...
首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Kinetic theory and Brazilian income distribution
【24h】

Kinetic theory and Brazilian income distribution

机译:动力学理论和巴西收入分配

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

We investigate the Brazilian personal income distribution using data from National Household Sample Survey (PNAD), an annual research available by the Brazilian Institute of Geography and Statistics (IBGE). It provides general characteristics of the country's population. Using PNAD data background we also confirm the effectiveness of a semi-empirical model that reconciles Pareto power-law for high-income people and Boltzmann-Gibbs distribution for the rest of the population. We use three measures of income inequality: the Pareto index, the average income and the crossover income. In order to cope with many dimensions of the income inequality, we calculate these three indices and also the Gini coefficient for the general population as well as for two kinds of population dichotomies: black/indigenous/mixed race versus white/yellow and men versus women. We followed the time series of these indices for the period 2001-2014. The results suggest a decreasing of Brazilian income inequality over the selected period. Another important result is that historically-disadvantaged subgroups (Women and black/indigenous/mixed race),that are the majority of the population, have a more egalitarian income distribution. These groups have also a smaller income than the others and this social structure remained virtually unchanged in this period. (C) 2018 Published by Elsevier B.V.
机译:我们使用来自国家家庭样本调查(PNAD)的数据,由巴西地理和统计研究所(IBGE)提供的年度研究,调查巴西个人收入分配。它提供了该国人口的一般特征。使用PNAD数据背景,我们还确认了一个半实证模型的有效性,以便在别人的高收入人和Boltzmann-Gibbs分布中调整帕累托动力法的效力。我们使用三种收入不等式措施:帕累托指数,平均收入和交叉收入。为了应对收入不平等的许多维度,我们计算这三个指数以及一般人群的基尼系数以及两种人口二分法:黑/土着/混合赛与白色/黄色和男性对女性。我们遵循2001 - 2014年期间这些指数的时间序列。结果表明,在选定期间减少了巴西收入不平等。另一个重要的结果是,在历史上处于劣势亚组(女子和黑/土著/混血),这是大多数人的,有一个更平等的收入分配。这些群体的收入比其他团体更小,而这种社会结构在此期间几乎保持不变。 (c)2018由elestvier b.v出版。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号