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Measuring inequality using censored data: a multiple imputation approach

Jenkins, SP and Burkhauser, RV and Feng, S and Larrimore, J (2011) 'Measuring inequality using censored data: a multiple imputation approach.' Journal of the Royal Statistical Society Series A (Statistics in Society), 174 (1). creators - Jenkins=3AStephen_P=3A=3A. ISSN 0964-1998

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Abstract

To measure income inequality with right-censored (top-coded) data, we propose multiple-imputation methods for estimation and inference. Censored observations are multiply imputed using draws from a flexible parametric model fitted to the censored distribution, yielding a partially synthetic data set from which point and variance estimates can be derived using complete-data methods and appropriate combination formulae. The methods are illustrated using US Current Population Survey data and the generalized beta of the second kind distribution as the imputation model. With Current Population Survey internal data, we find few statistically significant differences in income inequality for pairs of years between 1995 and 2004. We also show that using Current Population Survey public use data with cell mean imputations may lead to incorrect inferences. Multiply-imputed public use data provide an intermediate solution.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Jim Jamieson
Date Deposited: 26 Sep 2013 13:26
Last Modified: 17 Aug 2017 17:56
URI: http://repository.essex.ac.uk/id/eprint/7971

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