A Center for Technology-Based Decision-Making in the Economics of Rural Education

This project is a collaboration between Tennessee State University's Department of Agricultural Sciences, Applied Geospatial Information Systems Program and the Center of Excellence for Learning Sciences.

Funding Agency: U.S. Department of Agriculture/Cooperative State Research, Education, and Extension Service, Grant #2006-38814-17538.

Principal Investigators: Dr. Robert E. Harrison and Dr. Gary L. Peevely.

Project summary: Efforts have been made to fund education from public sources since the early years of this nation. The current philosophy, set in 1906, continues to be implemented as statewide policy and as such, continues to place rural schools and school districts at a distinct disadvantage. It is evident by the repetition of litigation in many states that the minimalist philosophy prevails even as courts mandate equal and adequate funding. The goal of this research is to make available expanded rural economic opportunities by providing adequate and equitable education processes for all school children and youth in rural areas of the United States. To achieve this goal, practitioner knowledge of the economics of rural education funding must be enhanced in order to add value to decision making processes and the implementation of sustainable methodological solutions. This project will apply cutting-edge technologies (e.g. GIS, econometrics, knowledge management) to the resolution of a problem that has remained persistent for the past 100 years. Objectives of the project are to: (1) develop a technology based model for analysis of rural economics of education; (2) develop alternative geospatial modeling of funding rural education; (3) develop a rural education econometrics knowledge management model.

Project background: In many states and local areas, it has become painfully evident that a community’s long term economic health rests, in part, on the presence of young people with strong modern workforce skills and solid educational credentials. Beaulieu & Israel (2005) indicated that community practitioners agree that the long term prosperity of places is closely linked to two key elements; the ability to promote the educational advancement of young people and the capacity to create local economic opportunities that successfully retain or attract talented well-educated youth.

Employers today, particularly in manufacturing, are attracted to rural areas that offer pools of well-educated and skilled labor. Counties tied to a low-skill labor force, are finding that changing production technologies and overseas competition severely limit the prospects for employment growth. Low education levels continue to pose a challenge for many rural counties seeking economic development. Technological innovation alters demand in favor of better educated workers because they have a comparative advantage in implementing new technologies (Lichtenberg, 1987). This is evident in agriculture where production per man hour has historically increased due to continued implementation of new technology. On the other hand, the decline in nonagricultural industries in rural America relates directly to poverty in rural communities. The farm population is only 10% of the rural population so the rural poor continue to be mostly non-farmers (Ropers, 1991). Most of the rural population relies on nonagricultural industries as a base for the economy. In many rural areas there is a scarcity of retail and manufacturing industries, resulting in dwindling incomes, rising unemployment, and populations leaving rural areas (Miller 1998). According to Quigley (2000) transfer payments to individuals in rural areas have been on the rise for 15 years and now comprise 19% of all rural income.

Non-metro communities must find the means to increase the share of college educated workers in their labor force – many of the highly educated in rural areas are natives that attended college locally or returned home after completing college (Gibbs R.M. 1998). There is evidence that the gap between urban and rural areas has increased in terms of education, cognitive skills and work experience (ERS 2005). However, the funding of rural education is many times dependent upon the levels and methodology of funding metropolitan and micropolitan districts as well (Jones et al 2005).

Education funding and achievement are related to regional economic development (S. Barro 1994). Rural communities view increased educational investments as an important component of their economic development strategy in an economic environment that stresses competitiveness in international markets and adaptability to sophisticated technologies. Gale and McGranahan (2002) argue that the current business environment in rural regions suffers from, among other things, a weakness in the quality of schools. They recommend investments in good schools and programs to upgrade skills of the current workforce.

A number of characteristics can be used to describe the rural poor. One-fourth of the rural poor live in the Midwest, one-third live in the South, 14.5% live in the West, and 7% live in the Northeast. Of the rural poor, 44% are African Americans. Of those counties that have been labeled by the Census Bureau (2000) as ‘Persistently Poor’, 340 of the 386 (88%) are non-metro. Of non-metro counties, the Census Bureau (2000) indicates that 18 % are persistent poverty counties, versus only 4% of metro counties.

An example of persistent rural poverty can be found in the region known as the southern Black Belt. The Black Belt is comprised of 623 counties across 11 states, including one of every five counties in the nation, and is home to 34% of the nation’s population. Black Belt school districts are predominately rural and spend less per pupil on instruction than non Black Belt Districts. When student assessment outcomes are examined, the Black Belt has the lowest aggregated scores of any other region in the nation. A minority rural youth in the Black Belt is four times more likely to live in poverty than a minority youth in any urban area. Thirty-eight percent of all adults residing in this area are without high school diplomas. The impoverishment of the rural Black Belt is of such magnitude that if the quality of life there did improve, it would substantially improve the well-being of the nation as a whole (Wimberly & Morris, 1997). Because today’s global economy puts a premium on a highly educated, adaptable labor force, such an undereducated, underdeveloped region as the Black Belt can be a significant drain on the regional and national economy (Calhoun, Reeder, & Bagi, 2000).

