Estimation of the Gini coefficient based on two quantiles.
Based on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a h...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318833 |
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| _version_ | 1850186928908926976 |
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| author | Pingsheng Dai Sitong Shen |
| author_facet | Pingsheng Dai Sitong Shen |
| author_sort | Pingsheng Dai |
| collection | DOAJ |
| description | Based on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a hundredth. Monte Carlo simulation shows that the new method has good performance and robustness for estimating Gini coefficients with different sample sizes and different inequality levels. Using the two quantiles in the deciles to estimate the sample Gini coefficient and the Lorenz fitting curve is a practical method. |
| format | Article |
| id | doaj-art-bd857a079cda45708301859e09c8d986 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-bd857a079cda45708301859e09c8d9862025-08-20T02:16:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031883310.1371/journal.pone.0318833Estimation of the Gini coefficient based on two quantiles.Pingsheng DaiSitong ShenBased on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a hundredth. Monte Carlo simulation shows that the new method has good performance and robustness for estimating Gini coefficients with different sample sizes and different inequality levels. Using the two quantiles in the deciles to estimate the sample Gini coefficient and the Lorenz fitting curve is a practical method.https://doi.org/10.1371/journal.pone.0318833 |
| spellingShingle | Pingsheng Dai Sitong Shen Estimation of the Gini coefficient based on two quantiles. PLoS ONE |
| title | Estimation of the Gini coefficient based on two quantiles. |
| title_full | Estimation of the Gini coefficient based on two quantiles. |
| title_fullStr | Estimation of the Gini coefficient based on two quantiles. |
| title_full_unstemmed | Estimation of the Gini coefficient based on two quantiles. |
| title_short | Estimation of the Gini coefficient based on two quantiles. |
| title_sort | estimation of the gini coefficient based on two quantiles |
| url | https://doi.org/10.1371/journal.pone.0318833 |
| work_keys_str_mv | AT pingshengdai estimationoftheginicoefficientbasedontwoquantiles AT sitongshen estimationoftheginicoefficientbasedontwoquantiles |