Univariate Multiple Imputation for Coarse Employee Income Data


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dc.creator Daniels, Reza Che
dc.date 2013-02-28T13:39:54Z
dc.date 2013-02-28T13:39:54Z
dc.date 2012
dc.date.accessioned 2015-05-28T10:05:13Z
dc.date.available 2015-05-28T10:05:13Z
dc.date.issued 2015-05-28
dc.identifier http://hdl.handle.net/11090/179
dc.identifier.uri http://hdl.handle.net/11090/179
dc.description This paper is concerned with conducting univariate multiple imputation for employee income data that is comprised of continuously distributed observations, observations that are bounded by consecutive income brackets, and observations that are missing. A variable with this mixture of data types is a form of coarsening in the data. An interval-censored regression imputation procedure is utilised to generate plausible draws for the bounded and nonresponse subsets of income. We test the sensitivity of results to mis-specification in the prediction equations of the imputation algorithm, and we test the stability of the results as the number of imputations increase from two to five to twenty. We find that for missing data, imputed draws are very different for respondents who state that they don't know their income compared to those who refuse. The upper tail of the income distribution is most sensitive to mis-specification in the imputation algorithm, and we discuss how best to conduct multiple imputation to take this into account. Lastly, stability in parameter estimates of the income distribution is achieved with as little as two multiple imputations, due largely to (a) the small fraction of missing data, in combination with (b) reduced within- and between-imputation components of variance for imputed draws of the bracketed income subset, a function of the defined lower and upper bounds of the brackets that restrict the range of plausibility for imputed draws. This is a joint SALDRU and DataFirst working paper
dc.description Multiple Imputation, Coarse Data, Income Distribution Classification-JEL: C15, C83, D31
dc.language.iso eng
dc.publisher Southern Africa Labour and Development Research Unit
dc.subject Multiple imputation
dc.subject Income distribution
dc.subject Imputed income
dc.title Univariate Multiple Imputation for Coarse Employee Income Data
dc.type Report
uct.type.publication Research en_ZA
uct.type.resource SALDRU Report en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Commerce en_ZA
dc.publisher.department SALDRU en_ZA
dc.identifier.ris TY - Report DA - 2015-05-28 DB - OpenUCT DP - University of Cape Town KW - Multiple imputation KW - Income distribution KW - Imputed income LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 T1 - Univariate Multiple Imputation for Coarse Employee Income Data TI - Univariate Multiple Imputation for Coarse Employee Income Data UR - http://hdl.handle.net/11090/179 ER - en_ZA

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