Testing Missing at Random Using Instrumental Variables
提出一种检验数据是否随机缺失的方法，利用工具变量构造检验统计量，推导了渐近分布，并通过蒙特卡洛模拟和劳动收入问卷实例验证了有效性。
This article proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s asymptotic distribution under the MAR hypothesis is derived. In particular, our results can be applied to testing missing completely at random (MCAR). A Monte Carlo study examines finite sample performance of our test statistic. An empirical illustration analyzes the nonresponse mechanism in labor income questions.