Matching on the Estimated Propensity Score
Matching on the Estimated Propensity Score
复制标题
DOI：
10.3982/ecta11293
复制
发表时间：
2016-03-01
期刊：
影响因子：
6.1
通讯作者：
Imbens, Guido W.
中科院分区：
文献类型：
--
作者：
Abadie, Alberto;Imbens, Guido W.
倾向评分匹配估计（Rosenbaum和Rubin（1983））被广泛用于评价研究以估计平均治疗效果。在这篇文章中，我们得到了大样本分布的倾向得分匹配估计。我们的推导考虑到倾向分数本身是在匹配之前的第一步中估计的。我们证明了第一步估计的倾向得分影响大样本分布的倾向得分匹配估计，并得出调整的平均治疗效果（ATE）和平均治疗效果的倾向得分匹配估计的大样本方差的治疗（ATET）。ATE估计量的调整是负的（或在某些特殊情况下为零），这意味着在大样本中，估计倾向评分的匹配比真实倾向评分的匹配更有效。然而，对于ATET估计器，调整项的符号取决于数据生成过程，忽略倾向分数中的估计误差可能导致置信区间过大或过小。
Propensity score matching estimators (Rosenbaum and Rubin (1983)) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity score is itself estimated in a first step, prior to matching. We prove that first step estimation of the propensity score affects the large sample distribution of propensity score matching estimators, and derive adjustments to the large sample variances of propensity score matching estimators of the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The adjustment for the ATE estimator is negative (or zero in some special cases), implying that matching on the estimated propensity score is more efficient than matching on the true propensity score in large samples. However, for the ATET estimator, the sign of the adjustment term depends on the data generating process, and ignoring the estimation error in the propensity score may lead to confidence intervals that are either too large or too small.