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Identification and Estimation of Categorical Random Coeficient Models

dc.contributor.authorGao, Z.
dc.contributor.authorPesaran, M. H.
dc.date.accessioned2022-04-28T12:51:35Z
dc.date.available2022-04-28T12:51:35Z
dc.date.issued2022-04-14
dc.description.abstractThis paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of Moments estimator is proposed, and its finite sample properties are examined using Monte Carlo simulations. The utility of the proposed method is illustrated by estimating the distribution of returns to education in the U.S. by gender and educational levels. We find that rising heterogeneity between educational groups is mainly due to the increasing returns to education for those with postsecondary education, whereas within group heterogeneity has been rising mostly in the case of individuals with high school or less education.
dc.identifier.doi10.17863/CAM.83975
dc.identifier.otherCWPE2228
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/336554
dc.language.isoeng
dc.publisherFaculty of Economics, University of Cambridge
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.subjectRandom coefficient models
dc.subjectcategorical distribution
dc.subjectreturn to education
dc.titleIdentification and Estimation of Categorical Random Coeficient Models
dc.typeWorking Paper
rioxxterms.versionAO

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