Cover Page PI#1 David L. Debertin PI#2 Stephan J. Goetz Project Summary In this project, we identify forces influencing survivability of rural micro-regions, with a particular emphasis on identifying and analyzing factors that have driven population and other measures of economic growth in rural regions in the U.S. over the past 15 years. This study takes advantage of some new work by the Department of Commerce (February, 1995) which divides the US into 348 multi-county regions each containing one or more cities at the core surrounded by a less densely populated rural area. A major focus of this research is to identify the forces that have played a role in determining whether a rural region is vibrant or in decline, and a number of basic hypotheses are to be tested in this analysis based on the new CEA micro-region definitions are central to this study. Among these are hypotheses linking the structure of agriculture to economic growth or decline within a region, and hypotheses which examine how urban areas shape the economies of the surrounding rural areas. Table of Contents Project Summary Form (CSRS 1232) . . . . . . . . . . . . . . . . . . . . . . 1 Project Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Rationale and Significance . . . . . . . . . . . . . . . . . . . . . . . . . 3 Past Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Research Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 References to Project Description. . . . . . . . . . . . . . . . . . . . . .13 Facilities and Equipment . . . . . . . . . . . . . . . . . . . . . . . . . .16 Collaborative Arrangements . . . . . . . . . . . . . . . . . . . . . . . . .16 Vita, Dr. Debertin . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 Vita, Dr. Goetz. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20 Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 Budget Justification . . . . . . . . . . . . . . . . . . . . . . . . . . . .27 Justification for Equipment Expenditures . . . . . . . . . . . . . . . . . .27 Current and Pending Support. . . . . . . . . . . . . . . . . . . . . . . . .28 Conflict of Interest Lists . . . . . . . . . . . . . . . . . . . . . . . . .30 Project Summary Form Forces Affecting Changes in Population and Economic Growth in Rural Areas: A CEA Micro-Region Approach Project Description Introduction What causes some rural regions to grow, while others remain stagnant or even experience economic decline? In this project, we identify forces influencing survivability of rural micro-regions, with a particular emphasis on identifying and analyzing factors that have driven population and other measures of economic growth in rural regions in the U.S. over the past 15 years. This study takes advantage of some new work by the Department of Commerce (February, 1995) which divides the US into 348 multi-county regions each containing one or more cities at the core surrounded by a less densely populated rural area. The counties in each of these "Component Economic Areas" or CEA micro-regions are not only geographically linked: each CEA micro-region is also linked by shopping and work-commuting patterns, socially and culturally. These CEA regions provide the basic geography with respect to how people relate to and link with each other within each part of the US. The vitality of rural counties in each micro-region may depend on economic activity taking place at the urban core. In addition, the urbanized areas of many of these regions may be dependent on the success or failure of primary economic activities occurring in the more sparsely populated areas outside the core city. This is particularly true for those regions that are heavily dependent on a single industry for economic growth--often either production agriculture or energy extraction of coal and oil. We believe that the ideal rural micro-region is one that not only has a viable and diversified economic base but also a stable if not increasing population. We have already calculated the rates of population change for each of the 348 CEA micro-regions and ranked the regions accordingly. From this very basic analysis, it is clear to us that the regions that have been heavily dependent on agriculture or energy extraction as a primary source of wealth have lost ground in comparison with other regions that have a more diversified economic base. Much has been written about the potential impacts on economic growth of rural regions of the "structure" of agriculture. The structure of agriculture is defined as the size and number of farms in a region and the percentage of output accounted for by each size category. In our analysis, we want to pay particular attention to how this structure of production agriculture has influenced changes in population and economic growth in regions of the US that contain a substantial rural population. We believe that in the CEA micro-regions with diversified economies and considerable potential for off-farm employment, farms will tend to be smaller, but the non-farm rural economies will be more vibrant. This, of course is a testable hypothesis within our proposed study. Of the 348 CEA regions, 47 of them lack an urban center of sufficient size to qualify as a Standard Metropolitan Statistical Area (100,000 people or more). The CEA region which lost the most people over the decade