Raising education levels, and the quality of that education, are an essential part of a successful strategy to improve the economic life of rural communities and the well-being and quality of life of the rural population.

Efforts have been made to fund education from public sources since the early years of this nation. The current tone for funding rural and urban schools was set in 1906 by the research of Ellwood Cubberly who wrote, “theoretically all the children of the state are equally important and are entitled to have the same advantages; practically this can never be quite true. The duty of the state is to secure for all as high a minimum of good instruction as possible.” The philosophy also continued to be implemented as statewide policy and as such, has continued to place rural schools and school districts at a distinct disadvantage. It is evident by the repetition of litigation in many states that the minimalist philosophy has prevailed even as courts mandate equal and adequate funding. Most states rely on the fiscal capacity theory of local areas to determine the extent to which state funds are redistributed to support local education (Georgia Future Communities Commission 1996).

However, rural school districts face unique problems and challenges because of their (usually) small student population, the large physical areas they often serve, their constraints in attracting and retaining high quality staff, and their unique tax bases, often concentrated on agricultural property (Ward 2003). In addition, Porter (2004) found that rural regions are in many cases tightly linked to nearby metropolitan regions and approaching rural regions as self contained economies will obscure policy choices. Additionally, the economic gap between rural and urban areas seems to be widening.

In rural areas the main component of local education funding is derived from real estate and/or property taxes. In a selected review of revenues and expenditures across all counties in five states; Arkansas, Georgia, Tennessee, Virginia, and Wyoming, the authors of this proposal found the greatest expenditure of local government revenue in rural areas was for the support of public education. This is happening at a time when property values are increasing at a much higher rate than personal incomes. This valuation of property and the complex interaction of property taxation and current education funding formulae have continued to vex policymakers and rural landowners alike. In addition, the problem has become one of the major contributions to the conversion of agricultural croplands to other uses when the value of the land and subsequent taxes become determining variables in the production function.

The conundrum in rural areas is that of providing adequate high quality education services by utilizing taxation based on the value of the rural lands. As the continued valuation of lands occurs, the taxation continues to increase. When education expenditures are equalized by litigation or policy, this tends to place an added burden on rural landowners when additional revenues are required under the concept of fiscal capacity.

The methodology of providing funding for local schools has not changed appreciably during the last century. However, in a time of increasing Federal accountability (No Child Left Behind) and continued state litigation that has transcended from equity of expenditures to a concept of adequacy, the impact of increasing expenditures and taxation on rural economics and quality of life remain undetermined.

To date, forty five of the fifty states have experienced litigation in the area of education finance. Many of these states have experienced continuations of these actions for more than twenty years. This question of determining the equity and now primarily the adequacy of expenditures has evolved into three predominant models of assigning a cost to the process. These models are used by those determined to be experts by plaintiffs and defendants alike in the litigation for equitable and adequate education expenditures. According to the National Conference of State Legislatures (2004), these three models are 1) the professional judgment model, 2) the successful schools model, and a more traditional 3) statistical model. The application of each methodology results in a cost figure that is said to be adequate. In addition to a base per pupil cost figure adjustments are made to accommodate special needs, at risk and students with other characteristics. The following models have been implemented by policy in most states and as such impact rural economies and the quality of rural life.

Professional Judgment Model: This was one of the first and probably one of the most enduring methods of attempting to configure policy to provide adequate revenues for education processes. Originally devised to make school district cost adjustments, this model uses the recommendations from a panel of experts to define the necessary components of an adequate education (Chambers and Parrish, 1994). The group of experts usually is comprised of education-related professionals (teachers, administrators and policymakers). The group decides what inputs are needed in terms of staff, equipment, programs and so forth to meet state educational standards. These inputs then are cost out to produce an “adequate” education funding level in a given state. Although the Wyoming Supreme Court (1995) upheld the results of the professional judgment approach, difficulties still remain with this methodology. The main problem results from possible inconsistencies arising between different expert panels (Duncombe and Yinger, 1999). The model has been shown to be inconsistent and therefore not research valid.

Successful Schools Model: This model examines all schools or districts in the state, identifies the ones that are meeting state standards, and then considers the amount that those schools are spending as an adequate education funding level. According to John Augenblick, the developer of the method, "The underlying assumption is that any district should be able to accomplish what some districts do accomplish" (Augenblick, 1997). According to the National Conference of State Legislatures (NCSL), one criticism of the successful schools model is that it bases its recommendations on a finite set of performance characteristics and does not account for the full scope of educational outcomes. Another problem with the method is that the proficiency data employed do not account for differences in student characteristics (Guthrie and Rothstein, 1999). The No Child Left Behind (NCLB) policy uses the conception of adequate yearly progress in determining the degree to which schools are increasing performance. (NCSL 2004) States with large percentages of rural population, such as Vermont have had difficulties in compliance with NCLB.

