Bayesian Inference for Welfare Comparisons of Income Inequality and Poverty

这项研究的主要预期结果是在贝叶斯推理框架内进行涉及收入不平等和贫困的福利比较的一系列技术。这些技术的各种应用预期将产生关于不同时间和空间的不平等比较以及关于贫穷水平变化的有用资料。鉴于减少不平等和贫穷程度是一个重大关切事项，发展适当的衡量技术对国家利益具有巨大的潜力。此外，该项目将作为培训两名博士生的工具，因此将有助于培养在衡量收入不平等方面具有专业知识的训练有素的计量经济学家。

The major expected outcome of this research is an array of techniques for making welfare comparisons involving income inequality and poverty within a framework of Bayesian inference. Various applications of the techniques are expected to yield useful information on inequality comparisons over time and space and on changes in the level of poverty. Given that reduction in levels of inequality and poverty is a matter of major concern, the development of suitable measurement techniques has immense potential for national benefit. In addition, the project will serve as a vehicle for training two PhD students, and hence will contribute to the small pool of highly trained econometricians with expertise in measuring income inequality.