Examining Rural Unemployment

A serious problem facing many rural communities is unemployment. With the decline in the farm population, closing of businesses, and temporary or permanent layoffs in industry, families face the situation of having one or both of the wage earners without employment.

Extension can be a valuable resource in helping communities tackle this problem. The response, however, is often reactive, such as helping the unemployed and their families cope with the problem. This article describes a recent Iowa research project that demonstrates a more proactive role Extension can play in addressing the rural unemployment problem.¹

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... This article describes a recent Iowa research project that demonstrates a more proactive role Extension can play in addressing the rural unemployment problem.

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Uniqueness of Rural Unemployment

Problems

Official unemployment statistics are calculated with formulas. The information base used to estimate unemployment is unemployment compensation claims. These claims may be adequate in urban, industrial settings, but they're less meaningful in rural areas because self-employment and farming are major occupations that frequently don't qualify for unemployment compensation.

A second problem of current estimating procedures is in the formulas used. The formulas were developed from base-line surveys conducted nearly two decades ago. Since then, the industrial mix and employment patterns of rural and urban areas have changed radically, but the formulas haven't adjusted to reflect those changes. Experts on employment and unemployment statistics contend the 2 formulas have a bias favoring the urban, industrial areas.²

Finally, the problem of the discouraged or chronically unemployed further reduces the validity of rural unemployment statistics. Unemployment rates rely on estimates of the total work force. Standard measures of the work force include those who are working (the employed) and those who are actively seeking a job (the unemployed). However, when a person quits actively looking for a job, he/she is no longer considered a member of the work force.

In rural areas, where access to an employment office is limited or requires greater expenditure of resources (longdistance travel or long-distance phone calls), the worker, depressed after many unsuccessful tries, may eventually quit checking with the employment office. This operational definition of actively seeking employment also ignores the informal network that characterizes rural areas where job openings are passed along through family and friendship networks.

Negative Consequences

There are two major negative consequences of the underestimation of rural unemployment. The most direct consequence is the inability of the rural community to attract new prospective industries and employers. A low unemployment rate shows that most residents have a job and, hence, that only a small labor pool is available.

The second consequence of unreliable unemployment data is the rural bias created in the distribution of state and federal funds. Many of the funds available to communities for industrial development, job training, and other development programs use the unemployment rates as a primary indicator of "need." When reported rates underestimate the number of unemployed, the area is disadvantaged in qualifying for and receiving its equitable share of public monies.

Methodology

In January, 1982, local leaders and the Extension staff in an 8-county region in southern Iowa initiated a discussion on their perceptions of the unemployment problem in the region. Through meetings of the Extension staff, Extension Councils, and community leaders, local citizens expressed the need for increasing employment opportunities for the seemingly growing number of unemployed. They soon discovered, however, that the official rates of unemployment were generally low, ranging from 3% to 7% across the 8 counties. The question they raised with the state Extension staff was, "Is our perception of the unemployment mentsituation in our region wrong, or is the official unemployment rate in error?"

Based on local input and consultation with Iowa State University researchers, a needs assessment study was proposed to the community leaders in the eight counties. The survey would provide not only answers to their questions about the level of unemployment, but also information useful in obtaining financial assistance from government sources and recruiting new employment opportunities. Extension partially funded the study and each of the counties agreed to provide some funding and recruit volunteers to collect the data.

A random sample of about 390 households was selected from each county. More than 200 local resident volunteers received training on how to conduct telephone interviews and carried out the data collection. Work history information was obtained for each adult eligible for the labor market (16 years and older) in the households. All data were collected during the same time as the monthly official rates were calculated so a direct comparison could be made. Data processing and analysis were done by the state Extension staff.

Findings

The sample size for the entire region was 3,125 randomly selected households. After adjusting for vacant households, the sample was reduced to 2,744 households. A completion rate of 67.8% was obtained by successfully contacting 1,861 households.

Living in these 1,861 households were 3,733 individuals 16 years or older eligible for the labor force. Of those individuals eligible for the labor force, 1,916 were employed, 402 were unemployed, and 1,415 were retired or disabled or, for other reasons, not considered part of the labor force.

Based on these data, the 17.3% unemployment rate across the 8-county region was computed this way:

402 (number unemployed) / 2,318 (1,916 employed + 402 unemployed) = 17.3% (unemployment)

By using the same formula for the computations, computed unemployment rates for the 8 counties ranged from 14.3% to 20.2%. During the same time these data were collected, the official reported unemployment rates for the 8 counties ranged from 4.7% to 7.9%, with an area unemployment rate of 6.5%.

Study Benefits

The most obvious benefit of the study was documenting the bias in official government unemployment statistics that works to the detriment of rural areas. These findings are important to the communities' efforts in attracting new industry and employers. They indicate an available labor force that's willing to go to work.

Secondly, the data are being used to help communities in the area gain state and federal resources to address the problem -manpower training, industrial recruitment, and development grants. A series of workshops has been organized in the communities to help them understand the data and how to use them in efforts to recruit industry and employers and to secure state and federal resources.

Another important benefit of this study was the spirit of cooperation and synergism instilled in the local communities by cooperatively addressing a locally relevant problem. The linkages established between communities, organizations, and residents in working together on a common problem will facilitate future cooperative problem solving. This participatory model of research will have long-lasting impacts through building capacity to analyze and act on local problems. The project demonstrates a more proactive role for Extension in future activities that warrant additional consideration.

Postscript

The benefits of this project can be shown in the activities that have occurred since the survey. In the past 12 months:

• Numerous community meetings were held in each of the counties to discuss the findings and the implications of the findings and to explore strategies to provide additional employment opportunities.
• A 30-minute television program on rural unemployment was produced and subsequently aired on several television stations around the state.
• Several media interviews publicized the project and what the communities are doing to attract new jobs.

While it's difficult to evaluate the effectiveness of the project, several promising developments have occurred or are in process. A $500,000 federal water treatment proposal is very close to f inal approval. Without the study, the application for the funds couldn't have been made because the funds were earmarked for regions with unemployment in excess of 10%. In the past few months, two new manufacturing plants have announced their intention to locate in the area. Initially, these 2 plants will create 50 new jobs. In addition to these accomplishments, several other economic development grant proposals are being written.

In summary, the project is responsible for creating awareness of the need for additional employment and stimulating the communities to work together in solving their problems. We feel certain this project between the communities and Extension will generate other economic development activities.

Footnotes

1. Journal Paper Number J-11323 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 2550.


2. For additional readings on the inadequacies of traditional measures of umemployment, see Donald W. Ickstadt, "Needs for Rural Labor Market Information at the Local Level," in Labor Market Information in Rural Areas, Collette Moser, ed. (East Lansing: Michigan State University, Center for Rural Manpower and Public Affairs, 1972), 25-31 and Peter F. Korsching and Stephen G. Sapp, "Unemployment Estimation in Rural Areas: A Critique of Official Procedures and a Comparison with Survey Data," Rural Sociology, XLIII (Spring, 1978), 103-12.