Effects of Increased Renewable Energy Consumption on Electricity Prices: Evidence for Six South American Countries

This research examines the relationship between renewable energy consumption and electricity prices in six South American countries (Argentina, Bolivia, Colombia, Chile, Ecuador and Peru). The methodology used is a panel econometric model with annual data for the period 1990–2015. The results show that the consumption of renewable energies influences the price of electricity paid by households, although its influence is very moderate. On the other hand, it was observed that the consumption of renewable energies has no relationship with the energy prices of the industrial sector and the commercial and services sector. In the countries analyzed, an increase in GDP causes an increase in the price of energy in the industrial sector. With more CO2 emissions and a rise in the international price of oil, the annual average price of the industrial sector decreases.

Evaluating the impact of energy and environment on economic growth in BRI countries

This study investigates the impact of renewable energy consumption (REC), nonrenewable energy consumption (NREC), and carbon emissions on economic growth in 133 Belt and Road Initiative (BRI) countries from 1996 to 2020. We divided our sample into four income groups. For empirical estimation, this study employs panel quantile regression (PQR), and fully modified ordinary least squares (FMOLS) estimation techniques. The results confirm that REC have a positive impact on economic growth and NREC has a negative impact on economic growth. A 1% increase in REC and carbon emissions results in an increase in economic growth of 0.108% and 1.085%, respectively. A 1% increase in NREC reduces economic growth by 0.263% in the full sample countries. There are regional differences, although NREC has a positive impact on economic growth in all income groups in the long run. These novel empirical findings will help policymakers design energy policies to fulfill the target of economic growth in BRI countries.

Exploring the Effects of Economic Complexity and the Transition to a Clean Energy Pattern on Ecological Footprint From the Indian Perspective

The study explores the association between economic complexity, globalization, renewable and non-renewable energy consumption on the ecological footprint in the case of India from 1990–2018. The autoregressive distributed lag (ARDL) is applied to measure the long-run elasticity, while the vector error correction model (VECM) is applied to classify the causal path. The empirical findings demonstrate that economic complexity, globalization process, and renewable energy consumption play a dominant role in minimizing environmental degradation. In contrast, economic growth and non-renewable energy consumption are more responsible for increasing the pollution level in both the short and long run. Furthermore, the VECM outcomes disclose that there is long-run causality between ecological footprint and economic complexity. Moreover, the empirical outcomes are robust to various robustness checks performed for analysis to the consistency of our main results. The Indian government/policymakers should encourage a more environmentally friendly production process and eco-friendly technologies in exports to minimize environmental degradation.

Investigation of The Driving Factors of Ecological Footprint in Malaysia

Malaysia’s growing trends in energy production related emissions throw doubt on the country's possibility of meeting the Paris Climate Change Agreement and SDG obligations. Taking into account Malaysia’s current growth pattern and climatic circumstances, this study evaluates the association between ecological footprint and its potential determinants: economic growth, oil consumption, renewable energy and domestic capital investment for the period between 1965 and 2017. The stationary nature of the parameters is investigated using the conventional unit root approach (ADF and PP unit root) and structural break unit root (ZA unit root). The bounds approach in combination with the critical approximation p-values of Kripfganz and Schneider (2018) established a cointegration association between the observed parameters. The ARDL approach uncovered that economic growth and oil consumption contribute to ecological footprint. Furthermore, renewable energy consumption and gross capital formation reduce the ecological footprint. The FMOLS and DOLS estimators were applied as the sensitivity analysis of the ARDL estimators. Furthermore, the spectral BC causality approach was also utilized to investigate the causal association between ecological footprint and its determinants.

Econometric Assessment of Institutional Quality in Mitigating Global Climate-Change Risk

Background: Environmental deterioration is the alarming situation that results from rapid urbanization and development. The rising temperature and climate volatility are accounted for by the massive carbon dioxide (CO2) emissions. The research on climate-change mitigation is trying to curtail the situations before they become irreversible and unmanageable. This study explores the role of institutions in mitigating climate change by moderating the impact of environmental quality on climate change risk. Methodology: Global data sets have been collected from world big data depositories like the World Economic Forum (WEF), the World Development Indicators (WDI), and the International Country Risk Guide (ICRG). Countries that are listed in WEF were used as the sample of the study. An analysis was based on 114 countries that are based on the availability of data. For estimation, descriptive statistics, correlation analysis, change effects, and a Panel Feasible Generalized Least Squares (FGLS) model were used for estimating the results. Results: The global assessment indicates that CO2 emissions increase the climate risk, but its impact can be reduced by increasing the quality of institutions. Additionally, an increase in renewable energy consumption and economic growth reduces the climate risk. Implications: It is an instrumental study that empirically investigated the role of institutions in reducing climate risk by moderating CO2 emissions. The results of this study will help policymakers to formulate policies regarding environmental protection.