مطالب

Objective: Recent literature emphasizing the importance of income distribution for pollution. The GINI index is the most common indicator for measuring income inequality in previous studies. The new literature has focused on relative redistribution, which is quantified by the GINI coefficientis defined as the difference between the GINI based on market income and GINI based on disposable income. Thus, this study relies on the redistributive effect of taxes and transfers and its impact on carbon dioxide emissions.Methods: The study is conducted using aggregated data from oil-exporting countries including Canada, the United States, the UK, Mexico, the Netherlands, Russia, and China between 2010 and 2020 by using a simultaneous equations system consisting of two equations so that economic growth and pollution emission are as endogenous variables. Elative redistribution, good governance, oil income, trade openness, and CO2 emission are the exogenous variables. Results: Based on model estimates, income inequality, good governance, and oil income have a positive and significant impact on economic growth over the years studied, while inequalities in human development and population growth rates have a negative impact. Economic growth and trade openness also have a negative and significant impact on the spread of pollutionConclusion: Taxes and transfer payments, as redistribution tools can stimulate economic growth. Relative redistribution as a more equitable way can lead to increased economic growth and economic growth reduces carbon dioxide emissions. Therefore, providing an appropriate standard of income inequality can help to better understand and formulate effective policies for income equality.

Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale. After screening the raw data, covariance-based confirmatory factor analysis was used to evaluate the validity, reliability and fittingness of the research model, and the hypotheses were tested in the form of a structural model. The results of convergent and divergent validity tests showed that the two indicators of the research model has validity. Also, the reliability tests indicated the generalizability of the research results at 85%. Also, all the research hypotheses were confirmed.Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale.

The present research was targeted toward examining the relationship between cultural intelligence (CQ), emo-sensory intelligence (ESQ), language learning strategies (LLS), and students’ language achievement (LA). A number of 300 EFL Iraqi students studying at the English Language Department of AL-Qadisiyah University, Iraq was selected through convenience sampling. The participants filled out the cultural intelligence questionnaire, emo-sensory intelligence scale, and the language learning strategy inventory. Students’ final scores were used as a means through which their language achievement could be gauged. The data were analyzed using Pearson Product-Moment Correlation and Structural Equation Modeling (SEM) analysis. The findings indicated a significant relationship between ESQ, CQ, learning strategies, and students’ language achievement. In addition, it was found that CQ and language learners’ strategy could directly predict the language achievement of Iraqi EFL learners. ESQ, could only predict language learners’ achievement through the mediation of language learning strategies.