Robust Mean-Squared Error Estimation for Poverty Estimates Based on the Method of Elbers, Lanjouw and Lanjouw
针对世界银行贫困地图方法中忽略区域间变异导致均方误差低估的问题，提出一种稳健的均方误差估计方法，模拟和孟加拉国实例显示其优于传统方法。
Summary The method of Elbers, Lanjouw and Lanjouw (ELL) is the small area estimation method developed by the World Bank for poverty mapping and is widely used in developing countries. However, it has been criticized because of its assumption of negligible between-area variability when used to calculate small area poverty estimates. In particular, the mean-squared errors (MSEs) of these estimates are significantly underestimated when this between-area variability cannot be adequately explained by the model covariates. A method of MSE estimation for ELL-type estimates is proposed which is robust to significant unexplained between-area variability. Simulation results show that the method proposed performs better than standard ELL MSE estimators when the area homogeneity assumption is violated. An application to a Bangladesh poverty mapping study provides some empirical evidence for this robustness.