Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects
提出一种处理内生性和空间依赖的贝叶斯工具变量方法，应用于分析电价统一对最贫困家庭的福利影响，发现10%的最贫困市镇福利收益超过初始收入的2%。
We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. We apply our method to analyze the welfare effects generated by a process of electricity tariff unification on the poorest households. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a two-tiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income.