This study examines the multidimensional impact of energy intensity (EI) and sectoral energy consumption on economic performance (EP). A sample of dataset includes European economies consisting of three decades from 1990 to 2020 is analyzed by employing several estimators and an inclusive estimation strategy for empirical robustness. This component of research is concerned with determining the trajectory of energy-growth relationships in order to explain changes in magnitude and intensity through time. This study is required in order to make an accurate comparison across time periods that how the change dimension is increasing or decreasing. Econometric practice is panel two step GMM. This study estimated by using GMM estimation and the results have been reported on the basis of probability values of F-statistics. The Kleibergen-Paap rk LM statistic with chi-square p-values of under-identification test are used to check the identification of the model. The chi-square probability values of Kleibergen-Paap rk LM statistics in all of the models of current study are highly significant which shows that model are identified. Moreover, Hansen J statistics are included to check validity of instruments. Our key findings suggest that energy intensity and energy mix on economic performance for European countries varies depending on the time era and degree of development. Results predict that economic expansion tends to be acutely susceptible to EI after 1990, and the lower the amount of income per capita, greater the sensitivity. It is also obvious that a broader approach is required.
This study has analyzed correlation among those variables that affect women working hours in labor market in Pakistan. We used primary data that was collected from the rural and urban areas of District Multan. A sample of 300 women having eight years education was taken randomly and formal questionnaire was constructed for this purpose. Ordinary Least Square method was applied for estimation of parameters. The results of our empirical study show that various variables have expected signs in analysis. We found that joint family setup, family expenditures, number of dependent, working days and wage rate impact positively and significantly to the working hours of women. In contrast, number of children, nuclear family size, etcare inversely related to the women working hours. Therefore, we suggest that there should be provision of better education for women to improve their working hours and participation rate in labor market.
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