Energy availability, especially derived from renewable sources, has sustainable effects on economic progress and environmental rectifications. However, using clean energy in the energy mix has been influenced by several macro fundamentals. The motivation of this study is to gauge the impact of uncertainties, environmental restrictions, and innovation on clean energy consumption for the period 1997–2021 by employing the new econometrical estimation techniques commonly known as CUP-FM and CUP-BC. Referring to the preliminary assessment with the slope of homogeneity, cross-sectional dependency, and the panel cointegration test, it is unveiled that research variables have exposed heterogeneity prosperities, cross-sectional dependence, and long-run association in the empirical equation. According to the empirical model output with CUP-FM and CUP-BC, EPU has a native statistically significant connection to clean energy consumption. At the same time, environmental tax and technological innovation have found beneficial effects on clean energy development. Additionally, the nonlinear estimation disclosed an asymmetric linkage between explanatory and explained variables in the long and short-run. Directional causality revealed a feedback hypothesis explaining the relationship between EPU, TI, and clean energy consumption. This study has offered policy suggestions based on the findings for future development.

Charting a Sustainable Future: The Impact of Economic Policy, Environmental Tax, Innovation, and Natural Resources on Clean Energy Consumption

Does environmental degradation matter for poverty? Clarifying the nexus between FDI, environmental degradation, renewable energy, education, and poverty in Morocco and Tunisia

Energy availability especially that derived from renewable sources has sustainable effects on economic progress and environmental rectifications. However, using clean energy in the energy mix has been influenced by several macro fundamentals. The motivation of this study is to gauge the impact of uncertainties, environmental restrictions and innovation on clean energy consumption for the period 1997–2021 by employing the new econometric estimation techniques commonly known as CUP-FM and CUP-BC. Referring to the preliminary assessment with the slope of homogeneity, cross-sectional dependency and panel cointegration test, it is unveiled that research variables have exposed heterogeneity prosperities, cross-sectional dependence, and long-run association in the empirical equation. According to the empirical model output with CUP-FM and CUP-BC, EPU has a native statistically significant connection to clean energy consumption. At the same time, environmental taxation and technological innovation have had beneficial effects on clean energy development. Additionally, the nonlinear estimation disclosed asymmetric linkage between explanatory and explained variables in the long and short run. Directional causality revealed a feedback hypothesis explaining the relationship between EPU, TI and clean energy consumption. The study has offered policy suggestions based on the findings for future development. 

Charting a Sustainable Future: The Impact of Economic Policy, Environmental Taxation, Innovation, and Natural Resources on Clean Energy Consumption

This study explores the influence of Urbanization, Trade, Human Capital, FDI, Money on Poverty of developing countries. To capture this effect, panel data of 20 developing countries has been collected through World Development Indicators (WDI) from 2006 to 2022. For the purpose of analysis, Im, Pesaran and Shin W test – unit root test has been applied to check the stationary and to choose the appropriate technique i.e. Panel ARDL technique. The unit root test observes the mixed order of integration about the selected variables. Moreover, the results of ARDL conclude that poverty in selected developing countries is reduced by Trade openness, Foreign Direct Investment, Households Consumption Expenditure, Domestic Investment and Human Capital Index. On the other side, poverty is increased by Urbanization and Money supply in the longrun. Convergence from shortrun to longrun has also been found which is evident from cointegrating term. 
 

/pdf/exploring-the-influence-of-urbanization-trade-human-capital-2c9z3vrz.pdf

Exploring the Influence of Urbanization, Trade, Human Capital, FDI and Money on Poverty in case of Selected Developing Countries

Agricultural inputs have a significant catabatic effect on rural poverty at present. However, few studies have assessed whether agricultural inputs inhibit the intending probability of being vulnerable to rural poverty, referred to as poverty vulnerability. Poverty vulnerability studies, which focus on the likeli-hood of poverty among households in the future, have forward-looking and prognostic features in poverty research. Such research provides essential tools for describing mechanisms that can eradicate poverty. This study investigates the impact of agricultural inputs on rural poverty vulnerability and the mechanisms of action, using data from the 2015 China Household Finance Survey (CHFS). The empirical results show that agricultural inputs significantly suppress the probability of rural poverty vulnerability. The results hold after replacing the poverty criterion, poverty vulnerability criterion, and core explanatory variables. To overcome the endogeneity problem created by possible reverse cau-sality and omitted variables in the baseline model, this study uses the instrumental variables method to test endogeneity. The study also applies a treatment effects model and propensity score matching method to estimate and address any endogeneity problems due to explanatory variables. The findings also remain robust and significant after addressing the endogeneity problem. Further analyses indicate that the inhibitive effect of agricultural inputs on rural poverty vulnerability is mainly achieved through increased agricultural yields, improved physical health, and increased opportunities for entre-preneurial behavior. A heterogeneity analysis finds that the inhibitive effect of agricultural inputs on poverty vulnerability is more pronounced in Midwest China, in households with physically healthy household heads, and in families whose leaders have risk preferences. Our findings provide empirical evidence that can help inform forward-looking and prognostic policies for developing countries when formulating anti-poverty strategies. 

Unravelling the influence and mechanism of agricultural inputs on rural poverty vulnerability: Evidence from China

Drawing on three-wave panel data from China Family Panel Studies (CFPS) of 2014, 2016, and 2018, this paper measures rural households’ vulnerability to relative poverty using the three-stage feasible generalized least squares (FGLS) model. We analyze the impact of human capital on vulnerability to relative poverty by using the two-way fixed-effected model and panel quantile regression. Empirical results exhibited that labor force migration, health, education, and working experience all have a negative effect on vulnerability to relative poverty. Labor force migration has the greatest negative effect among the four factors. Heterogeneity analysis results exhibited that labor force migration has the biggest negative effect in the east region. Health and education have the greatest negative impact in the central region. Labor force migration, health, work experience, and education have a greater effect on nonpoor households than on poor households.

Human Capital and Rural Households’ Vulnerability to Relative Poverty: Evidence from China

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Human Capital and Rural Households’ Vulnerability to Relative Poverty: Evidence from China