Estimation of upper and lower bounds of Gini coefficient by fuzzy data

Reza Ashraf Ganjoei, Hossein Akbarifard, M. Mashinchi

Data in Brief · 2020 · 13 citations · 3 references

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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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