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Reconciling reports: modelling employment earnings and measurement errors using linked survey and administrative data
被引:5
|作者:
Jenkins, Stephen P.
[1
]
Rios-Avila, Fernando
[2
]
机构:
[1] London Sch Econ & Polit Sci, Dept Social Policy, Houghton St, London WC2A 2AE, England
[2] Levy Econ Inst Bard Coll, Annandale On Hudson, NY USA
关键词:
measurement error;
earnings;
finite mixture models;
linkage error;
linked survey data and administrative data;
EXTENT;
INCOME;
D O I:
10.1093/jrsssa/qnac003
中图分类号:
O1 [数学];
C [社会科学总论];
学科分类号:
03 ;
0303 ;
0701 ;
070101 ;
摘要:
We develop and apply new statistical models for linked survey and administrative data on employment earnings, incorporating 4 types of measurement error. In addition, we allow error distributions to differ with individual characteristics, which improves model fit and allows us to investigate substantive hypotheses about factors associated with error bias and variance. Contributing the first UK evidence to a field dominated by findings about the USA, we show that measurement errors are pervasive, but the 4 types are quite different in nature. We also document substantial heterogeneity in each of the error distributions.
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页码:110 / 136
页数:27
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