Although ERS coded all U.S. counties, the thresholds for the economic and policy types were set using nonmetro counties only. Most thresholds were roughly set at the nonmetro mean plus one standard deviation. ERS used counties that met the 2003 definition of nonmetro (micropolitan and noncore combined) in analyzing the means. The codes are primarily meant to be useful in the analysis of rural conditions, trends, and program needs. ERS coded metro counties to facilitate comparisons across the country. If researchers are solely interested in metro conditions, they should carefully test whether these classifications are meaningful in that context.
Methods for Determining the Economic Dependence Types
Labor and proprietors' earnings by place of work are the basis for the economic dependence categories. Each industry's earnings were calculated as a percent of total labor and proprietors' earnings in the county in 1998, 1999, and 2000. These percentages were summed, and divided by 3 to obtain annual average percentages. This averaging was done to minimize the effects of any one-year anomaly in an industry's earnings. For simplicity, all labor and proprietors' earnings in a county are referred to as total county earnings.
County-level estimates of earnings by place of work used to measure economic dependence came from the Bureau of Economic Analysis' (BEA) Regional Economic Information System (REIS). BEA recalculated state and county earnings for all years in its REIS when it released new 2002 data in May 2004. The years 1969-2001 were revised from the previous release of May 2003. These new estimates incorporate the results of comprehensive revision to the national income and product accounts released December 10, 2003 and to state personal income released April 27, 2004. The revised estimates also reflect new and revised county-level source data.
Selection of the industries ERS classified was guided by regional economics theory. Farming, mining, manufacturing, and Federal/State government industries produce goods or services for export outside the local economy. Exporting industries are termed 'basic' in regional economics and are often shown to be sources of larger growth in local economies (or declines during economic downturns) than industries that produce for the local market. Service industries may either produce for the local or export economies. ERS set a high service earnings threshold to help assure that the counties we classified as services-dependent do have service industries that serve more than the local population. These economic dependence categories are mutually exclusive.
Farming dependence was based on two thresholds-farm earnings accounting for an annual average of 15 percent or more of total county earnings during 1998-2000 or farm occupations accounting for 15 percent or more of all occupations of employed county residents in 2000. The farming occupation option was adopted to allow counties into the farming-dependent group that had highly farming-oriented economies but did not meet the earnings threshold, most often due to negative farm earnings estimates for some or all of the analyzed years. Farming dependence was determined first and takes precedence over all the other economic dependence types.
The final farming-dependent counties differ from the preliminary ones we published in May 2004, based on older BEA data. Nationally, BEA's revised county earnings estimates for farming are 12, 7, and 9 percent higher in 1998, 1999, and 2000 than in the older data release. By State, the revised estimates for those years also differ from the older data, but are not always higher. For example, in 2000, Minnesota's revised farm earnings are 19 percent less than the old estimate while Wisconsin's revised farm earnings are more than twice the old estimate. Even with such large national and State revisions, only 35 counties differ in their final farming-dependent status from their preliminary status. Twenty-seven lost their preliminary farming-dependent status and 8 counties gained final farming-dependent status. Of the preliminary farming-dependent counties, 432 (94 percent) remain farming-dependent in the final codes.
Mining (including metal; coal; oil and gas; stone; sand and gravel; clay, ceramic, and refractory minerals; chemical and fertilizer minerals; and miscellaneous nonmetallic minerals, such as gem stones, diatomaceous earth, peat, and talc) and Federal/State government dependence were also based on the industry accounting for an annual average of 15 percent or more of total county earnings during 1998-2000.
Manufacturing dependence was based on accounting for an annual average of 25 percent or more of total earnings during the 3 years.
Services dependence (including retail trade, finance, insurance, real estate, and services as defined by the Standard Industrial Classification System (SIC)) was based on accounting for an annual average of 45 percent or more of total earnings during the 3 years.
If a county qualified for more than one of mining, Federal/State government, or manufacturing types, it was classified in the industry in which it was the largest number of percentage points above the threshold. Services were not allowed to take such precedence over the other three industries. There were a few counties in which services exceeded its 45-percent threshold by more than other industries exceeded their thresholds. Most of those counties were State university or capital counties where we believe the service industries follow from the Federal/State government industry being concentrated there rather than government following services.
Counties that are not classified as dependent upon any of those industries are termed Nonspecialized. ERS has not explored whether any other particular industry is concentrated in those counties. BEA began reporting industry data by the North American Industry Classification System (NAICS) with its 2001 REIS data. In a few years, we plan to revisit the economic dependence classification, using NAICS industries to do a more detailed analysis of industry concentrations. That analysis will probably leave many fewer nonspecialized counties.
