Evaluating Social Policy by Experimental and Nonexperimental Methods
利用挪威康复项目的随机实验数据，比较了多种非实验估计量与实验结果的差异，发现样本选择偏差处理不当会导致评估高度不可靠，而双重差分和倾向得分匹配表现更好。
Although it is important to establish causal relationships in social policy evaluation, the effects are difficult to observe due to sample selection. To evaluate the performance of estimators designed to handle sample selection bias, we analyse data from a Norwegian rehabilitation project with a randomised experimental design. The data permit us to compare the performance of different nonexperimental estimators with the experimental results. In our case study we find that nonexperimental evaluation based on sample selection estimators with selection terms that fail to meet conventional levels of statistical significance is highly unreliable. The difference in difference estimator and propensity score matching estimators perform better in our context.