Mohsen Mehrara; Mojtaba Mohammdian
Volume 19, Issue 61 , February 2015, , Pages 83-116
Abstract
This paper has tried to apply Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approaches as methods of averaging in Bayesian econometrics in order to investigate the impact of 18 macroeconomic variables on Gini coefficient in Iran based on annual data from 1976 to 2010. The results ...
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This paper has tried to apply Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approaches as methods of averaging in Bayesian econometrics in order to investigate the impact of 18 macroeconomic variables on Gini coefficient in Iran based on annual data from 1976 to 2010. The results of two approaches indicate that the growth rate of Gross domestic products is the most important determinant of the Gini coefficient, implying economic growth arising from oil booms leads to more unequal distribution of income. As regards to other variables, the results of BMA estimation indicate that second and third effective variables on Gini coefficient are respectively the ratio of government current expenditure to GDP and the ratio of oil revenue to GDP for which an increase in the ratios engenders inequality. Thus the distribution of oil rents and government expenditure is inconsistent with primary purposes of politicians to ameliorate income distribution. Also the results of WALS estimation rank openness and exchange rate as the most effective variables respectively with positive sign. Therefore economic liberalization moving along with oil revenue during the sample period, has been against the favor of lower income groups. According to aforementioned results, it is necessary to revise economic growth policies to the benefit of low-income groups of people. In addition, renovation of budgeting process and allocation of resources with aim to reduce rent-seeking opportunities and more privileges for low-income groups must be considered by policy makers.
