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

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 calcula...

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Autores principales: Ganjoei, Reza Ashraf, Akbarifard, Hossein, Mashinchi, Mashaallah, Majid Jalaee Esfandabadi, Sayyed Abdol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Computer Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038473/
https://www.ncbi.nlm.nih.gov/pubmed/32123714
http://dx.doi.org/10.1016/j.dib.2020.105288
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author Ganjoei, Reza Ashraf
Akbarifard, Hossein
Mashinchi, Mashaallah
Majid Jalaee Esfandabadi, Sayyed Abdol
author_facet Ganjoei, Reza Ashraf
Akbarifard, Hossein
Mashinchi, Mashaallah
Majid Jalaee Esfandabadi, Sayyed Abdol
author_sort Ganjoei, Reza Ashraf
collection PubMed
description 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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spelling pubmed-70384732020-03-02 Estimation of upper and lower bounds of Gini coefficient by fuzzy data Ganjoei, Reza Ashraf Akbarifard, Hossein Mashinchi, Mashaallah Majid Jalaee Esfandabadi, Sayyed Abdol Data Brief Computer Science 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. Elsevier 2020-02-14 /pmc/articles/PMC7038473/ /pubmed/32123714 http://dx.doi.org/10.1016/j.dib.2020.105288 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Ganjoei, Reza Ashraf
Akbarifard, Hossein
Mashinchi, Mashaallah
Majid Jalaee Esfandabadi, Sayyed Abdol
Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title_full Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title_fullStr Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title_full_unstemmed Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title_short Estimation of upper and lower bounds of Gini coefficient by fuzzy data
title_sort estimation of upper and lower bounds of gini coefficient by fuzzy data
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038473/
https://www.ncbi.nlm.nih.gov/pubmed/32123714
http://dx.doi.org/10.1016/j.dib.2020.105288
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