Search

The objective of this paper is to examine, for a panel of seven countries from the European Union, spanning the period 1986-2015, whether the use of renewable energy impacts their output elasticities of capital and labor and, thereby, influences the factor shares. By applying a set of models from threshold analysis, the analysis detects-for the first time-the presence of thresholds in the use of renewable energy with nontrivial consequences; notably, once the thresholds are crossed, the output elasticity of capital declines, while the output elasticity of labor rises. These changes in the elasticities indicate substantial changes in factor shares triggered by the identified threshold level of renewable energy consumption. This paper also finds changes in output elasticities of factors of production for other threshold variables including energy production from oil and gas or coal. These findings portray a complex and non-linear relationship between energy sources (e.g., renewables and non-renewables) vis-à-vis the economic growth level (e.g., GDP), with far-reaching consequences for factor shares from using renewables vis-à-vis non-renewables. Accordingly, it can be assumed that the changes in factor shares can, in turn, shape the incentives for the adoption of renewables within the selected European nations. Hence, future economic policies should emphasize the augmentation of renewable energy in the national energy system in order to sustain the rate of economic growth.

This study aims to provide a new perspective on environmental studies by examining the influence of environmental-related technological innovation, foreign direct investment, renewable energy consumption, and economic growth on the climate change index (CCI), a novel proxy for environmental quality indicators. From the econometric standpoint, this study employs the "non-linear autoregressive distributed lag" model and spectral causality over the period of 1999-2018 for India. The results show that positive shocks to economic growth have detrimental long- and short-term effects on environmental quality, whereas negative shocks have no effect. While a positive shock has an insignificant impact, a negative shock to environmental technology innovation has a long-term negative impact on environmental quality. This study provides evidence for the pollution halo hypothesis in India. Besides, a long-term negative shock to the usage of renewable energy fosters environmental degradation. Furthermore, in short-, medium-, and long-term frequency, spectral causality demonstrates unidirectional causation from CCI to environmental-related technological innovation. Bidirectional causation is demonstrated between the CCI and renewable energy consumption in the short and medium term. In addition, environmental-related technological innovation and foreign direct investment are demonstrating a bidirectional relationship in the short term. This study has advocated the Sustainable Development Goals (SDGs)-centric policy paradigm, which can assist the Indian government in achieving SDG-13 (mitigating climate change) and SDG-7 (clean energy consumption).

Irrespective of the vast array of empirical evaluations pertaining to the environmental Kuznets curve (EKC) hypothesis, both for India and other countries, previous studies, amid divergent submissions, inadvertently failed to highlight the relevant threshold that ensures significant reductions in environmental decay. Additionally, the implications of environmental-control technology on environmental quality are also lacking mostly in the context of Indian economy. Thus, this study enlists environmental-control technology and other relevant factors over the period 1980-2018 and employs the novel multiple threshold nonlinear ARDL technique, a model rarely applied in previous studies for updated empirical narratives. Accordingly, the empirical evidence rectifies that the variables converged to long-run equilibrium. Furthermore, from the tercile partial deviations, it is established that at the middle threshold (GDP