was one of these, losing over 15 percent of its population. However, populations are not declining nor is economic activity waning in all CEA regions of the US that lack an SMSA-size core. Many of these CEA micro-regions, despite their rural character, have had stable or even growing populations coupled with increasing levels of economic activity. In these areas, vibrant local economies produce a diversified array of jobs which, in turn, could lead to increased employment opportunities and increased income for both farm and non-farm rural residents. A major focus of this research is to identify the basic forces that have played a role in determining whether a rural region is vibrant or in decline, and a number of basic hypotheses are to be tested in this analysis based on the new CEA micro-region definitions are central to this study. 1. The rural economies of CEAs which contain an SMSA-size urban center will be more vibrant, faster-growing, and contain more diverse employment opportunities than those which do not contain an SMSA. 2. CEA regions which lack the population to have an SMSA as an urban center experience slower rates of population gain, and, in a few cases, even significant population losses, when compared with CEA regions that have an SMSA-size urban core. 3. CEA regions that have diversified economies as measured by the percentages of the labor force employed in various industries have experienced faster rates of economic growth than CEA regions with less diversified economies 4. Farms are, on average, larger and increasing in size more rapidly over time in CEA micro-regions which lack an urbanized center of sufficient size to be an SMSA. 5. The rural economies of CEA regions which lack an SMSA-size urban center tend to be heavily dependent on but a small number of specific sectors--perhaps agriculture, mining or petroleum extraction, and thus the economies in these rural areas frequently lack diverse off-farm employment opportunities. 6. The type of farming will tend to be more extensive, that is, most commonly, extensive livestock and grain production, in the rural portions of the CEAs which lack an SMSA urban center. While agricultural income may comprise a large share of total income, the structure of agriculture will favor large, capital-intensive operations employing only a comparatively small number of people. 7. The agriculture in counties surrounding the CEAs with large urban centers will tend to be diversified and often intensive, often focusing on high-value horticulture and other specialty crop enterprises that can readily be marketed to those residing within the urban core. 8. Part-time farming in which farm families rely heavily on off- farm income will be more common in CEAs that contain an SMSA- size core. . Rationale and Significance A basic rationale for conducting this study is that research similar to this has not been done before. We believe that such analysis is likely to result in some very interesting and useful results--results that could have importance for public policy aimed at reshaping rural America. In the past, research aimed at identifying the forces which influence the viability of rural areas has focused on economic activity within a very narrow geographic area, perhaps within a single rural town. While relying on some of the basic premises of regional economics, in particular, Central Place Theory, this study takes a new and decidedly different approach from the past literature in this area. Since these Component Economic Areas have only been recently defined by the U.S. Department of Commerce (1995), only minimal quantitative work employing them has been conducted in an effort to test hypothesis with respect to the forces influencing population and economic growth rates within a region. For our analysis, these regions present ideal opportunities for examining the extent to which the structure of production agriculture within a region influences both the urbanized areas and the non-farm rural areas. Further, the metropolitan region itself may affect the structure of agriculture within the surrounding hinterland. In addition, comparisons can be made of the relative population change taking place in the rural and urban areas to observe how the hinterland is faring in comparison with the central place or places within each CEA. In this project, we argue that the survivability and viability of rural areas is heavily tied to a larger, more macro-oriented view of the micro- region in which the communities are located. Two rural towns which at some starting point in time were comparable in that they had very similar total populations and employment opportunities may proceed on very different paths depending on the particular characteristics of the micro-region or CEA in which they are located. These different paths may, over time, lead to widely divergent changes not only in population but also in employment growth and in other indicators of economic activity. Rural communities lucky enough to be positioned in locales that are an easy commuting distance from an urbanized center face a wider array of options for economic growth than communities not as ideally located. Much of the literature in rural development argues that these divergent paths are primarily attributable to choices that community