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A model specification test for semiparametric nonignorable missing data modeling

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  • Tang, Cheng Yong

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.

Suggested Citation

  • Tang, Cheng Yong, 2024. "A model specification test for semiparametric nonignorable missing data modeling," Econometrics and Statistics, Elsevier, vol. 30(C), pages 124-132.
    • Handle: RePEc:eee:ecosta:v:30:y:2024:i:c:p:124-132
    DOI: 10.1016/j.ecosta.2021.08.005
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