Statistical Model: Another more historical yet evolving model used to determine adequacy is the statistical model. This approach is the most technically complex attempt to define adequacy and, as a result, has been applied only in limited settings. The underlying philosophy of statistical models is that, with enough data about education expenditures and student characteristics, statistical techniques should be able to isolate the effects of different types of inputs and arrive at a base cost of adequacy education (Duncombe et al, 1996). Statistical models can be adjusted to account for student characteristics, environmental factors and other variables of a locality. These variables then are reintroduced to arrive at the cost of an adequate education in a particular school. The statistical model draws conclusions about the differences in cost associated with special populations to arrive at a base level of funding. This results in the ability to accurately estimate the differences in resource needs between different educational settings. The approach promises that, with increasingly comprehensive data being collected in educational settings and with more refined statistical techniques, it will be possible to define an accurate measure of the cost of educational adequacy. The main critique of the statistical model has been that the techniques are simply not understandable to the average lawmaker. A statistical model utilized in education funding research is inherently a complex system. As such the model / system is one whose component parts interact with sufficient intricacy that they cannot be predicted by standard linear equations; so many variables are at work in the system that its overall behavior can only be understood as an emergent consequence of the holistic sum of all the behaviors embedded within. However, experience shows that policy decision makers are unwilling to act on a methodology that they do not understand (the "black box" problem) (Guthrie and Rothstein, 1999).

Economists understand that in our changing world economy, the economic standard and well being of a place is dependent on those in proximity to that place. Porter (2002) in the identification of economic clusters is a prime example. Utilizing a geospatial information system and integrating such techniques as geographically weighted regression will give decision makers charged with funding rural education a much better grasp of impacts and alternatives in this process. The proliferation of web-based communication will allow ubiquitous access to the information and processes generated by this research.

References:

Augenblick, J., Determining Base Cost for State School Funding Systems. Denver, CO: Education Commission of the States Issuegram, 1997.

Augenblick, John, "Calculation Of The Cost Of An Adequate Education In Maryland In 1999-2000 Using Two Different Analytic Approaches Prepared For Maryland Commission On Education Finance, Equity, And Excellence (Thornton Commission)," prepared by Augenblick & Myers, September 2001.

Augenblick, John, Recommendations for a Base Figure and Pupil Weighted Adjustments to the Base Figure for Use in a New School Finance System in Ohio, Report presented to the School Funding Task Force, Ohio Department of Education, 1997

Campbell County School District v. State, No. 94-136, No. 94-137, No. 94-138, No. 94-139, No. 94-140, Supreme Court Of Wyoming, 907 P.2d 1238; 1995 Wyo.

Chambers, J., and Thomas Parrish, "State Level Education Finance," Cost Analysis for Education Decisions: Methods and Examples. Advances in Educational Productivity, Volume 4, W.S. Barnett, ed. Greenwich, CT: JAI Press, 1994.

Chambers, Jay, Public School Teacher Cost Differences Across the United States, NCES Working Paper 95-758, Washington, D.C.: U.S. Department of Education, Office of Educational Research and Improvement, 1995.

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Duncombe, W., J. Ruggiero, and J. Yinger, "Alternative Approaches to Holding Schools Accountable," Holding Schools Accountable, H.F. Ladd ed. Washington, D.C.: The Brookings Institute, 1996, pp. 327-356.

Duncombe, William D., and John M. Yinger, "Performance Standards and Educational Cost Indexes: You Can't Have One Without the Other," Equity and Adequacy in Education Finance: Issues and Perspectives, Washington DC, National Academy Press, 1999, p. 271.

Duncombe, William, "Estimating the Cost of an Adequate Education in New York", Center for Policy Research Working Paper No. 44, The Maxwell School. Syracuse, NY: Syracuse University, February 2002.

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Guthrie, James W., and Richard Rothstien, "Enabling 'Adequacy' to Achieve Reality: Translating Adequacy into State School Finance Distribution Arrangements," Equity and Adequacy in Education Finance: Issues and Perspectives, Washington DC, National Academy Press, 1999, p. 215.

Guthrie, James, G.C. Hayward, J.R. Smith, R. Rothstien, R.W. Bennett, et all, A Proposed Cost-Based Block Grant Model for Wyoming School Finance, Sacramento, CA: Management Analyst & Planning Associates, L.L.C, 1997.

Hanushek, Eric A., "The Economics of Schooling: Production and Efficiency In Public Schools," Journal of Economic Literature, Vol. 24, 1986, pp. 1141-1146.

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Rose v. Council for Better Educ., No. 88-SC-804-TG, Supreme Court of Kentucky, 790 S.W.2d 186; 1989 Ky.