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Estimation of upper and lower bounds of Gini coefficient by fuzzy data
Reza Ashraf Ganjoei1, Hossein Akbarifard1, Mashaallah Mashinchi2
1Department of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, Iran.
Abstract:
The data presented in this paper are used to examine the uncertainty in macroeconomic variables and their impact on the Gini coefficient. Annual data for the period 2017 - 1996 are taken from the Bank of Iran website https://www.cbi.ir. We used fuzzy regression with symmetric coefficients to calculate upper and lower bound data of Gini coefficient. Estimated data at this stage can be a very useful guide for policymakers, on the other hand, it is a benchmark for evaluating the effectiveness of government policies. The reason for using fuzzy regression to estimate data on Gini coefficients is the extra flexibility of this model.
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