2020 Census Data Products: Data Needs and Privacy Considerations Proceedings of a Workshop (2020) / Chapter Skim
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6 Business and Private Sector Applications
6 Business and Private Sector Applications
Pages 75-84
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, who discussed the specific use cases of estimating housing in floodplains and benchmarking existing home sales. Floor discussion followed their remarks.
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Brummet noted that survey weighting relied on accurate population benchmarks, and any error in the census population totals would propagate to other products such as the postcensal population estimates and the American Community Survey (ACS)
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It would be preferable to construct on-spine geographies in as functional and effective a way as possible in order to optimize the noise-injection procedures for geographies of interest to data users. 6.2 CENSUS DIFFERENTIAL PRIVACY AND PRIVATE SECTOR DATA PRODUCTS Ken Hodges (Claritas)
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With Table 6.2, Hodges spotlighted two example outliers in terms of differences between the 2010 Census tables and the 2010 DDP in persons per household or average household size: a block group in Maine that saw its population per household diminished to near 0 and another in California that jumped from 2.3 to 99.0 persons per household. He recited other such phenomena: a block group in Louisiana with four people total in the original 2010 data, 0 people in group quarters, three housing units, and two households, so that persons per household equaled two.
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group quarters population must be less than or equal to total population; (4) household population must be greater than or equal to family households times two because every family household had to have at least two people; and (5)
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Claritas would want to remain as a strong advocate for the Census Bureau and for census data and looked forward to remaining engaged with the Census Bureau throughout the process of developing differential privacy protection algorithms for the 2020 Census data.
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Moving forward, NAR would want to update these floodplain weights with the 2020 decennial housing unit counts at the block level and the latest maps provided by FEMA. 6.3.2 Benchmarking Existing Home Sales Evangelou explained that NAR's data on existing home sales, monthly and annual, have been developed from a sample of multiple listing service sales.
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Hodges said that this question was very important for Claritas because so many of its business users wanted data aggregated to areas, such as a 20-minute drive time around a store, which by definition were off-spine geographies. That capability was critical for Claritas products, which was why Hodges and Burgoyne focused on whether the small-area data summed exactly to larger-area totals in the DDP.
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observed that Hodges had been in the information business for a long time and was very forthcoming and transparent about Claritas' data products, but some of Hodges' colleagues in the private sector had not met such a high standard. O'Hare asked if Hodges had any advice for people as to what kinds of questions they should ask when someone tried to sell them data that were "better than the census." Hodges replied that the solution used to be simple, which was to ask the prospective data supplier if they were building from the decennial census numbers or the Census Bureau's population estimates.
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