论文标题
使用Beta的混合物对不平等措施的小面积估计
Small Area Estimation of Inequality Measures using Mixtures of Beta
论文作者
论文摘要
谈论特定地区的经济不平等对于加深空间异质性至关重要。通常计划收入调查以在国家或大型级别的水平上产生可靠的估计，因此我们为一组不平等措施（Gini，相对Theil和Atkinson Indexes）实施了一个小面积模型，以获得微区估计。考虑到不平等估计器是用偏斜和重尾分布定义的单位间隔器，我们在涉及Beta混合物的区域水平上提出了贝叶斯分层模型。进行了欧盟-SILC数据的应用程序，并执行基于设计的模拟。我们的模型在偏差，覆盖范围和错误方面优于标准Beta回归模型。此外，我们通过得出近似方差函数来扩展不平等估计量的分析。
Economic inequalities referring to specific regions are crucial in deepening spatial heterogeneity. Income surveys are generally planned to produce reliable estimates at countries or macroregion levels, thus we implement a small area model for a set of inequality measures (Gini, Relative Theil and Atkinson indexes) to obtain microregion estimates. Considering that inequality estimators are unit-interval defined with skewed and heavy-tailed distributions, we propose a Bayesian hierarchical model at area level involving a Beta mixture. An application on EU-SILC data is carried out and a design-based simulation is performed. Our model outperforms in terms of bias, coverage and error the standard Beta regression model. Moreover, we extend the analysis of inequality estimators by deriving their approximate variance functions.
