Despite the fact that the global economy grows, the income inequality increases. The Income Inequality is an important factor which affects the human life negatively both in the financial and the social manner. It has been made lots of investigations whose topic is the economic growth and the income inequality. In this paper, it has been compared the connection between the economic growth and the income inequality in terms of the polity in the countries. Therefore, it has been desired to be brought a different perspective into the literature on the subject of the economic growth and the income inequality. It has been given information about the situation in the world especially aimed at the income inequality. The correlation of “Gini Coefficient” and “Economic Growth” belonging to the democratic countries (USA, United Kingdom and Germany) and the autocratic countries (Ethiopia, Nigeria and Gabon) in terms of their polities has been tested with the Panel Data Methodology. Empirical analysis involves the period of 1995-2015. In the results obtained by making Panel Data Model, it has been ascertained a negative correlation between the Economic Growth and the Income Inequality for the democratic countries. However in the autocratic countries, it has been seen that this correlation is very weak.

Traditional production is carried out using fossil fuels. In recent years, the destructive effects of fossil fuel elimination especially on human health and the environment became prominent. This effect leads to an increase in health expenditures (HE), and health problems that are severe and require long term therapies. To counter this problem, some countries have taken some measures to mini the effects of fossil fuels. One of these measures is called “Land Use, Land Use Change and Forestry” or LULUCF for short. LULUCF aims to reduce greenhouse gas emissions in the atmosphere by natural means that are cheap. In this regard, this paper aims to analyze the effects of harmful gases of total emissions in terms of health expenditures both including LULUCF (LI) and excluding LULUCF (LE). Panel data methodology and SPSS Path (Structural Equation) Model were used and cover G7 countries between 1990 and 2016. It was found that there is no linear relationship between LE and HE and LI has no effect on HE. Path analysis showed a negative correlation between LI total emission and SH and a positive correlation between LE total emission and HE.