10

Statutory Requirements and Resource Allocation

Although there was not a session devoted specifically to this topic, the issue of statutory requirements to use decennial data was a frequent refrain. As a result, this chapter captures themes that emerged over the course of the two days of presentations, discussions, and remarks. As many speakers implored, accurate decennial data impacts resource allocation at various levels of government.

STATE AND LOCAL LEVELS

Mary Craigle (Montana Department of Commerce), serving as discussant for one of the sessions, framed her comments as her perspective as the chair of the State Data Center. She stated that her remarks would not focus on metrics, but on people and state and local governments that use references to Demographic and Housing Characteristics (DHC) values. When legislators reference census data, they often are ignorant or lack knowledge about these data, where they come from, and how they are developed. Although they are using these values, they may not have the expertise to gauge whether the value is fit for use. In Montana, there are also some timing issues that cause some real problems.

Craigle referenced a 2017 Census Bureau publication, “Uses of Census Bureau Data in Federal Funds Distribution.” She noted that this paper provides 132 examples of funding for programs from census figures. The funding formulas for these programs impact decisions about resource allocation: formula grants for rural areas; youth homelessness demonstration programs;

payments to agricultural experiment stations under the Hatch Act; and the Indian Housing Block Grant program.

Montana statutes and administrative rules use decennial figures to set eligibility criteria and funding allocation in areas such as the following:

• Disposition of gasoline and vehicle fuel taxes (MCA § 15-70-101);
• 9-1-1 system funding (MCA § 10-4-101);
• Public library state aid (MCA § 22-1-327);
• Apportionment of funds to the Urban Housing System (MCA § 60-3-211);
• Distribution of liquor tax for financial assistance (MCA § 53-24-206);
• Branch banking location limitations (MT Rule 2.59.902);
• Urban hospital (MT Rule 37.86.2901); and
• Limits on the compensation of a mayor, city council members, and city employees (MCA § 7-3-4255 as defined by § 7-1-4113).

Craigle concluded by noting that the Montana legislature only meets every other year for 90 days, so statutes that reference decennial or other census data cannot be adjusted to different metrics outside of this time frame without calling a special legislative session.

Additional speakers raised similar concerns during their presentations. Joel Alvarez and Erica Maurer (New York City Department of City Planning) emphasized that inaccurate data impact the allocation of city services. Regarding planning and resource allocation in Northern Virginia, Jill Kaneff’s presentation pointed out that the impact of accurate local and regional data is felt in communities when it determines whether new facilities, such as schools or fire stations, are needed.

RURAL COMMUNITIES

Tom Mueller (University of Oklahoma) noted that demographers do not analyze data at the total level where the data are reliable. Instead, population counts are used by agencies in policies to determine resources, and a lot of people use the decennial census as their denominator. Similarly, Julia Cho (U.S. Department of Agriculture [USDA]) discussed statutory requirements, noting that USDA program eligibility is defined by population using the decennial census data and other criteria. For example, the community facility program invests in rural areas below 20,000 population, and the water and environmental program invests in rural areas below 10,000 population.

LEGISLATIVE REQUIREMENTS IN TEXAS

Helen You (Texas Demographic Center) explained that Texas law requires that the Demographic Center produce annual population estimates and biennial population projections. You stated that estimates and projections of their programs are used by more than 500 entities per year. Some of the public agency users include the following:

• Governor’s Office (for numerous purposes);
• Legislative Budget Board (for budget planning);
• Legislative Council (for redistricting planning);
• Comptroller’s Office (as a basis for their estimates for regions);
• Texas Department of Transportation (for facility, route, and highway construction planning);
• Texas Water Development Board;
• Texas Department of State Health Services (to increase accuracy of their service projections);
• Texas Economic Development Council;
• Numerous other state agencies and public organizations; and
• Numerous county judges and other local officials (for redistricting and other purposes).

These data in turn are used by public agencies as denominators for calculating prevalence rates for many subjects.

SCHOOL ENROLLMENT FORECASTING

Reliance on decennial data for school district resource allocation was a recurrent theme in several sessions. Sarah Radway (Tufts University) and Miranda Christ (Columbia University) emphasized that in population estimates for children ages 4–5, used for kindergarten planning, the utility of census data is critical because inaccurate data may lead to insufficient allocation of resources. Doug Geverdt (National Center for Education Statistics) also offered observations about the necessity of school district geography, which is currently not prioritized with DHC demonstration data.

Ethan Sharygin (Portland State University) provided several use cases during “Use Cases Part I,” stating that he found 53 citations in statutes for decennial census data and 74 additional citations in state administrative rules where population data were used for a particular program or policy. One of his use cases discussed in Chapter 6 focused on school enrollment forecasts in Oregon as required by statute (ORS 195.11). He explained that the statutory requirement is for every school district above a certain size

to conduct long-range planning to inform things such as bond issuances: 57 of 211 districts met this requirement. The Population Research Center where Sharygin works completes the enrollment forecasting for a number of districts in Oregon.

CASE STUDY OF TAXATION ALLOCATION

Amy O’Hara (Georgetown University) offered an example to illustrate when a legal mandate requires population estimates to distribute tax proceeds (RCW 54.28.055). The Washington State Office of Financial Management produces annual population estimates for incorporated places, unincorporated areas, fire protection districts, and library districts within the Thermal Electric Generating Facility Area. The boundary is defined as lying within 35 miles of the most commonly used entrance of the Columbia Generating Station and is south of the southern boundary of the township 15 miles north.

This is a concrete example of how taxes are disbursed and that would require custom geography. Some of the areas within the radius of the power station are off-spine geographies, such as fire protection districts. O’Hara stated these user-defined areas have become very challenging now because the block-level data are unreliable. However, it does not change the fact that one needs data to come up with these population estimates. O’Hara referred to these as “problem blocks” and provided another example of Benton County, which is one of the counties with fire protection districts. Some of these areas are the “impossible blocks” that have no occupied units but positive population. The Census Bureau has already said, “Don’t use these blocks,” but, as O’Hara explained, some users have to use blocks.