A model specification test for semiparametric nonignorable missing data modeling

Cheng Yong Tang

Econometrics and Statistics, 2024, vol. 30, issue C, 124-132

Abstract: The instrumental variable approaches have been demonstrated effective for semiparametrically modeling the propensity function in analyzing data that may be missing not at random. A model specification test is considered for a class of parsimonious semiparametric propensity models. The test is constructed based on assessing an over-identification so as to detect possible incompatibility in the moment conditions when the model and/or instrumental variables are misspecified. Validity of the test under the null hypothesis is established; and its power is studied when the model is misspecified. A data analysis and simulations are presented to demonstrate the effectiveness of our methods.

Keywords: Data missing not at random; Instrumental variable; Model specification test; Propensity function (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:30:y:2024:i:c:p:124-132

DOI: 10.1016/j.ecosta.2021.08.005

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