leaders make with regard to efforts aimed at fostering economic and population growth. While we do not minimize the role that local community leadership might play in encouraging and promoting economic development efforts, we believe that these micro-regions are in large measure being shaped by forces largely outside the control of local residents. A clear understanding of these underlying forces is at the basis for the development of broad-based strategic plans aimed at fostering economic growth while overcoming disadvantages. It is these forces that our study seeks to identify. Have the CEAs that lack an SMSA core experienced a slower population growth rate than the CEAs that contain both a SMSA and a rural area? How does the structure of agriculture differ between the two groups? Do farms tend to be fewer but larger, on average, for those CEAs that lack an SMSA core? Is an SMSA core a particular advantage in enabling the micro-region to achieve a faster pace of economic growth as measured by changes in per capita personal income? Have the CEA micro-regions containing an SMSA been able to provide a greater number and a more diverse array of employment opportunities for those living in rural areas? Are the rural economies in the CEA micro-regions with SMSA cores more vibrant? These questions can be answered by employing quantitative empirical models developed as part of this project. Past Research A number of previous attempts have been made to link a non- metropolitan county to an urbanized center in an effort to determine how a rural area is potentially affected by economic activity taking place at the urban core (and, for that matter, how the urban core is affected by economic activity within the surrounding rural area). The best known and most widely used approach has employed the so-called "Beale" codes, developed a number of years ago by Calvin Beale at the USDA. Each county in the US has been assigned a Beale code number, and these numbers range from zero to nine, depending on the proximity of the county to an urbanized center. The Beale codes have Central Place Theory as their basis. In applying Central Place Theory to a region consisting of an urban center surrounded by rural counties of varying degrees of remoteness, a logical hypothesis is that population growth (as well as other measures of economic activity) would be most rapid in counties located adjacent to, or within an easy commuting distance to, the urban center. Counties located further away would be expected to have less rapid population growth, or perhaps even population decline, an perhaps have less diversified economies with fewer employment opportunities. The project principal investigators have employed the Beale Codes as explanatory variables in recently-published studies (Goetz and Debertin, October, 1996) The only authors who have made an attempt to employ the CEA micro-regions as a basis for analysis of rural regions are Henry and Drabenstott. However, their study objectives were quite different from ours. They were primarily interested in comparing economic growth rates within rural counties of each micro-region with the economic growth rates in the urbanized core. They found that there were a significant number of micro-regions where the economic growth rates were higher in the surrounding rural counties of the micro-region than in the urbanized core. In the Henry-Drabenstott analysis, the 47 CEAs that are not sufficiently urbanized to contain an SMSA were simply deleted from the data set. In our study, we expect to pay particular attention to what is going on inside these 47 CEAs which lack an SMSA core, in that many of these are located in the most rural areas of the US. Studies that attempt to link the characteristics of the agriculture within a region to the economic activity taking place there have more frequently been done. Most of these studies, however, concentrate on analyzing the potential impacts of the structure of agriculture in the region immediately surrounding a town of a modest size, as opposed to looking at the problem from a regional perspective. In her book, Lobao summarizes studies by agricultural economists and sociologists that link characteristics of farms to characteristics of non-farm rural communities. Many of the research studies addressing these issues were case studies, or studies conducted only within a specific state. None of these studies employed the micro-region approach we are intending on using here. The best-known study which attempted to link the size and number of farms to non-farm community growth and development was conducted in the 1940s (Goldschmidt). Goldschmidt's case study involved two California towns--Dinuba and Arvin, selected because he believed that the underlying economic and demographic conditions affecting both towns were similar. However, Dinuba was surrounded by many small farms averaging 57 acres per farm; whereas Goldschmidt's data revealed that fewer but larger farms surrounded Arvin, averaging 497 acres in size. By Goldschmidt's measures, Dinuba was experiencing considerable economic growth and development, whereas Arvin was not. Goldschmidt concluded from the comparisons that the size and number of farms surrounding a community--the structure of agriculture within the local area--was an important determinant of community growth and development.We wonder if Goldschmidt would have come to the same conclusions if the analysis had been conducted within the context of the CEA micro-regions in which Dinuba and Arvin are located. In 1984, Hayes and Olmstead reanalyzed the data used by Goldschmidt, and concluded that variables other than average farm size could have lead to differential rates of economic growth and development between Arvin and Dinuba. These variables were not fully accounted for in the Goldschmidt study. They argued that many of these differences could be instead attributed to factors such as "...