Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Elliott co-PI on new study examining how early environment impacts children's health

Levy says ACA has helped increase rates of insured, but rates still lowest among poor

Bruch reveals key decision criteria in making first cuts on dating sites

More News

Highlights

U-M ranked #4 in USN&WR's top public universities

Frey's new report explores how the changing US electorate could shape the next 5 presidential elections, 2016 to 2032

U-M's Data Science Initiative offers expanded consulting services via CSCAR

Elizabeth Bruch promoted to Associate Professor

Next Brown Bag

Mon, Oct 3 at noon:
Longevity, Education, & Income, Hoyt Bleakley

Imputing for Late Reporting in the U.S. Current Employment Statistics Survey

Archived Abstract of Former PSC Researcher

Copeland, Kennon, and Richard L. Valliant. 2007. "Imputing for Late Reporting in the U.S. Current Employment Statistics Survey." Journal of Official Statistics, 23(1): 69--90.

Surveys of economic conditions are often published monthly to provide up-to-date measures of the state of a country’s economy. In establishment surveys, some sample units may not report in time to be included in the current month’s estimates, but eventually do report data. This late reporting can lead to revisions of estimates as more sample data become available. To maintain credibility, it is important that the size of revisions be kept as small as possible. We study this issue using the U.S. Current Employment Statistics (CES) survey. A model-based view of the CES weighted link relative estimator is used to identify potential bias due to model misspecification. An alternative approach, involving imputation for missing data, is used in an attempt to reduce the magnitude of revisions between preliminary and final estimates of employment for a month. The alternative, while not yielding statistically significant improvement in monthly revisions at the industry level, offers the potential for improved estimates for lower level aggregation.

Public Access Link

Browse | Search : All Pubs | Next