Gini coefficient

Economic justice and equitable distribution of income, along with important issues such as economic growth and development, the reduction of inflation and unemployment, have always been of concern to economists. Fair distribution of income and reduction of income inequality in society, and the identification of factors affecting income inequality to make the right policy are necessary and obvious. The purpose of this paper is to examine the impact of income tax on income distribution in Iran. In this regard, Autoregressive Distributed Lag (ARDL) approach has been used to investigate the existence of a long-run relationship between variables and to estimate the coefficients related to long-run and error correction models for income inequality from 1978 to 2012. The results indicate a long-run relationship among the variables and show that an increase in income tax revenues leads to a reduction in income inequality.

This article examines the effect of government size on the high, medium and low thresholds of the Gini coefficient in Iran. For this purpose, the auto regression model of soft fuzzy logistic transfer (FLSTAR) has been used for the period of 1997-2019. One of the reasons for using this model is flexibility in its application. The main focus of this paper is to calculate the Gini coefficient bands according to the size of government in the economy. Hence, we calculate the bands (high, middle and low) of the Gini coefficient. The study show that the threshold size of the government is equal 0.499. Findings of this research are applied in a real case which reveal that with increase of government share in economy the Gini coefficient increases as well. Therefore, the government should seriously pursue privatization policies.

Life expectancy and infant mortality are two major indicators for assessing the efficiency of every social health system. The bulk of literature on health economics is related to unilateral influences of macroeconomic variables on health sector indices and less attention has been paid to bilateral and simultaneous effects. Therefore, this paper aims to examine the bilateral and simultaneous impacts of the key macroeconomic variables on life expectancy and infant mortality in Iran during 1981-2018. To this end, by considering the government’s health care expenditures and GINI coefficient, a system of simultaneous equations based on variables of life expectancy, infant mortality and economic growth is developed. The findings indicated that income growth per capita affects the growth of life expectancy index positively by 31%, but the growth of social-class differences or income inequality has a negative effect on this index. Moreover, the escalation of health care budget in Iran has led to slumps in infant mortality rate by 83%. Such outcome exhibits the significant role of government, parliament and legislature in approving and improving the budget of the Ministry of Health and facilitating achievement of higher social-health standards. Finally, findings of present study reflected the simultaneous and positive effects of improving growth of life expectancy and reverse effect of infant mortality growth indices on the economic growth of Iran. The estimations provided evidence on the interactions between enhancing the macroeconomic conditions and improving the health economy indicators and existence of a reinforcing loop between them.

Income inequality is one of the undesirable phenomena of social life and most of the countries in the world have kept it their main goal to reduce Income inequality. This study is based on the economic impact of the doom index on the distribution of income using data from selected Islamic countries (Afghanistan, Albania, Egypt, Indonesia, Iran, Malaysia, Pakistan, Turkey, Bangladesh, Kazakhstan, Moldova and Uganda) from 2010 to 2018, using panel data approach for variables EViews model is used. This study explains the significant effect of misery index with a coefficient of (0.057) on the Gini coefficient and shows that with a one percent increase in the misery index can increase Gini coefficient by 0.057 percent and increases the class gap in societies. It also shows that Labor productivity with a coefficient of 0.01 has a significant negative effect on the Gini coefficient, which explains the 0.01% decrease in income distribution inequality due to a 1% increase in labor productivity. Therefore, in addition to controlling inflation and unemployment, improving human resource skills, economic policymakers should use incentive mechanisms to develop exports and the effectiveness of governments to reduce the class gap in their societies.

Aging and its consequences have made population aging a major social issue. Aging populations are likely to exacerbate inequality by increasing the public and private financial burdens of social welfare costs. The goal of this study was to estimate the effects of aging on income inequality for 81 countries (37 developing and 44 developed) from 2000 to 2020. The study used a dynamic panel approach in a generalized method of moments (GMM) framework. This study's findings confirm a positive relationship between aging and income inequality in both developing and developed countries, and it demonstrates that the aging effect on income inequality is greater in developing countries than in developed countries. Furthermore, improving human capital, increasing per capita income, proper management, and use of total natural resource rents (% of GDP) in countries, and increasing trade between countries reduce income inequality, according to the findings of this study. Policymakers should reduce income inequality by investing in education, increasing per capita income, managing, and utilizing total natural resource rents (as a percentage of GDP), expanding trade with other countries, and planning for the effects of aging.