[d]ifferences in water costs, mineral endowments and the age of agricultural development...too many other variables besides farm size cloud the picture" (pg. 435). The 1940 population (data Goldschmidt had access to when the initial study was done) of Dinuba was 3,790 and Arvin, 4,042. Currently, Dinuba remains more prosperous than Arvin. The most recent Census population estimate (U.S. Bureau of the Census, Population Estimates Web-site for July, 1994) lists Dinuba's population at 13,553, considerably larger than Arvin at 10,161. As part of this study, we hope to revisit this controversy in the context of the differences in the CEA micro-regions in which the two towns are located. In a table (pp. 60-64), Lobao indicates which of the subsequent studies support the Goldschmidt finding and which did not. Those that supported the Goldschmidt findings include studies conducted for Wisconsin by Rodefield (1974) and by Martinson, Wilkening, and Rodefield (1976); studies in California by Fujimoto (1977) and by the Small Farm Viability Project (1977). Also supporting the Goldschmidt hypothesis was a study by Larry Swanson (1980) employing data from 27 Nebraska counties. MacCannell and Dolber-Smith's 1986 study employed a variety of socioeconomic indicators for 98 counties in Arizona, California, Florida and Texas, and largely supported the Goldschmidt findings. Flora and Flora's 1986 Great Plains' study, outlined below in further detail, also confirmed the Goldschmidt finding. A number of studies provide partial or mixed support of the Goldschmidt findings. These included studies by Skees and Swanson (1986); Green (1985); Wheelock (1979); and by Gilles and Dalecki (1988). In contrast, using data from 520 Pennsylvania communities, Swanson's 1982 study did not support the Goldschmidt findings, nor did studies by Heaton and Brown (1982), or county-level studies by Buttel, Lancelle and Lee (1986, using data on 105 counties in the Northeast); and van Es, Chicoine and Flotow (1986 using data on 331 corn belt counties). Could it be that the mixed support for the Goldschmidt conclusion can be explained on the basis of difference in the micro regions in which these various studies have been conducted? Heady and Sonka (1975) attempted to determine how farm size was related to the welfare of the farm and non-farm economy. They used a linear programming model to link farm-size structure to total income in the farm sector, the number and size of farms, income per farm, secondary income generation, and consumer food costs. The study concentrated on the 12 states in the North Central region. A portion of the analysis was also conducted for the U.S. as a whole. Their model forecast considerable shifts in the patterns of crop and livestock production under different assumptions about the size of farms in an area. They concluded that a farming structure consisting largely of small farms would result in "... increased economic activity in those nonfarm sectors dependent on agriculture" (p. 75). They did not, however, forecast population change in rural regions. A 1979 study by Marousek attempted to identify economic linkages between farm size and characteristics of rural communities. Marousek chose a single community in Idaho for his analysis. Using an input- output model, he found that while small farms accounted for only a minimal share of agricultural output, small farm operators tended to have a greater propensity to both buy inputs locally and make consumption purchases locally than did large farm operators. He therefore argued that small farms have impacts on the non-farm economy that are larger than would be expected if the analysis were based on gross sales alone. He concluded that it was important to preserve small farms to protect the well-being of the non-farm rural economy. Most of the economic literature dealing with population change focuses instead on the role of new technologies and characteristics that might once again make it possible for non-farm labor in a technology- based society to work at a considerable distance from their employers' offices, perhaps even at home in a small rural community. Loveridge and Schmid (p. 1163) argue that "[w]e need to better understand how changes in living preferences, congestion costs, interlinked production systems and transportation will change [the] spatial allocation of economic activity." Flora and Flora attempted to link farm size to community characteristics in farming-dependent counties in the Great Plains and West. Some of these characteristics measured changes in variables such as the number of retail establishments and changes in the volume of retail sales over the period 1967-77. They included