Search

Given the alarming rate of climate change and environmental degradation, major countries are seeking ways to curtail environmental damage and attain sustainability in the future. In the quest for a green economy, countries are motivated to adopt renewable energy that can assist in resource conservation and efficiency. Accordingly, this study examines the diverse effects of the underground economy, environmental policy strictness, geopolitical risk, gross domestic product, carbon emissions, population, and oil prices on renewable energy for 30 high- and middle-income countries from 1990 to 2018. The empirical outcomes based on quantile regression document significant variations across two country groups. For instance, for high-income countries, the shadow economy has a detrimental effect across all quantiles but it is statistically significant at the top quantiles. Nonetheless, the effect of the shadow economy on renewable energy is detrimental and significant statistically across all quantiles for middle-income countries. In the context of environmental policy stringency, the effect is positive across both country groups, though there is heterogeneity in outcomes. Geopolitical risk has a positive influence on the deployment of renewable energy for high-income countries but negatively impacts renewables for middle-income countries. As far as policy suggestions are concerned, the policymakers of both high- and middle-income countries need to take steps to constrain the growth of the shadow economy by adopting effective policy strategies. Policies need to be implemented for middle income-countries to reduce the unfavorable effect of geopolitical uncertainty. The findings of this study contribute to a better and more precise understanding of factors shaping the role of renewables whereby the energy crisis would be mitigated. • Effect of shadow economy, environmental regulation, and geopolitical risk on renewable energy. • Empirical results are provided based on panel quantile approach. • Shadow economy hinders but environmental regulation encourages renewables. • Geopolitical risk promotes (dampens) renewable energy in high- (middle-) income countries. • Impacts are heterogeneous across the distribution of renewable energy development. [ABSTRACT FROM AUTHOR]

This research aims to explore the correlation between meteorological parameters and COVID-19 pandemic in New Jersey, United States. The authors employ extensive correlation analysis including Pearson correlation, Spearman correlation, Kendall's rank correlation and auto regressive distributed lag (ARDL) to check the effects of meteorological parameters on the COVID new cases of New Jersey. In doing so, PM 2.5, air quality index, temperature (°C), humidity (%), health security index, human development index, and population density are considered as crucial meteorological and non-meteorological factors. This research work used the maximum available data of all variables from 1st March to 7th July 2020. Among the weather indicators, temperature (°C) was found to have a negative correlation, while humidity and air quality highlighted a positive correlation with daily new cases of COVID-19 in New Jersey. The empirical findings illustrated that there is a strong positive association of lagged humidity, air quality, PM 2.5, and previous infections with daily new cases. Similarly, the ARDL findings suggest that air quality, humidity and infections have lagged effects with the COVID-19 spread across New Jersey. The empirical conclusions of this research might serve as a key input to mitigate the rapid spread of COVID-19 across the United States. • The study examines the effects of air pollutants on the COVID-19 spread in New Jersey. • Air quality and humidity significantly enhance new COVID-19 cases. • Air quality, humidity and COVID-19 has lagged effects with new infections. • Temperature may not be a significant determinant of COVID-19. [ABSTRACT FROM AUTHOR]

The nexus between economic growth and energy consumption has been exhaustively explored, yet the empirical evidence and the theoretical points of view remain at odds. This study contextualises and capitalises on this discrepancy and examines the connection between non-renewable and renewable energy consumption and economic growth, considering the moderating impact of economic complexity, trade openness, FDI and institutional quality. We use a panel quantile regression model and data from 32 European countries in the period 1995–2014. Our key results show that economic complexity, renewable energy consumption, trade openness, FDI and institutional quality enhance economic growth. The results for non-renewable energy consumption showed both a positive and a negative impact in different quantiles, indicating that the consumption of renewable energy is in fact more effective for economic growth than the use of non-renewables. Our findings have far-reaching implications for stakeholders and policymakers working on sustainable economic growth and energy policy with a view to meeting the commitments made under the Paris Agreement (COP21). • Economic complexity contributes to economic growth. • Trade openness, foreign direct investment and institutional quality enhance economic growth. • Renewable energy is more suitable for economic growth than non-renewable. • To honour Paris Agreement (COP21), renewable energy consumption should be encouraged. [ABSTRACT FROM AUTHOR]

This study contributes to the environment-growth nexus literature by examining corruption's effect on environmental quality in 17 Middle East and North Africa (MENA) countries between 1984 and 2018. We use four different indicators of environmental degradation (ecological footprint, carbon dioxide emissions, greenhouse gas emissions, and carbon emission intensity) to gain a comprehensive view of the relationship. This study's methodological value added is the application of the method of moments quantile regression, which enables us to account for different relationships between the independent variables and environmental quality at different levels of environmental degradation. The results indicate that corruption worsens environmental quality based on three of the four indicators of environmental degradation, while the impact appears to become less severe at higher levels of environmental deterioration. The results also indicate that traditional mean-based panel data estimation methods provide an incomplete picture of the factors behind environmental problems: The explanatory variables' impacts tend to vary at different levels of environmental quality, and the impact's sign can even change when moving from the lowest to the highest environmental degradation quantiles. Overall, the results highlight the importance of curbing corruption to enable enforcement of more stringent environmental regulations. [Display omitted] • The effect of corruption on environmental degradation is investigated. • We used the Method of Moment Quantile Estimations. • Corruption worsens environmental quality in the MENA region. • Corruption increases ecological footprint, GHG emission and carbon emission intensity. [ABSTRACT FROM AUTHOR]