The equivalence of three latent class models and ML estimators

dc.contributor.authorTennekoon, Vidhura S.
dc.contributor.departmentDepartment of Economics, School of Liberal Artsen_US
dc.date.accessioned2016-11-04T16:06:30Z
dc.date.available2016-11-04T16:06:30Z
dc.date.issued2016-04
dc.description.abstractThe purpose of this letter is to show the equivalence of three latent class models; the switching regression model with endogenous switching and a latent outcome (the binary Roy model), the probit model with a systematically misclassified dependent variable, and a trivariate probit model with partial observability. The probit model with measurement error is an enhanced version of existing models which allows for the potential correlation between error terms. Establishing this connection, we hope, will help a researcher working on one of these classes of estimators to benefit from the literature and software related to other families.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationTennekoon, V. S. (2016). The equivalence of three latent class models and ML estimators. Economics Letters, 141, 147–150. http://doi.org/10.1016/j.econlet.2016.02.028en_US
dc.identifier.urihttps://hdl.handle.net/1805/11381
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.isversionof10.1016/j.econlet.2016.02.028en_US
dc.relation.journalEconomics Lettersen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectbinary roy modelen_US
dc.subjectpartial observatory modelen_US
dc.subjectmisclassified dataen_US
dc.titleThe equivalence of three latent class models and ML estimatorsen_US
dc.typeArticleen_US
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