Activity Number:
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179
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Survey Research Methods Section
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Abstract #318661
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Title:
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Bayesian Decision Theory for Further Optimizing the Use of Administrative Records in the Census NRFU
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Author(s):
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Yves Thibaudeau* and Darcy S. Morris
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Companies:
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U.S. Census Bureau and U.S. Census Bureau
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Keywords:
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Administrative Records ;
Propensity ;
Backward Induction ;
NRFU ;
Decennial Census
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Abstract:
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Morris, Keller and Clark (2016) show how to identify reliable administrative records for enumerating the occupants of housing units in the context of the U.S. Decennial Census Non-Response Follow-up. We propose using Bayesian decision theory to extend the approach of these authors and account for costs and response propensities of field follow-ups. We elicit a loss function that emphasizes the importance of a correct enumeration for each unit. We exploit the properties of the loss function to make decisions between conducting new field follow-ups and utilizing administrative records to complete an enumeration. This leads to a general Bayesian decision theory problem. We attempt approximating the Bayes (optimal) solution of this problem through a version of "backward induction" (DeGroot 1970; Brockwell Kadane 2003). We give explicit formulas applicable to specific situations and derive possible strategies.
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Authors who are presenting talks have a * after their name.