Empirical narratives pertaining to the implications of energy security (ENS) on environmental quality (EQ), particularly in the context of Emerging Seven (E7) countries, are currently understudied. Likewise, the influence of renewable energy (RWN), economic complexity (ECI) and environmental control technology (EVT) on EQ is still unsettled. Thus, based on arrays of pollution metrics (ecological footprint (ECF), carbon emission damage (CO2D) and consumption-based carbon emissions (CCO2) and annual panel series spanning 1990–2018, this study provides fresh insights into the implications of the listed variables on EQs in E7 countries. Accordingly, the following empirical narratives were established: (i) The effects of the enlisted panel series on EQ are sensitive to the peculiarities of each pollution metric. (ii) Estimates of the pool mean group autoregressive distributed lag (PMG-ARDL) model and those of cross-sectional augmented autoregressive distributed lag (CS-ARDL) underscore the important roles of ENS and RWN on EQ, particularly on ECF; and ECI on CO2D. While EVT provides insignificant carbon emission reducing effects across all variants of EQ indicators, population and economic growth are all time-significant pollution enablers. (iii) The outcomes of the panel quantile regression demonstrate that ENS enhances EQ only at the 25th and 50th quantiles and accelerates pollution at the 75th and 95th quantiles. RWN enhances EQ across all quantiles while ECI deaccelerates ECF and CO2D and accelerates CCO2across all quantiles. Furthermore, EVT accelerates ECF and CO2D while it deaccelerates CCO2across all quantiles. Meanwhile, the unpleasant effects of growth and population are reemphasized. Policy strategies to ensure a sustainable environment in E7 have been highlighted.

It has recently been underscored that access to energy has adverse impacts upon human development in South Asia. In this paper, we apply different variants of the autoregressive distributed lag (ARDL) model to explain how improved access to energy might adversely impact human development in India over 1980–2018. From the basic ARDL model, a 1% increase (decrease) in energy efficiency will increase (lower) human development by 6.1% in the long run. We note that the causality runs from energy efficiency to human development. The application of the novel dynamic ARDL simulations offers two insights; first, it confirms the importance of energy efficiency for driving human development. Secondly, it shows asymmetric effects: we find that a 10% increase in energy efficiency boosts human development from 7% to 12% in the long run, while a 10% decrease in energy efficiency lowers human development from 7% to 3%. Using the frequency domain causality analysis, we establish that energy efficiency drives human development in India. We also explore the symmetric and asymmetric impacts of several control variables on human development in India. Our findings establish that energy efficiency will not only help India reduce its environmental footprint but also propel human development.

Bangladesh has recently pledged at the 26th Conference of Parties (COP26) to reduce its carbon dioxide emission figures by 22% at the end of 2030. However, since this South Asian country has always turned to fossil fuels for electricity generation purposes, achieving this emission reduction goal is a challenging task for the Bangladesh government. Nevertheless, considering the negative environmental implications associated with the generation and consumption of unclean energy, particularly electricity, it is critically important for Bangladesh to expedite the process of clean transformation of its traditional pollution-intensive power system. Hence, the objective of this study is to dissect the repercussions of hydroelectricity use on Bangladesh’s fossil fuel consumption-related carbon dioxide As opposed to the traditional method of quantifying environmental quality using total carbon dioxide emissions, this study considers Bangladesh’s annual carbon dioxide emissions generated from the combustion of gas, oil, and coal. Besides, novel Fourier-based econometric methods that effectively handle structural break problems in data are utilized in this study. Based on the results, it is found that up-scaling hydroelectricity consumption levels exert emission-inhibiting effects while greater economic globalization activities are witnessed to boost the emissions. More importantly, hydroelectricity consumption and economic globalization are observed to jointly curb fossil fuel consumption-based emissions of carbon dioxide. Additionally, the results verify the environmental Kuznets curve hypothesis for Bangladesh. Furthermore, financial sector development is found to be effective in reducing the natural gas consumption-related carbon dioxide emissions while urbanization is held responsible for amplifying emissions generated from all three types of fossil fuels. Therefore, considering these findings, the Bangladesh government needs to particularly emphasize scaling up production and consumption of hydroelectricity to decarbonize its economy.

To promote women empowerment, enrichment in democratic governance is an essential requirement in any state or nation participation in political agenda and politics is essential in the development of good governance and democratic framework. In this regard, to increase the political participation of women, the most important institutions are the political parties. Political parties can influence women's political empowerment through Civil Society Organizations (CSOs) and international organisations. In India, women are still in a subordinate position in determining legislative and political priorities. In this backdrop, our study assesses the status of political participation that is playing a crucial role in achieving gender equality and women empowerment in West Bengal, India.