Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/162508 
Year of Publication: 
2017
Series/Report no.: 
SFB 649 Discussion Paper No. 2017-007
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
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 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.
Subjects: 
incomplete data
missing-data mechanism
selection model
nonparametric hypothesis testing
consistent testing
instrumental variable
series estimation
Document Type: 
Working Paper

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