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.

EXTENDED ABSTRACT INTRODUCTION The number of revealed corruption-related crimes is one of the major challenges of Iran which has been significantly increased in recent years. According to official reports, although only two cases of embezzlement were reported in 1990s and 2000s with a total value up to $ 800 million, administrative corruption has significantly increased in 2010s with 13 large corruption cases and a total value up to $ 14 billion and a growth of over 1500% compared to 1990s and 2000s (The Iranian Students News Agency[1] (ISNA), 2017). The spread of such amount of corruption in administrative and bureaucratic system of the country can have irreparable economic and social consequences. The statistic investigations have shown that macroeconomic indicators including economic growth, employment, unemployment, poverty, inflation and income distribution have become less favorable in 2010 compared to previous decades (Statistical Center of Iran, Iran Statistical Yearbook, 2017). In this regard, the following questions can be raised: is there a relationship between corruption and the indicators of income distribution and poverty in the country? Since the volume of international and unilateral sanctions on Iran has increased in the 2010s, does such a widespread growth in the volume and value of corruption cases in Iran have a relationship with sanctions?   METHODOLOGY Therefore, the purpose of the present study is to investigate the effect of sanctions on causal relationship between corruption, income inequality and poverty in Iran during 1984 to 2020. For this purpose, the indices of per capita income, poverty line, administrative corruption and control of corruption, Atkinson and Gini have been utilized to investigate their interactions through Toda-Yamamoto Causality Test.   FINDINGS Findings of research show that:   sanctions have affected the causality of per capita income on administrative corruption. sanctions have affected the causality of corruption control on per capita income. sanctions have affected the causality of income distribution on per capita income. sanctions had no effect on causality of per capita income, on Atkinson Index and vice versa. sanctions had no effect on causality of per between poverty line, on administrative corruption and vice versa. sanctions had an effect on causality of per between poverty line, on corruption control and vice versa. sanctions had a significant positive effect on poverty line, but had no significant effect on GINI index. In other words, sanctions have affected the causality of income distribution on poverty line. sanctions had no effect on causality of poverty line, on Atkinson Index and vice versa. sanctions had no effect on causality of GINI index, on administrative corruption and vice versa. sanctions had no effect on causality of GINI index, on corruption control and vice versa. sanctions had a significant positive effect on administrative corruption, but had no significant effect on Atkinson index. In other words, sanctions have affected the causality of income distribution on administrative corruption. sanctions had a significant positive effect on Atkinson index, but had no significant effect on corruption control. In other words, sanctions have affected the causality of corruption control on income distribution.     CONCLUSION The purpose of the present study was to investigate the effect of sanctions on causal relationship between corruption, income inequality and poverty in Iran during1984 to 2020. For this purpose, the indices of per capita income p, poverty line, Atkinson, GINI, administrative corruption and corruption control were investigated. In general, the following results were obtained from the present study:   Income distribution is not an effective variable for poverty in Iran. Corruption is an effective variable for causality of poverty in Iran and its significance level is higher under sanctions condition. Corruption and poverty cannot properly explain the income distribution in Iran. However, the corruption control can be the cause of income distribution and poverty line is a proper representative for the cause of income distribution under sanctions conditions. Income distribution is a strong variable for causality of corruption in Iran. Poverty can properly explain the causality of corruption in Iran under sanctions condition, but is not the cause of corruption under normal condition.   According to the obtained results, it seems that sanctions condition is an effective variable for the relationship between variables of income distribution, corruption and poverty. However, the effective factors of income distribution need further investigations in future.