Abstract
Kirk Mueller, George Stamas, and Shail Butani
(1995) "Nonresponse Adjustment In Certainty Strata For An
Establishment Survey," Proceedings of the Section on
Survey, American Statistical Association.
The Current Employment Statistics survey is conducted by
the U.S. Bureau of Labor Statistics and State Employment
Security Agencies to produce monthly estimates of employment,
hours and earnings by industry for the U.S., States, and
areas. This establishment survey is currently undergoing a
redesign. Sample design research indicates that a simple but
well executed probability design could considerably reduce
mean squared error compared to samples selected using the
current realized sampling rates. What this research has not
considered is that the realized sampling rates are not
deviations from a more optimum design as much as they are the
result of low participation rates when units are first
solicited for the survey, particularly among units in the
largest employment size classes. This research compares bias
of estimators resulting from nonresponse adjustment using
information available on these nonparticipants from
administrative records from the State Unemployment Insurance
(UI) programs for earlier months, with more traditional
survey methods. In other words, unlike most other studies, in
this research we do not assume nonrespondents to be missing
at random. For this study, we can evaluate the effectiveness
of various imputation procedures since responses for every
month for every unit are available from the administrative
records consisting of UI accounts.
The data used in this study are discussed in Section 2. This
will include a brief discussion of the CES survey and our
test population. Section 3 presents the methods used in the
various imputation routines. Section 4 describes the
evaluation criteria used to analyze the results. Section 5
contains our results and comparisons of the imputation
methods. Conclusions from this paper are contained in Section
6.
Last Modified Date: July 19, 2008
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