Measurement Error and Misclassification: A Comparison of Survey and Administrative Data
A. Kapteyn, and J. Ypma. Journal of Labor Economics, 25 (3):
513-551(2007)
Abstract
We provide both a theoretical and empirical analysis of the relation between administrative and survey data. By distinguishing between different sources of deviations between survey and administrative data we are able to reproduce several stylized facts. We illustrate the implications of different error sources for estimation in (simple) econometric models and find potentially very substantial biases. This article shows the sensitivity of some findings in the literature for the assumption that administrative data represent the truth. In particular, the common finding of substantial mean reversion in survey data largely goes away once we allow for a richer error structure.
%0 Journal Article
%1 kapteyn2007measurement
%A Kapteyn, Arie
%A Ypma, Jelmer Y.
%D 2007
%I The University of Chicago Press, Society of Labor Economists, NORC at the University of Chicago
%J Journal of Labor Economics
%K socdes
%N 3
%P 513-551
%T Measurement Error and Misclassification: A Comparison of Survey and Administrative Data
%U http://www.jstor.org/stable/10.1086/513298
%V 25
%X We provide both a theoretical and empirical analysis of the relation between administrative and survey data. By distinguishing between different sources of deviations between survey and administrative data we are able to reproduce several stylized facts. We illustrate the implications of different error sources for estimation in (simple) econometric models and find potentially very substantial biases. This article shows the sensitivity of some findings in the literature for the assumption that administrative data represent the truth. In particular, the common finding of substantial mean reversion in survey data largely goes away once we allow for a richer error structure.
@article{kapteyn2007measurement,
abstract = {We provide both a theoretical and empirical analysis of the relation between administrative and survey data. By distinguishing between different sources of deviations between survey and administrative data we are able to reproduce several stylized facts. We illustrate the implications of different error sources for estimation in (simple) econometric models and find potentially very substantial biases. This article shows the sensitivity of some findings in the literature for the assumption that administrative data represent the truth. In particular, the common finding of substantial mean reversion in survey data largely goes away once we allow for a richer error structure.},
added-at = {2017-11-27T15:49:49.000+0100},
author = {Kapteyn, Arie and Ypma, Jelmer Y.},
biburl = {https://www.bibsonomy.org/bibtex/2b4f3ebf0e3584f42284e98d5eab36a29/dirtyhawk},
interhash = {5a556530ffaf5fae42f4981fdc882ad4},
intrahash = {b4f3ebf0e3584f42284e98d5eab36a29},
issn = {0734306X, 15375307},
journal = {Journal of Labor Economics},
keywords = {socdes},
number = 3,
pages = {513-551},
publisher = {The University of Chicago Press, Society of Labor Economists, NORC at the University of Chicago},
timestamp = {2018-09-19T18:10:30.000+0200},
title = {Measurement Error and Misclassification: A Comparison of Survey and Administrative Data},
url = {http://www.jstor.org/stable/10.1086/513298},
urldate = {2017-11-27},
volume = 25,
year = 2007
}