two measures of farm size--the percent of land in farms of 500-999 acres (called medium farms) and the percent of land in farms of 2000+ acres (called large farms). A particularly important finding of this study was that retail trade in local communities tended to be negatively related to the measures of farm size. In communities surrounded by medium size farms, the volume of retail trade and the number of retail establishments tended to increase over time, ceteris paribus; in communities surrounded by large farms, the opposite was true. They argued that the medium- sized farms likely had higher labor/capital ratios than large farms (and thus needed more labor per unit of output) and also tended to have a greater propensity to make purchases locally. One goal of this study is to determine whether the same conclusion applies to other regions. Education represents human capital that can be a major force in rural economic development (Johnson and Broomhall). Goetz argues that education represents a key to rural economic development, but rural communities are often ill-equipped to provide job opportunities for those with college degrees, who find that in order to obtain employment consistent with their newly acquired job skills, they need to migrate to urban areas (see also Debertin; Debertin, Infanger and Goetz). While being able to hire educated workers may be one factor in industrial location decisions by firms, education also drives migration patterns, as workers seek jobs that use their newly acquired skills. To the extent that educated workers migrate from a rural community, the local community does not reap the gains from their education. Research Methods As indicated earlier, the recently defined multi-county CEA micro-regions (Survey of Current Business) most commonly consist of both a metropolitan area--that is, a Standard Metropolitan Statistical Area--and a group of surrounding counties that are more nearly "rural" in character. In some instances, however, these areas are located in regions in which a metropolitan area sufficient to fulfill the Census definition for an SMSA (an SMSA requires a minimum of 100,000 people) does not exist, such as areas in much of the Great Plains. In these cases, however, the CEAs still contain one or more cities at the core with total population of under 100,000. Still others, particularly those located in the heavily-populated Northeast, may consist almost entirely of urbanized area. There are over 3,000 counties in the contiguous 48 states. These were aggregated by the Commerce Department into the 348 CEAs, Of these, 59 lack any counties which can be classified as rural. In addition, there are 47 CEAs which lack an SMSA core, and the remaining 242 contain both a metropolitan center as well as a rural hinterland (Henry and Drabenstott). We have worked with the file containing the CEA-to-FIPS county code linkages. Since the CEAs consist of multi-county areas or regions, the boundaries of each CEA are made up of portions of a county boundary. This facilitates the use of the CEAs for conducting applied quantitative research. In particular, any data that are available on a county level are easily aggregated into data for a CEA. Further, it is possible to compare the population change as well as changes in other indicators of economic activity for the urbanized and the hinterland portions of the CEA. Figure 1 illustrates the multi-county CEA regions for the US. Since the micro-regions defined by the CEAs each consist of multi- county areas, it is a straightforward procedure to aggregate data from existing county-level data or data for urban places, cities and towns. The procedure we employed for calculating population changes for CEA micro-regions can be applied to other data currently reported on a county-level. The Bureau of the Census not only provides county-level population figures for each decile, current annual county-level estimates are readily available on an annual basis for downloading from Census files at FTP sites on the Internet. We have experience in downloading these data files from the internet sources. From these files rates of population change can be calculated not only for decade-long increments as we have already done from the files for the 1980 and 1990 census files, but for any other length of time of interest. This makes it possible to compare estimate population changes within the CEA the micro-region with data for the exact same time period from another source. For example, Farm size and other data from the U.S. Census of agriculture is not from the decile years, but from the years 1982, 1987, and, most recently, 1992. While the CEA micro-regions each consist of several counties, the county-level detail can be retained. This was the approach employed by Henry and Drabenstott in their study. It is a simple matter to determine the size of the rural and urban populations separately and to aggregate these data for each CEA. Thus, comparisons can be made across CEA micro-regions for both the rural and the urban populations. Similarly, counts of farm numbers can be developed for each micro-regions as well as average farm size measure for the micro-region. Once the data have been aggregated into the CEA micro-regions, or into the rural and urban, quantitative model building, from the simple