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Abstract Details
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Activity Number:
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563
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #301397 |
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Title:
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Two-Stage Bayesian Benchmarking for Small-Area Estimation
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Author(s):
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Malay Ghosh*+
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Companies:
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University of Florida
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Address:
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, , ,
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Keywords:
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Bayes ;
Benchmarking ;
Small Area ;
Two Stage
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Abstract:
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Small area estimates are usually model based, and thus when aggregated, do not typically match the direct estimate for a large geographical area. This often causes concern since the direct estimate for a large geographical area is believed to be quite reliable. In order to address this concern, and possibly also to guard against potential model failure, small area estimates are often adjusted to match the direct estimate for the larger area after aggregation. This is usually referred to in the small area literature as benchmarking. The paper proposes two-stage Bayesian benchmarking with one single model. A simple illustration is where one wants to benchmark the state estimates to the national estimate, and then the county estimates to the corresponding benchmarked state estimates.
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Authors who are presenting talks have a * after their name.
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