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Activity Number:
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631
- Small Area Estimation: “Producing Estimates for Small Areas from Sampled Data”
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Type:
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Invited
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Date/Time:
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Thursday, August 1, 2019 : 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 #300388
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Title:
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Interpolating Distributions for Populations in Nested Geographies Using Public-Use Data with Application to the American Community Survey
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Author(s):
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Scott H. Holan* and Matthew Simpson and Christopher K. Wikle and Jonathan R. Bradley
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Companies:
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University of Missouri/U.S. Census Bureau and SAS and University of Missouri and Florida State University
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Keywords:
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Bayesian methods;
Functional data;
Multi-scale model;
Small area estimation;
Spatial statistics
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Abstract:
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Statistical agencies often publish multiple data products from the same survey. First, they produce aggregate estimates of various features of the distributions of several socio-demographic quantities of interest. Often these area-level estimates are tabulated at small geographies. Second, agencies frequently produce weighted public-use microdata samples (PUMS) that provide detailed information of the entire distribution for the same variables. However, public-use micro areas usually constitute relatively large geographies in order to protect against the identification of households or individuals included in the sample. These two data products represent a trade-off in official statistics: publicly available data products can either provide detailed spatial information or detailed distributional information. We propose a model-based method to combine these two data products to produce estimates of detailed features of a given variable at a high degree of spatial resolution. Our motivating example uses the disseminated tabulations and PUMS from the American Community Survey to estimate U.S. Census tract-level income distributions and statistics associated with these distributions.
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Authors who are presenting talks have a * after their name.