to the far more elaborate can be readily accomplished. A simple analysis employs an Analysis of Variance (ANOVA) approach to compare population and economic growth rated by dividing the CEA population into a number of different samples, depending on different criteria contained n the data. An example would be to take the group of 47 CEA micro-regions that lack an SMSA size core and compare the population and economic growth rates for three categories, that is, (1) those most heavily dependent on agriculture as a primary income source; (2) those most heavily dependent on energy extraction as a primary source of income; and (3) the group with more diverse economies that are not primarily dependent of either agriculture nor energy extraction. Another ANOVA approach compares those CEA micro regions that have significant numbers of farms which also contain SMSA-size urban cores with those CEA micro regions that also contain significant numbers of farms that do not contain an SMSA-size core. Our hypothesis here is that the farming-dependent economies in the non- urbanized portions of the CEA are more vibrant if the CEA micro- regions contain an urbanized core. This ANOVA modeling will provide a basis for a formal econometric model of the forces affecting economic and population growth within the CEA micro-regions. The two most logical endogenous variable are percentage changes in papulation growth and per capita income over selected time periods. Multidirectional causality may exist between these two endogenous variable, calling for a simultaneous equation system.The unit of observation, obviously, is the CEA micro region. Components of the regression equations that act as explanatory variable representing the forces thought to influence growth or decline within the various micro regions, all measured by aggregating county- level data into the CEA regions by taking advantage of the CEA-to-FIPS file. These explanatory variables can be divided into a number of different categories Category I variables quantifying the structure of agriculture within the CEA region. Generally, these variables measure number and percentage of farms in each size category as defined by the USDA category (See, Goetz and Debertin, August, 1996 for an application employing a similar approach Category II variables quantifying the economic diversity of the CEA micro- region. In the application cited above, the investigators employed an approach in which the percentage of the labor force employed in each major employment category was calculated. Color Map Page References to Project Description Butler, Margaret A. and Calvin L. Beale "Rural-Urban Continuum Codes for Metro and Non-Metro Counties, 1993." USDA, ERS, Agriculture and Rural Economy Division, Staff Report AGES 9425, 1994. Buttel, Frederick Mark Lancelle and David R.Lee. "Emerging Agricultural Technologies, Farm Structural Change, Public Policies and Rural Communities in the Northeast." in Technology, Public Policy and the Changing Structure of American Agriculture: Volume 2, Background Papers, Part D. Office of Technology Assessment, Washington, D.C., 1986, pp. 213-372. Debertin, David L., "Rural Development Issues for Agricultural Economists to the Year 2000: Discussion. Am. J. Agr. Econ 75 (December, 1993), 1173-4. Debertin, David L., C.L. Infanger, and S.J. Goetz. "The Viability of Rural Communities: Challenges for the 1990s and Beyond." Proceedings--Rural Planning and Development: Visions of the 21st Century and Beyond, Orlando, FL, 1991. Flora, Cornelia Butler and Jan L. Flora "Public Policy, Farm Size, and Community Well-Being in the Farming-Dependent Counties of the Plains. in Agriculture and Community Change in the U.S.: The Congressional Research Reports, ed Louis E. Swanson, Rural Studies Series, Westview Press, Boulder, CO, 1988. pp. 76-129. Fujimoto, Isao, "The Communities of the San Joaquin Valley: The Relation between the Scale of Farming, Water Use and Quality of Life." Special Studies of the Committee on Agriculture, 95th Congress, First Session Washington, D.C., U.S. Government Printing Office, 1977. Gilles, Jere Lee and Dalecki, Michael. "Rural Well Being and Agricultural Change in Two Farming Regions," Rural Sociology 53, Spring, 1988, pp. 40-55. Goetz, Stephan J. "Human Capital and Rural Labor Issues" Am. J. Agr. Econ 75 (December, 1993), 1164-68. Goetz, Stephan J. and David L. Debertin. "Rural Population Decline in the 1980s: Impacts of Farm Structure and Federal Farm Programs." American Journal of Agricultural Economics 78 (August, 1996) pp. 517- 29. Goetz, Stephan J. and David L. Debertin. "Rural-Urban Locational Choices of Medical Doctors: A County-Level Analysis." Review of Agricultural Economics 18 (October, 1996) pp. 547-63. Goldschmidt, W.R. Small Business and the Community: A Study in the Central Valley of California on Effects of Scale of Farm Operations. Report of the Special Committee to Study Problems of American Small Business. Washington, D.C., 79th Cong., 2nd Sess., 1946. Green, Gary P. "Large Scale Farming and the Quality of Life in Rural Communities: Further Specification of the Goldschmidt Hypothesis." Rural Sociology 50, Summer, 1985, pp. 262-73. Hayes, Michael N. and Alan L. Olmstead, "Farm Size and Community Quality: Arvin and Dinuba Revisited" Am. J. Agr. Econ. 66 (November, 