Impacts of renewable and disaggregated non-renewable energy consumption on CO2 emissions in GCC countries: A STIRPAT model analysis.

This research investigates the effects of renewable (REC) and disaggregated non-renewable energy consumption (coal, oil, and natural gas) on CO2 emissions (CO2) in GCC countries, employing the STIRPAT model. The research also compares the impact of various non-renewable energy (NREC) sources to identify their contributions to CO2 emissions. Demographic factors like population and economic growth are considered main determinants of CO2. Panel data econometric methods are used, including diagnostic tests and unit root tests, to found long-run relationships among the variables. The study reveals significant positive associations between coal, natural gas, oil consumption and CO2, with oil having the highest impact. Conversely, REC shows a significant negative correlation with CO2. Economic growth and population are also linked to increased CO2. The findings emphasize the need for strategies promoting renewable energy usage, energy efficiency, public transportation, carbon pricing, and research in green technologies to alleviate CO2 and enhance sustainable development in the GCC countries.

Investigating the crowding effect of FDI on domestic investments: Evidence from Bangladesh.

This study empirically investigates the crowding effect of Foreign Direct Investment (FDI) on domestic investments in Bangladesh, utilizing annual time series data from 1972 to 2022. Initially, unit root tests are conducted with and without considering structural breaks in the dataset. This study employs the Johansen test of cointegration to investigate the enduring association between the variables and utilizes the Vector Error Correction Model (VECM) to accommodate this relationship over the long term. Following the estimation of the VECM, formulas about the magnitude of the crowding effect (CE) are applied to examine the impact of FDI on domestic investment in Bangladesh. Results indicate that FDI positively influences domestic investments in both the short and long run.

Exploring the nexus between FDI inflows and economic growth: A sectoral level analysis.

This study investigates the relationship between Foreign Direct Investment (FDI) inflows and economic growth at sectoral levels in Bangladesh, employing a panel study framework. Utilizing sectoral-level panel data spanning six sectors from 2007-08 to 2018-19, the analysis is conducted using Panel Vector Error Correction Model (Panel VECM). Results from panel unit root tests confirm that all variables are integrated of order one I (1), indicating stationarity. The Pedroni panel co-integration test further supports the presence of co-integration among the variables. Notably, the Panel VECM reveals evidence of a unidirectional causal relationship from Real Gross Domestic Product (RGDP) to Real Foreign Direct Investment (RFDI) across all six sectors of Bangladesh. The findings underscore the significance of formulating pragmatic policies and implementing them effectively to attract FDI across sectors, thereby contributing to the overall economic growth of Bangladesh.

Relationship between greenfield investment and economic growth: Evidence from Bangladesh.

The key purpose of the study is to investigate the relationship between Greenfield investment and economic growth of Bangladesh using annual time series data during the period 2003-2020. The study employs Toda-Yamamoto (T-Y) tests of Granger causality method that performs Modified Wald Test (MWALD) in order to establish causal relation among different variables. There are three steps in implementing the T-Y procedure. The first step involves using different tests (ADF, PP, and KPSS test) to identify the maximum order of integration of the variable. The second step requires selecting the optimal lag length (p) based on several lag length selection criteria. In the third step, MWALD approach is used for testing the vector auto regression model for causality. The results of the tests (ADF, PP, and KPSS) concluded that the maximum order of integration of the variables is two. Then, the optimal lag length of two (p = 2) has been selected based on several lag length selection criteria. Finally, the findings reveal the evidence of unidirectional causality from Real Greenfield Foreign Direct Investment (RGFDI) to Real Gross Domestic Product (RGDP). The key contribution of this study is to investigate the Greenfield investments-growth relationship for a country like Bangladesh.

Green logistics and environment, economic growth in the context of the Belt and Road Initiative.

Infrastructure development has been a priority area since the Belt and Road Initiative (BRI) was proposed. This paper uses the generalized method of moments (GMM) to analyze the relationship between the green logistics, environment and economic growth based on panel data of countries along the BRI from 2007 to 2018. It is found that fossil fuels are the core of logistics operation activities, and the more fossil fuels are used, the more detrimental to the sustainable development of the environment. "The green logistics is negatively correlated with fossil fuel energy consumption and carbon emissions per capita in countries along the Belt and Road. At the same time, the green logistics can also bring more export opportunities for these countries and increase the national income per capita. The development of the green logistics is of great significance to the countries' environment and sustainable economic development along the Belt and Road.

Differential game model and coordination model for green supply chain based on green technology research and development.

The purpose of this paper is to establish a green supply chain differential game model for green technology research and development based on a secondary green supply chain composed of a single manufacturer and a single retailer. It compares the differential game equilibrium solutions under centralized and decentralized decision-making. The green supply chain members are coordinated through the dynamic wholesale price mechanism, and numerical simulation is used as a methodology, to verify and explain the results. The study found that compared to decentralized decision-making, the level of green technology and the total profit of green channels are higher under centralized decision-making. When the coordination parameters are within a certain range, the dynamic wholesale price mechanism can coordinate the behavior of manufacturers and retailers. The result also discovers that under the dynamic wholesale price mechanism, with the increase of investment cost coefficient, or the increase of price sensitivity or the decrease of consumer's environmental awareness, the green technology level, product green degree, price, retailer's profit, and the total profit of green channel is decreased. In contrast, the wholesale price and manufacturer's profits are increased.

Analysis of the causes of moral injury in the outbreak of 2019-nCoV.

The infection of the novel coronavirus that originated from Wuhan, China in December 2019 converted rapidly into a pandemic by March 11, 2020. Whereas the infection mortality rate is not completely understood, it seems to be significantly beyond that of other recent pandemics (e.g., H1N1 pandemic). This paper discusses moral injury in the context of disaster and epidemic and how easily the moral psychology of individuals and society can be shaken. Moral injury is a multiscientific concept involving psychology, culture, and religion. Amid the outbreak of the novel coronavirus pneumonia, immoral behaviors and events such as violence, injury, and illness have also caused different degrees of impact on the moral standards of individuals, confusing moral cognition, destroying moral emotion, and weakening moral toughness, resulting in varying degrees of moral injury. If there is no national health, there will be no positive society for all. Based on this, the public needs to pay close attention to the moral health of the whole people and effectively avoid the occurrence of moral injury. (PsycInfo Database Record (c) 2020 APA, all rights reserved).