Measuring Inequality Using Censored Data: A Multiple Imputation Approach

Stephen Jenkins (), Richard V. Burkhauser (), Feng S and Jeff Larrimore ()
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Feng S: Shanghai University of Finance and Economics

No 2009-04, ISER working papers from Institute for Social and Economic Research

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 ReiterÂ’s (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.

New Economics Papers: this item is included in nep-ecm and nep-ltv
Date: 2009-02-09
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Working Paper: Measuring Inequality Using Censored Data: A Multiple Imputation Approach (2009)
Working Paper: Measuring Inequality Using Censored Data: A Multiple Imputation Approach (2009)
Working Paper: Measuring inequality using Censored data: A multiple imputation approach (2009)
Working Paper: Measuring Inequality Using Censored Data: A Multiple Imputation Approach (2009)
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