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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp011z40ks82c
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dc.contributor.authorMcCall, Brian P.en_US
dc.date.accessioned2011-10-26T01:55:42Z-
dc.date.available2011-10-26T01:55:42Z-
dc.date.issued1988-08-01T00:00:00Zen_US
dc.identifier.citationJournal of Political Economy, Vol. 98, No. 1, February 1990en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp011z40ks82c-
dc.description.abstractThis paper develops a model of occupational matching where, within an occupation, information at one job may be useful for predicting the match at other jobs. Recent developments in the theory of superprocesses are used to derive the optimal sampling policy which predicts that those currently working their second job within an occupation are less likely to separate from this job then those working their first job. Also, this difference should increase with tenure in the previous job since, for those with long tenures, it is more likely that occupational sorting has taken place. These predictions are tested using weekly tenure data from the National Longitudinal Survey: Youth Cohort. Controlling for unobserved heterogeniety and employing semi-parametric estimation techniques, it is found that one’s previous job tenure significantly lowers the likelihood of leaving the current job only if both jobs are of the same occupation. However, overall, occupational switchers are more likely to leave the current job only if the tenure in the previous job is greater than one year. Similar results are found for job quitters when the data is analyzed using a competing risks framework.en_US
dc.relation.ispartofseriesWorking Papers (Princeton University. Industrial Relations Section) ; 237en_US
dc.relation.urihttp://links.jstor.org/sici?sici=0022-3808%28199002%2998%3A1%3C45%3AOMATOS%3E2.0.CO%3B2-Nen_US
dc.subjectoccupational matchingen_US
dc.subjectsemi-parametric estimationen_US
dc.subjectcompeting risksen_US
dc.subjectjob matchingen_US
dc.titleOccupational Matching: A Test of Sortsen_US
dc.typeWorking Paperen_US
pu.projectgrantnumber360-2050en_US
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