Author: Glenda Humiston
Definitions of “rural” are not standardized – some programs use definitions such as “communities under 50,000 that are rural in nature,” “areas of less than 2,500 not in census places,” or “Nonmetro County.” In addition to the confusing nature of the definitions, they generally do not relate well with realities of western states and mountainous topography – greatly impacting the eligibility of communities and individuals to access programs. The negative impact of these definitions is especially true for rural communities that have been experiencing inordinately high in-migration from other areas; growth not necessarily due to increased economic opportunity within the region, but rather from lack of affordable housing for low- and middle-income people in nearby areas.
Much of this is due to the historical practice of relying on counties as the jurisdiction for USDA’s field-based agencies. While this has generally worked well in the east and Midwest, it does not make any sense for the western U.S. for the simple reason that our counties are extremely large. For example, San Bernardino County is larger than nine U.S. states1 and is one of the THIRTY California counties that are larger than the state of Rhode Island.
This is not only a problem with current USDA definitions but can be found throughout the federal government in any program utilizing the definition of “Metropolitan” counties administered by the White House Office of Management and Budget. As you can see from the map below, the vast majority of California is considered to be metropolitan – including the entire San Joaquin Valley and Shasta County! However, according to USDA calculations urbanized areas and urban clusters comprise only 5.1% of California’s total land mass2.
During a series of Town Hall Forums held throughout California in 2010, local elected officials, service providers and other stakeholders repeatedly raised this issue. When asked for solutions, key recommendations included
- Utilize census block group data instead of county level data to determine areas of persistent poverty and calculations for all programs.
Several USDA programs maintain set asides for persistent poverty counties3. As can be seen in the map below, California has many areas suffering from persistent poverty – yet not one single county in California is considered to have persistent poverty by USDA! This contrasts sharply with states that have much smaller counties and are able to qualify those areas (easily seen in the previous map). Calculating persistent poverty – as well as eligibility for other programs and allocations – by census tract would improve targeting of finite resources to areas of most need.
- Enable Rural Development programs to support essential community facilities in areas considered non-rural but that serve rural populations.
Hospitals, health clinics, food banks, and social facilities are often located in non-rural areas. The rural definition should be “flexible” to support at least the portion of essential facilities that serves rural people and communities.
- Ensure viability of agricultural support industries regardless of location.
Although agricultural production occurs in rural areas, California’s agriculture is highly diverse and many types of processing and marketing facilities are required in non-rural areas to prepare and deliver products to various domestic and international markets. Program rules need to allow maximum flexibility in ability to support enterprises and facilities that support agriculture in non-rural areas.
- Permanently change the grant calculation of Median Household Income (MHI).
Percentage of grant eligibility for several Rural Development programs is partially dependent on the MHI of the community as a percentage of the state non-metropolitan median household income. Using this criterion in California eliminates most of the rural population from the calculation of the state’s non-metropolitan median household income and includes only the most remote areas that tend to have lower incomes.
- Funds should be allocated to states based on the percent of the population that lives in eligible communities.
Fifty percent of the weight allocating funds under Water and Environmental Program and Communities Facilities Program is based on rural population. This population data comes from census definitions of rural (less than 2,500 population). However program eligibilities under the actual statutes are much higher. Aligning allocations with actual population that is eligible would allow for a much more equitable allocation of funds.
- Programs targeting small and underserved farms must clearly define the target, taking into account the many categories of small and underserved farmers not addressed in current ERS definitions.
The USDA definition of Limited Resource Farmer compares a farmer or rancher’s income to the average within a county so if you are poor in a poor county you are not qualified for priority funding.
- Consider terrain and topography where distance is included in the definition.
The Sierra Nevada, Cascade, and Coastal Mountains are all major land forms and the California coastline is 840 miles long. The distances between two points may seem close if a lineal (as the crow flies) measurement is used; however, actual travel between two points can be much greater distance and quite onerous. California’s land features and road routes must be considered in any definition for rural.
These issues are all part of the ongoing debate as the 2012 Farm Bill is being negotiated. It is important that all citizens become more aware of these challenges and the consequences of any policy enacted.
1 Maryland, Hawaii, Massachusetts, Vermont, New Hampshire, New Jersey, Connecticut, Delaware, and Rhode Island
2 Urban land is based on population density and was delimited using the United States Census definitions of urbanized areas and urban clusters. http://nrs.fs.fed.us/data/urban/state/?state=CA
3 USDA’s Economic Research Service defines counties as being persistently poor if 20 percent or more of their populations were living in poverty over the last 30 years (measured by the 1970, 1980, 1990, and 2000 decennial censuses). While this map only shows data available electronically, it is estimated that additions of the 1980 and 2010 Census data will have little effect on areas shown.