Investigating the unparalleled effects of economic growth and high-quality economic development on energy insecurity in China: A provincial perspective.

China has changed its focus from traditional high-speed economic growth to high-quality economic development (HQED) and the implementation of environmentally friendly practices. This transition can have parallel or unparallel impacts on energy insecurity (EIS). In this regards, HQED, inter Alia, is crucial in mitigating EIS and combating the energy crisis. Our study explores the impact of economic growth (EG) and HQED on EIS using the provincial panel data of China for the period 2011-2017. From the perspective of comparative analysis, the results reveal that HQED reduces EIS while EG increases it. The robustness checks indicate that industrial structure (IS) has a negative impact on EIS, whereas industrial structure upgrading (ISU) and green innovation (GI) have a positive influence. This implies that IS contributes to an increase in EIS, whereas ISU and GI result in a decrease in EIS. In addition, the analysis reveals that digital financial inclusion (DFI) exhibits a significant positive relation with EIS, albeit occasionally a negative but insignificant link. The policy implication is that the government should stimulate policies to promote HQED which reduces the EIS.

The role of eco-innovation, renewable energy consumption, economic risks, globalization, and economic growth in achieving sustainable environment in emerging market economies.

In the last two decades, environmental degradation has been a topic of concern. The rising level of CO2 emissions (CO2E) has adversely affected life in the E7 countries, which comprise of Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. The increased in CO2E is the cause of rising sea levels in the E7 countries. Visibly, E7 nations which are considered as the largest emitters of CO2 are facing the most severe environmental challenges. This study investigates the impact of eco-innovation, economic growth (EG), renewable energy consumption (REC), economic risk (ERI), and globalization on the CO2E, using the Feasible Generalized Lease Squares (FGLS) and Panel Corrected Standard Errors (PCSE) techniques for the period 1995 to 2018. The results indicate an inverted N-shaped relationship between eco-innovation and CO2E. Also, eco-innovation, REC, and economic risk are observed to be significant factors in abating CO2 emissions. On the contrary, globalization and GDP are responsible for rising CO2E in E7 countries. According to empirical estimates, eco-innovation improves the efficiency of carbon emissions, which lowers CO2E. In addition, because they are immune to changes in the price of oil and gas and disruptions brought about by geopolitical events, renewable energy sources can offer countries a more secure energy source than fossil fuels. Alternative energy sources can reasonably cut CO2E while offering a more reliable and secure energy source. Therefore, it is crucial that policies be put in place to cut CO2E by giving priority to environmental innovative policies.

Capital structure determinants across sectors: Comparison of observed evidences from the use of time series and panel data estimators.

This comparative study is an attempt to explore the determinants of capital structure for Malaysian firms listed in various sectors level. Within the framework of traditional and moderate dynamic capital structure theories, the key determinants such as fixed assets, current assets, return on equity, size, earning per share and total assets are tested in relation to the debt-equity ratio. The large-scale study entails data collected from 551 listed firms of Bursa Malaysia main market over 12 years period i.e. 2005-2016. Notably, this study combines Time Series econometrics with Panel Data analysis to enhance methodological robustness. Moreover, the comparative analysis approach is designated to recognize the most persistent capital structure determinants. In the first place, the Multiple Regression analysis (MRA) is selected as a baseline estimation method. Subsequently, the Auto Regression Distributed Lag model (ARDL), the Panel Data Static models, and Dynamic model via the Generalized Method of Moments (GMM) are employed to identify the capital structure determinants for the firms listed at Bursa Malaysia. The outcomes are surprising and indicate that the entire market is primarily controlled by the studied determinant total assets, which is significant in both construction and property sectors through MRA, ARDL, and GMM analysis. Technically, the significant role of tangibility and the existence of speed of adjustment across sectors imply that the Dynamic Capital Structure is the most prominent among all, followed by the Dynamic Trade-off theory.