EconStor >
Forschungsinstitut zur Zukunft der Arbeit (IZA), Bonn >
IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA) >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/35759
  
Title:Measuring inequality using censored data: a multiple imputation approach PDF Logo
Authors:Jenkins, Stephen P.
Burkhauser, Richard V.
Feng, Shuaizhang
Larrimore, Jeff
Issue Date:2009
Series/Report no.:IZA discussion papers 4011
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 Reiter'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.
Subjects:Income inequality
topcoding
partially synthetic data
CPS
Current Population Survey
Generalized Beta of the Second Kind distribution
JEL:D31
C46
C81
Persistent Identifier of the first edition:urn:nbn:de:101:1-20090304434
Document Type:Working Paper
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

Files in This Item:
File Description SizeFormat
593240073.pdf565.92 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/35759

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.