ABSTRACTThis research examines the trends in environmental footprints through energy innovations, digital trade, economic freedom, and environmental regulation from the context of G7 economies. Quarterly observations from 1998-2020 have been utilized for the advanced-panel model entitled Method of Moments Quantile Regression (MMQR). The initial findings confirm slope heterogeneity, interdependence between the cross-sectional units, stationarity properties, and panel cointegration. The results through FM-OLS, D-OLS, and FE-OLS justify that energy innovations, digital trade, and environmental regulations control ecological damages. In contrast, economic freedom and growth are causing more damage to nature, like ecological footprints (EFP). Similarly, the results through MMQR confirm that the impact of energy innovations, digital trade, and environmental regulations is accepted as a panacea to control environmental degradation in G7. However, the magnitude of the coefficient varies across different quantiles. More specifically, the findings show that the impact of energy innovations is highly significant at 0.50th quantile. In contrast, through digital trade, the impact on EFP is only significant under medium and higher order quantiles (i.e. 0.50th, 0.75th-1.0th). Contrarily, economic freedom is causing more EFP across all the quantiles, where the findings are highly significant at 0.75th quantile. Besides, a few other policy implications are also discussed.
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.
This paper investigates the efficiency and total factor productivity (TFP) growth of the Pakistani banking industry and determines the impact of risk and competition on the efficiency and TFP growth. The data envelopment analysis (DEA)-based Malmquist productivity index is used to measure efficiency and TFP growth of the Pakistani banking industry. The generalized method of moments (GMM) model is applied to observe the impact of risk and competition on efficiency and TFP growth. The motivation behind the use of GMM model is its ability to overcome unobserved heterogeneity, autocorrelation, and endogeneity issues. The results of the study show that the credit and liquidity risks have positive while insolvency risk has negative effect on the efficiency and TFP growth. The competition leads to improve technological efficiency but declines the technical efficiency growth. Among other explanatory variables, operational cost management, banking sector development, GDP growth rate, and infrastructure development show significant relationships with various efficiencies and TFP growth. The banks also facilitate for the purchase of carbon-intensive products in order to reduce carbon emissions. Strong banking development successfully allocate their financial resources for the development of energy-efficient technology while banking sector development is found to be negatively related with environmental sustainability. The strong banking sector possesses a significant negative influence on carbon reduction and environmental degradation.
Recent research has shown a huge impact of non-renewable energy (NRE) production on environmental health. In this context, this work analyzes the effects of GDP growth and long- and short-term consumption of renewable and non-renewable energy (RE and NRE, respectively) on carbon emission in BRICS and OECD economies. The quantile autoregressive distributed lag (QARDL) model was employed on the panel data from 1980 to 2016. Findings suggest a negative GDP-carbon emission correlation and a positive NRE-carbon emission correlation in the considered economies. Furthermore, carbon emission decreases with increase in gross capital formation, whereas trade openness does not have any significant effect on carbon emission. It has been determined that the application of the error correction method (ECM) has less effect on energy consumption as compared to the past levels and changes in energy consumption. In the long-term, a positive correlation of carbon emission and energy consumption is observed, whereas limited short-term effects of energy consumption on carbon emission are observed. Therefore, an RE-based energy production approach is recommended in the selected region for the future projects.
The purpose of this research is to measure the combing impact of corporate social responsibility on company performance and to conduct a comparative analysis among local and foreign companies in this context. This research aims to conduct an empirical analysis about how corporate social responsibility contributes to company performance. The study utilizes AHP and fuzzy TOPSIS theory to conduct research. The results revealed that environmental corporate social responsibility has a vital role in the development of organizational reputation and employee commitment. It can be observed from the results that the weights of environmental CSR, corporate CSR, financial CSR, and social CSR are 0.30, 0.25, 0.24, and 0.21, respectively. The preference of these four criteria is environmental CSR > corporate CSR > financial CSR > social CSR. The corporate CSR criterion got the maximum weight of 0.30, whereas the social CSR criteria received the lowest weight of 0.21. The financial CSR get weights of criteria 0.25, and the commercial potential obtained 0.24 weights, while the financial CSR got the 2nd highest criteria weight of 0.25, and the social CSR get weights of criteria 0.21 lowest weighted. The research provides valuable information for decision-makers. The study provides a valuable information for policy makers.
This work aims to study the time-frequency relationship between the recent COVID-19 pandemic and instabilities in oil price and the stock market, geopolitical risks, and uncertainty in the economic policy in the USA, Europe, and China. The coherence wavelet method and the wavelet-based Granger causality tests are applied to the data (31st December 2019 to 1st August 2020) based on daily COVID-19 observations, oil prices, US-EPU, the US geopolitical risk index, and the US stock price index. The short- and long-term COVID-19 consequences are depicted differently and may initially be viewed as an economic crisis. The results illustrate the reduced industrial productivity, which intensifies with the increase in the pandemic's severeness (i.e., a 10.57% decrease in the productivity index with a 1% increase in the pandemic severeness). Similarly, indices for oil demand, stock market, GDP growth, and electricity demand decrease significantly with an increase in the pandemic severeness index (i.e., a 1% increase in the pandemic severeness results in a 0.9%, 0.67%, 1.12%, and 0.65% decrease, respectively). However, the oil market shows low co-movement with the stock exchange, exchange rate, and gold markets. Therefore, investors and the government are recommended to invest in the oil market to generate revenue during the sanctions period.