Library

eCommons

DigitalCollections@ILR
ILR School
 

Levels and long-term trends in earnings inequality: Overcoming Current Population Survey censoring problems using the GB2 distribution

Simple item page
dc.contributor.authorFeng, Shuaizhang
dc.contributor.authorBurkhauser, Richard V.
dc.contributor.authorButler, J. S.
dc.date.accessioned2020-12-06T23:09:34Z
dc.date.available2020-12-06T23:09:34Z
dc.date.issued2006-01-01
dc.description.abstractOver its history, the March Current Population Survey (CPS) has increasingly captured the upper tail of the distribution of all sources of income. This, together with time-consistency problems in top coding, means that users of both the public-use and restricted-access CPS will understate the level of wage earnings and income inequality in earlier years and overstate their growth over time. We address this problem by modeling the personal earnings of full-time, full-year workers using the generalized beta distribution of the second kind, calculating Gini coefficients from the estimated parameters, and comparing them with past findings.
dc.description.legacydownloadsDE113A_pdf2.pdf: 250 downloads, before Oct. 1, 2020.
dc.identifier.other452132
dc.identifier.urihttps://hdl.handle.net/1813/89952
dc.language.isoen_US
dc.subjectEDIcat4-DER
dc.subjectdata
dc.subjectdisability
dc.subjectDisability Employment Research
dc.subjectdisability statistics
dc.subjecteconomics
dc.subjectEDI
dc.subjectemployment
dc.subjectestimates
dc.subjectpolicy
dc.subjectstatistics
dc.subjectstats
dc.subjectCPS
dc.subjectCurrent Population Survey
dc.subjectpublic-use
dc.subjectrestricted-access
dc.subjectearnings
dc.subjectGini
dc.subjectgb2
dc.titleLevels and long-term trends in earnings inequality: Overcoming Current Population Survey censoring problems using the GB2 distribution
dc.typearticle
local.authorAffiliationFeng, Shuaizhang: Cornell University
local.authorAffiliationBurkhauser, Richard V.: rvb1@cornell.edu Cornell University
local.authorAffiliationButler, J. S.: University of Kentucky

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
DE113A_pdf2.pdf
Size:
63.61 KB
Format:
Adobe Portable Document Format
Download

Collections

K. Lisa Yang and Hock E. Tan Institute on Employment and Disability Collection