Methods for Determining the Policy Types
The housing stress (2000), low-education (2000), low-employment (2000), persistent poverty (1970, 1980, 1990, and 2000), population loss (1980, 1990, and 2000), and retirement destination (1990 and 2000) classifications are all based on census data from the years in parentheses after their names. The policy type definitions given in 2004 County Typology for all but the housing stress and nonmetro recreation types are sufficiently straightforward that they need no further explanation here (see Descriptions and Maps).
Two of the policy types were created under cooperative agreements. The nonmetro recreation classification was created through a cooperative agreement between Calvin Beale of ERS and Ken Johnson of Loyola University-Chicago. The retirement destination classification was created through a cooperative agreement between Calvin Beale of ERS and Glenn Fuguitt of the University of Wisconsin-Madison.
Housing Stress: The Selected Conditions variable calculated by the Census Bureau and available on 2000 census summary file 3 (table HCT28) was used to measure housing stress. We counted households meeting one or more of the four selected conditions (lacking complete plumbing, lacking complete kitchen facilities, gross rent or selected owner costs greater than 30 percent of household income, and more than 1 person per room) as "stressed" and computed them as a share of the total number of occupied housing units in the county.
Gross rent is contract rent plus the estimated average monthly cost of utilities (electricity, gas, water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter (or paid for the renter by someone else). Gross rent is intended to eliminate differentials that result from varying practices with respect to the inclusion of utilities and fuels as part of the rental payment.
Selected monthly owner costs are the sum of payments for mortgages, deeds of trust, contracts to purchase, or similar debts on the property (including payments for the first mortgage, second mortgage, home equity loans, and other junior mortgages); real estate taxes; fire, hazard, and flood insurance on the property; utilities (electricity, gas, and water and sewer); and fuels (oil, coal, kerosene, wood, etc.). It also includes, where appropriate, monthly condominium fees or mobile home costs (installment loan payments, personal property taxes, site rent, registration fees, and license fees).
Rooms used in computing persons per room include living rooms, dining rooms, kitchens, bedrooms, finished recreation rooms, enclosed porches suitable for year-round use, and lodgers' rooms. Excluded are strip or pullman kitchens, bathrooms, open porches, balconies, halls or foyers, half-rooms, utility rooms, unfinished attics or basements, or other unfinished space used for storage.
Nonmetro Recreation: This classification was originally completed in 2002 and results were published in Rural America . Only counties that were classified as nonmetro by the 1990 census were classified. The classification was updated for this typology by coding the metro counties in 1990 that changed to nonmetro status in 2000. While this is the only typology code that does not apply to all U.S. counties, it can be used to look at nonmetro counties using either the 1993 or 2003 definition of nonmetro.
Data used to create the nonmetro recreation classification were:
- wage and salary employment in entertainment and recreation, accommodations, eating and drinking places, and real estate as a percentage of all employment reported in the Census Bureau's County Business Patterns for 1999;
- percentage of total personal income reported for these same categories by the Bureau of Economic Analysis;
- percentage of housing units intended for seasonal or occasional use reported in the 2000 Census; and
- per capita receipts from motels and hotels as reported in the 1997 Census of Business.
The three variables measuring employment, income, and seasonal housing were converted to z-scores and combined into a weighted index (weights of 0.3 were assigned to income and employment and 0.4 to seasonal housing) to reflect recreational activity. Counties with index scores of 0.67 or higher were regarded as potential recreation counties.
Additional counties were considered to be recreation counties if their value was greater than 0 (the mean of the index) and they had at least $400 per capita of hotel-motel receipts. Inclusion of such counties to the list added some comparatively large counties with a high volume of recreation activity but with urban centers big enough to dilute the percentage of direct recreational income and employment or the proportion of second homes.
Counties were also accepted if at least 25 percent of their housing was seasonal, so long as the index exceeded the mean. Each potential candidate was individually appraised from printed and/or Internet sources and personal knowledge to determine or verify the nature of their recreational function. Fourteen counties that ostensibly qualified, but lacked any known recreational function, were deleted from the list either because they were very small in population with inadequate and misleading County Business Patterns coverage or because they reflected high travel activity without recreational purpose, i.e., overnight motel and eating place clusters on major highways.
All 3,141 counties, boroughs, independent cities, parishes, and other county-equivalents that were enumerated in the 2000 Census of Population and Housing were classified. We did not classify U.S. territory's subdivisions. Colorado created a new county, Broomfield (FIPS 8014), after the 2000 census. It has been added to the data file and coded the same as Boulder because the largest share of Bloomfield's population resided in Boulder County (56.1 percent) at the time of the 2000 census. Adams County had 39.82 percent of Bloomfield's population then, Jefferson County had 4.05 percent, and Weld County had 0.03 percent.
The following Virginia independent cities and counties were analyzed as combined units, then each component was assigned the combined unit's code.
|These independent cities:
||Were combined with these counties:
||James City (County)