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Measuring Inequality Using Censored Data: A Multiple Imputation Approach
by Stephen P. Jenkins, Richard V. Burkhauser, Shuaizhang Feng, Jeff Larrimore
(February 2009)
revised version published in: Journal of the Royal Statistical Society, Series A (Statistics in Society), 2011, 174 (1), 63 - 81

Abstract:
To measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference uses Reiterís (Survey Methodology 2003) formulae. Using Current Population Survey (CPS) internal data, we find few statistically significant differences in income inequality for pairs of years between 1995 and 2004. We also show that using CPS public use data with cell mean imputations may lead to incorrect inferences about inequality differences. Multiply-imputed public use data provide an intermediate solution.
Text: See Discussion Paper No. 4011  




 

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