2020 Census Data Products: Data Needs and Privacy Considerations Proceedings of a Workshop (2020) / Chapter Skim
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5 Delivery of Government Services
5 Delivery of Government Services
Pages 59-74
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From page 59... ...
and containing 32 census tracts, 88 block groups, and 1,100 blocks. He noted that planners used decennial census data for a variety of purposes: understanding the composition of their community; understanding the dynamics of community change; evaluating the potential effects of private sector development and the provision of public goods, particularly sewers, parks, highways, and transit systems; and modeling the effects of changes in dynamic systems such as transportation and population.
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He examined the percentage change for this age group at the census tract level from the originally released 2010 Summary File 1 (SF1) compared with the 2010 Demonstration Data Products (DDP)
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Figure 5.1 Percent change between 2010 Census published data and 2010 Demonstration Data Products for selected groups, tracts and block groups in Cambridge, Massachusetts. SOURCE: Clifford Cook workshop presentation.
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The biggest increase in vacant housing was in one of these block groups (in the far northwestern part of the city, which consists of one small private development, one large public housing development, and two even larger privately owned affordable housing developments. The vacancy rate there went from roughly 2 to 3 percent in SF1, which made sense knowing the organizations that run those developments, to roughly 29 percent.
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They were not thinking about differential privacy in the way they were doing their work. 5.2 DECENNIAL CENSUS, RURAL HOUSING DATA, AND DIFFERENTIAL PRIVACY Keith Wiley (Housing Advocacy Council)
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He first aggregated census tracts to states. For total population and total housing units, there was little difference between the originally published 2010 data and the data in the DDP.
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Wiley said that the Housing Assistance Council has done studies to try to assess this risk to rural communities, comparing Section 515 housing units to the balance of occupied renter housing stock. If differential privacy added 400 to 500 units in a place like Pendleton County, West Virginia, this type of analysis would be useless.
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. Jarosz noted another key attribute of regional planning organizations: although they have a transportation planning mandate, they also do other planning work in many states, such as habitat conservation planning, public safety, and in many cases housing planning.
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Jarosz agreed with Cook that vacancy rates are important. Cook showed examples of problematic rates in the DDP by census tract, and Jarosz found
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occupied units must be the sum of all housing units minus vacant units; and (3) average household size must be at least one, and household size multiplied by number of occupied units gives the population in a size category.
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For counts HHi in household size categories of i = 1 person, 2 persons, through 7+ persons, the calculated (minimum) household population must be HHP ≥ (HH1 × 1)
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Housing counts, occupancy and vacancy characteristics, and household size and structure all need to be accurate for very small levels of geography for transportation planning. 5.3.4 Concluding Comments Jarosz suggested that housing occupancy and vacancy either be invariant or have a larger portion of the privacy budget.
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Adopting a kind of Hegelian dialectic, the two concerns that Flaxman has heard from the Census Bureau is whether there will still be sufficient privacy protection if the total count is invariant at the block level and whether this would compromise the accuracy of other statistics. Flaxman believes that the most relevant concern of public health decision makers with regard to differential privacy for 2020 Census data was quality.
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He developed these kinds of graphs to explain the variability introduced by differential privacy in ways that local policy makers could understand by making a comparison with a survey conducted with simple random sampling. Similarly, he developed histograms that with the use of shading illustrated the spread in error and whether error was biased in a positive or negative direction for different aggregations that users need, such as census tracts, cities, counties, states, and blocks with group quarters populations in total and by type such as nursing homes or prisons.
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He experimented with making enumeration district population counts invariant in the 1940 data released by the Census Bureau with a differential privacy algorithm applied to introduce noise and obtained a good result. He repeated his suggestion that the population count be made invariant at the block level or that bias be addressed in some other way and also suggested that the Census Bureau should publish the microdata files (after privatization)
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Yet private data sources that can be purchased are often black boxes, in contrast to the greater familiarity of census data gathering and tabulation processes. Cook hoped that it would be possible to determine roughly how much noise will be infused into the 2020 census data products.
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