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Activity Number: 32 - Measuring the Economy: Economic and Workforce Statistics
Type: Contributed
Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
Sponsor: Government Statistics Section
Abstract #323895 View Presentation
Title: An Optimization Approach to Reconciling Sample Allocations
Author(s): David Piccone* and Matthew Dey
Companies: U.S. Bureau of Labor Statistics and Bureau of Labor Statistics
Keywords: optimization ; stratified sample allocation ; establishment survey ; power Neyman allocation ; minimum allocation ; occupational employment statistics
Abstract:

As part of a larger project, a research team at the Bureau of Labor Statistics (BLS) created an alternative sample design for the Occupational Employment Statistics (OES) survey. There are three sample allocations for the new sample design, each geared towards improving the estimator in different ways. There is an efficient allocation that aims to lower the sampling error of the OES estimates, and two minimum allocations that set a lower sample size threshold for area and industry domains. Each of the three sample allocations are stratified designs, however they use different strata definitions. This paper describes how we reconcile the three allocations using an optimization approach.


Authors who are presenting talks have a * after their name.

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