基于模糊数据的基尼系数上下界估计

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

作者信息

Ganjoei Reza Ashraf, Akbarifard Hossein, Mashinchi Mashaallah, Majid Jalaee Esfandabadi Sayyed Abdol

机构信息

Department of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, Iran.

Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.

出版信息

Data Brief. 2020 Feb 14;29:105288. doi: 10.1016/j.dib.2020.105288. eCollection 2020 Apr.

DOI:10.1016/j.dib.2020.105288

PMID:32123714

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7038473/

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.

摘要

本文所呈现的数据用于检验宏观经济变量的不确定性及其对基尼系数的影响。2017 - 1996年期间的年度数据取自伊朗央行网站https://www.cbi.ir。我们使用具有对称系数的模糊回归来计算基尼系数的上下界数据。现阶段的估计数据对政策制定者而言可能是非常有用的指导，另一方面，它是评估政府政策有效性的一个基准。使用模糊回归来估计基尼系数数据的原因在于该模型具有额外的灵活性。