A Bayesian Measure of Poverty in the Developing World
提出一种基于贝叶斯方法修订国际贫困线的新方法，在传统收入基础上加入社会包容变量，估计全球收入分布及发展中世界的贫困人口数量，并讨论人口加权和购买力平价更新的影响。
We propose a new methodology to revise the international poverty line (IPL) after Ravallion et al . (2009) using the same database, but augmented with new variables to take into account social inclusion in the definition of poverty along the lines of Atkinson and Bourguignon (2001). We provide an estimation of the world income distribution and of the corresponding number of poor people in the developing world. Our revised IPL is based on an augmented two‐regime model estimated using a Bayesian approach, which allows us to take into account uncertainty when defining the reference group of countries where the IPL applies. The influence of weighting by population is discussed, as well as the IPL revision proposed in Deaton (2010). We also discuss the impact of using the new 2011 PPP and the recent IPL revision made by the World Bank.