Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data

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dc.contributor.authorDaniels, Reza C.en_ZA
dc.contributor.authorRospabe, Sandrineen_ZA
dc.date.accessioned2014-09-09T13:48:09Z
dc.date.available2014-09-09T13:48:09Z
dc.date.issued2005-02en_ZA
dc.description.abstractThis paper estimates an earnings function where the dependent variable is a mix of point and interval data using an interval regression model based on a pseudo-maximum likelihood estimation procedure. The analysis uses the 1999 OHS, and takes into account point and interval income observations, as well as design features of the survey including stratification, clustering and weights.en_ZA
dc.identifier.apacitationDaniels, Reza C., & Rospabe, S. (2005). <i>Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data</i> (Development and Poverty Research Unit Working Paper Development Policy Research Unit Working Paper 05/091). University of Cape Town ,Faculty of Commerce ,Development Policy Research Unit (DPRU). Retrieved from http://hdl.handle.net/11427/7372en_ZA
dc.identifier.chicagocitationDaniels, Reza C., and Sandrine Rospabe <i>Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data.</i> Development and Poverty Research Unit Working Paper Development Policy Research Unit Working Paper 05/091. University of Cape Town ,Faculty of Commerce ,Development Policy Research Unit (DPRU), 2005. http://hdl.handle.net/11427/7372en_ZA
dc.identifier.citationDaniels, Reza C. & Rospabe, S. 2005. <i>Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data</i>. (Development and Poverty Research Unit Working Paper Development Policy Research Unit Working Paper 05/091). University of Cape Town ,Faculty of Commerce ,Development Policy Research Unit (DPRU). http://hdl.handle.net/11427/7372 .en_ZA
dc.identifier.isbn1-920055-05-3en_ZA
dc.identifier.ris TY - Working Paper AU - Daniels, Reza C. AU - Rospabe, Sandrine AB - This paper estimates an earnings function where the dependent variable is a mix of point and interval data using an interval regression model based on a pseudo-maximum likelihood estimation procedure. The analysis uses the 1999 OHS, and takes into account point and interval income observations, as well as design features of the survey including stratification, clustering and weights. DA - 2005-02 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2005 SM - 1-920055-05-3 T1 - Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data TI - Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data UR - http://hdl.handle.net/11427/7372 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/7372
dc.identifier.vancouvercitationDaniels Reza C, Rospabe S. Estimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Data. 2005 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/7372en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDevelopment Policy Research Unit (DPRU)en_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.publisher.institutionDevelopment Policy Research Unit
dc.publisher.institutionUniversity of Cape Town
dc.relation.ispartofseriesDevelopment and Poverty Research Unit Working Paper Development Policy Research Unit Working Paper 05/091en_ZA
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 Internationalen_ZA
dc.rights.holderCopyright University of Cape Town 2005.en_ZA
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_ZA
dc.subject.otherC42en_ZA
dc.subject.otherC51en_ZA
dc.titleEstimating an Earnings Function from Coarsened Data by an Interval Censored Regression Procedure. Dataen_ZA
dc.typeWorking Paperen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceWorking paperen_ZA
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