A binary choice model with sample selection and covariate-related misclassification
Resumen: Misclassification of a binary response variable and nonrandom sample selection are data issues frequently encountered by empirical researchers. For cases in which both issues feature simultaneously in a data set, we formulate a sample selection model for a misclassified binary outcome in which the conditional probabilities of misclassification are allowed to depend on covariates. Assuming the availability of validation data, the pseudo-maximum likelihood technique can be used to estimate the model. The performance of the estimator accounting for misclassification and sample selection is compared to that of estimators offering partial corrections. An empirical example illustrates the proposed framework.
Idioma: Inglés
DOI: 10.3390/econometrics10020013
Año: 2022
Publicado en: Econometrics 10, 2 (2022), 13 [20 pp.]
ISSN: 2225-1146

Factor impacto CITESCORE: 2.0 - Economics, Econometrics and Finance (Q2)

Factor impacto SCIMAGO: 0.464 - Economics and Econometrics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/S32-20R
Tipo y forma: Article (Published version)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


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