This paper 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 statisticís 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.
Incomplete data, missing-data mechanism, selection model,
nonparametric hypothesis testing, consistent testing,
instrumental variable, series estimation.