraveling the environmental Kuznets curve: interplay between [Formula: see text] emissions, economic development, and energy consumption

The study investigates the complex interplay among [Formula: see text] emissions, energy consumption, and economic growth in China, employing the Environmental Kuznets Curve (EKC) framework to analyze the dynamics from 1990 to 2022. The research contributes to the urgent need for sustainable development by filling important gaps in comprehending China's specific challenges and potential and considering the relationship between economic advancement and environmental quality. This study utilizes advanced econometric tools, including the AutoRegressive Distributed Lag model, Vector Error Correction Model, and AutoRegressive Integrated Moving Average, to comprehensively examine the complicated relationship between variables, considering both short-run and long-run dynamics. The study supports the EKC concept, suggesting that targeted measures can reduce environmental degradation as China's economy advances. Strategic policy recommendations include emission reduction targets, investments in green technologies, and promoting sustainable consumption patterns. Furthermore, transitioning from fossil fuels to cleaner energy aligns with global climate objectives. This research provides valuable insights for policymakers, emphasizing the interconnected nature of energy consumption, [Formula: see text] emissions, and economic growth in shaping China's sustainable future.

Does the digital economy empower the green development of foreign trade?

The digital economy has become a new driving force for China's economic development in recent years, and it may contribute to solving the corresponding problems of resource and environmental pressure. Therefore, this study strives to explore whether the digital economy contributes to the green development of foreign trade. First, this study measures the digital economy development in China. Second, this study presents a list of environmental and polluting products and examines the impact of digital economy development on exports of representative products based on an extended gravity model. The main findings are as follows. First, the digital economy significantly promotes the green development of foreign trade. Second, the signing of Free Trade Agreements (FTAs) and the income level of importing countries and regions strengthen the role of the digital economy in promoting the green development of foreign trade. Third, the digital economy promotes the green development of foreign trade through green technological innovation. Finally, some policy implications are proposed based on the findings of this study.

Economic uncertainty and population health: insights from emerging markets and developing countries

This study employs a Bayesian panel vector autoregressive model to examine the impact of economic uncertainty on public health, using an annual, country-level panel dataset of 103 emerging markets and developing countries spanning the years 1995 through 2019. The results from the full sample suggest that the immediate effects of heightened economic uncertainty on health are marginal, yet it may engender prolonged life expectancy and lowered mortality rates. The analysis unveils considerable heterogeneities among various country classifications. The health-enhancing effects of economic uncertainty are predominantly discernible in emerging markets, low-income and upper-middle-income countries. Additionally, a diminution in suicide rates, attributed to escalated economic uncertainty, is uniquely detected in upper-middle-income countries. Furthermore, economic growth and healthcare expenditure emerge as paramount determinants in bolstering overall population health, particularly in lower-middle-income countries. The detrimental effect of environmental pollution on health is more pronounced in emerging markets and middle-income nations. Excluding high-income countries, it is essential to emphasize the beneficial health outcomes resulting from financial development and globalization, as well as the deleterious effects of environmental pollution. Lastly, several policy implications aligned with the findings are outlined, providing a roadmap for decision-makers in these diverse economies to promote better health outcomes.

The impacts of renewable energy and institutional quality in environmental sustainability in the context of the sustainable development goals: A novel approach with the inverted load capacity factor

It is crucial to fulfill sustainable development goals in combating environmental pollution. Recently, there has been a growing literature on environmental pollution; however, while many proxies represent environmental pollution, few proxies represent environmental sustainability. In this paper, we examine the effects of institutional quality (SDG-16), economic growth (SDG-8), and renewable energy (SDG-7) on the inverted load capacity factor (SDG-13) in OECD countries from 1999 to 2018. The objective is to ensure environmental sustainability within the Sustainable Development Goals (SDGs) framework. In this respect, the study differs from the existing literature by approaching the sustainable environment literature from a broader perspective. Long-term empirical estimates from the PMG-ARDL technique have shown that institutional quality, reel income, and population increase the inverted load capacity factor, that is, decrease environmental sustainability. However, on the contrary, renewable energy decreases the inverted load capacity factor. Therefore, renewable energy consumption helps reach SDG-7 and SDG-13 in OECD countries. In addition, it is found that economic growth is significant both in the long run and in the short run, and the impact of economic growth on the environment is greater in the short run than in the long run. This result supports the environmental Kuznets curve (EKC) hypothesis for OECD countries. The panel causality test results find a bidirectional causality relationship from renewable energy and population to inverted load capacity factor and a unidirectional causality relationship from institutional quality to inverted load capacity factor. This study argues that policymakers should concentrate on deploying environmentally friendly technology to slow down environmental degradation, increase the usage of renewable energy sources, and promote sustainable development in line with the SDGs.

The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA

This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.

The cost of aging: Economic growth perspectives for Europe

This study explores the causal relationship between the economy and the elderly population in 15 European countries. The economy was measured by the Per Capita Gross Domestic Product growth rate, while the population aged above 65 as a percentage of the total was considered the elderly population. The data were obtained from a time series dataset published by the World Bank for six decades from 1961 to 2021. The Granger causality test was employed in the study to analyse the impact between the economy and the elderly population. An alternate approach, wavelet coherence, was used to demonstrate the changes to the relationship between the two variables in Europe over the 60 years. The findings from the Granger causality test indicate a unidirectional Granger causality from the economy to the elderly population for Luxembourg, Austria, Denmark, Spain, and Sweden, while vice versa for Greece and the United Kingdom. Furthermore, for Belgium, Finland, France, Italy, Netherlands, Norway, Portugal, and Turkey, Granger causality does not exist between the said variables. Moreover, wavelet coherence analysis depicts that for Europe, the elderly population negatively affected the economic growth in the 1960s, and vice versa in the 1980s.

Renewable energy, economic freedom and economic policy uncertainty: New evidence from a dynamic panel threshold analysis for the G-7 and BRIC countries

This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.