Decomposition of welfare distribution in Iran

After Hamilton (2001) and Costa (2001) many empirical and analytical studies (Gong and Meng (2007), Barrett and Brzozowski (2008), …) have manipulated and extended Engel's law to estimate CPI bias and regional price differences. However, there is not yet any study on Iran in which the biases in spatial prices or price indices are discriminated. In this study we suggest that bidimensional social welfare perspectives may contribute very well to policy implications intending to protect Iranian households. To do so, first, we use Hamilton's approach to estimate a Spatial Price Index (SPI) helping us to have a better household welfare criterion. Second, using a developed version of Gini bidimensional decomposition, we find the contribution of rural and urban areas to inequality. Our decomposition method is an improved version of Mussard (2004) bidimensional decomposition method. Our results indicate that while Iranian authorities repeatedly have claimed that income inequalities have improved after the targeted cutting of subsidies in 2011, the above improvement is due to a bias in regional price indices.