Reza Najarzadeh - Department of Economics, Tarbiat Modares University, Tehran, Iran
Alireza Keikha - Department of Economics, Tarbiat Modares University, Tehran, Iran
Hassan Heidari - Department of Economics, Tarbiat Modares University, Tehran, Iran

This study aims to investigate poverty risk and inequality decomposition based on the education level of Iranian urban household heads in ۲۰۱۷. A logistic regression model is estimated with the poverty status of households as a dependent variable, a set of control variables (gender and age), and the education level of household heads as explanatory variables. We also use the Gini decomposition as appropriate inequality decomposition for selected provinces. These provinces are categorized based on whether they are deprived or non-deprived provinces using the Council of Ministers guidelines. The findings show that the poverty risk of families in both deprived and non-deprived provinces as well as the country as a whole decrease when the education level of the household head increases. The marginal effect of the first level of education is higher than other levels. Therefore, one can conclude that Iran is more similar to less developed countries. We also show that being a male household head reduces the poverty risk of families in Iran, but the gender of household heads has no significant effect in the selected provinces. In addition, the poverty risk in higher age groups is lower than that of other age groups. Based on the Gini decomposition reports, the highest level of inequality is observed in Sistan and Baloochestan province which suffers from the highest level of unemployment and illiteracy rates in Iran. Finally, inequality decomposition confirms the crucial role of education in explaining inequality.

Poverty Risk, Education, inequality decomposition, Logistic regression, Iran