1984) pp. 431-6. Heady, Earl O. and Steven T. Sonka "Farm-Size Structure and Off- Farm Income and Employment Generation in the North Central Region" North Central Regional Center for Rural Development, Iowa State University, Ames, IA, 1975. Heaton, Tim B. and David L. Brown. "Farm Structure and Energy Intensity: Another Look." Rural Sociology 47, Spring, 1982, pp. 17-31. Henry, Mark and Mark Drabenstott. "A New Micro View of the U.S. Rural Economy." Kansas City Federal Reserve Bulletin Second Quarter, 1966, pp. 53-70. Johnson, Thomas G. and David E. Broomhall, "Education and Economic Development in Rural Appalachia," in Education, Off-Farm Employment and Rural Economic Development: Perspectives from States in the Southeast, Southern Rural Development Center, Mississippi State, MS, 1992, pp. 20-29. Lobao, Linda, "Locality and Inequality: Farm and Industry Structure and Socioeconomic Conditions." Suny Series on New Inequalities, A Gary Dworkin, ed. The State University of New York Press, Albany, NY, 1990. Loveridge, Scott, and A. Allan Schmid "Strategic Planning and Population Settlement," Am. J. Agr. Econ 75 (December, 1993), 1160- 63. MacCannell, Dean and Edward Dolber-Smith. "Report on the Structure of Agriculture and Impacts of New Technologies on Rural Communities in Arizona, California, Florida and Texas, in Technology, Public Policy and the Changing Structure of American Agriculture: Volume 2, Background Papers, Part D. Office of Technology Assessment, Washington, D.C., 1986, pp. 19-167. Martinson, Oscar B., Eugene A. Wilkening, and Richard D. Rodefield, "Feelings of Powerlessness and Social Isolation Among 'Large Scale Farm Personnel." Rural Sociology, 41: Winter, 1976. Pagoulatos, Angelos, Sylvie Marzin and David L. Debertin "Diversification and Farm Acreage Variation in Kentucky Counties." North Central Journal of Agricultural Economics 9:1 Jan., 1987. "Redefinition of BEA Economic Areas" Survey of Current Business 70, February, 1995 Rodefield, Richard D. "The Changing Organizational and Operational Structure of Farming and the Implications for Farm Work Force Individuals, Families and Communities, Ph.D. Dissertation, the University of Wisconsin, Madison, 1974. Skees, Jerry R. and Louis E. Swanson. "Examining Policy and Emerging Technologies Affecting Farm Structure in the South and the Interaction Between Farm Structure and Well Being of Rural Areas," in Technology, Public Policy and the Changing Structure of American Agriculture: Volume 2, Background Papers, Part D. Office of Technology Assessment, Washington, D.C., 1986, pp. 373-495. Small Farm Viability Project. The Family Farm in California: The Small Farm Viability Project, Governor's Office, Department of Planning and Research, the Department of Food and Agriculture, and the Department of Housing and Community Development, Sacramento, California, 1977. Swanson, Larry."A Study in Socioeconomic Development: Changing Farm Structure and Rural Community Decline in the Context of the Technological Transformation of American Agriculture," Ph.D. Dissertation., University of Nebraska, 1980. Swanson, Louis. "Farm and Trade Center Transition in an Industrial Society:Pennsylvania 1930-1960." Ph.D. Dissertation The Pennsylvania State Univ., University Park, Pennsylvania, 1982. van Es,J.C., David L. Chicoine and Mark A. Flotow. "Agricultural Technologies, Farm Structure and Rural Communities in the Corn Belt:Policy Changes and Implications for 2000." in Technology, Public Policy and the Changing Structure of American Agriculture: Volume 2, Background Papers, Part D. Office of Technology Assessment, Washington, D.C., 1986, pp. 496-570. Wheelock, Gerald C., "Farm Size, Community Structure and Growth: Specification of A structural Equation Model." Paper Presented at the Annual Meetings of the Rural Sociological Society, Burlington, Vermont, 1979. Facilities and Equipment The researchers have access to the following computer hardware and software: (1) Desktop Access to the University with a full array of statistical software including programs such as SAS, SPSS and LIMDEP, among others. In addition, the university has just installed a Convex Exemplar computer, which is a scalable, parallel computer with 16 Hewlett Packard high end, shared memory processors. Additional processors will be added over time. (2) Unix-based SUN Lxi Workstation under control of project investigators with GIS software including ARCINFO. This system is networked to the project investigators individual offices via an Ethernet connection, and to the other Unix-based workstations owned by the UK college of agriculture. (3) Two Pentium-based PC computers in the project investigators offices networked to the SUN workstation and to the University mainframe via ethernet connections. (4) Census data available on the File Server at Cornell University, as well as all other public domain data available via internet. Collaborative Arrangements (none are planned) Abbreviated Vita and Five-Year Publication List David L. Debertin Professor Tenured Faculty Appointment Date: June, 1974 Date and Location of Birth Nov. 24, 1947, Minot N. Dak. Degrees Received: Institution Degree Date Major North Dakota State UniversityB.S. 1969 Ag. Education - Agronomy North Dakota State UniversityM.S. 1970 Ag. Economics Purdue University Ph.D. 1973 Ag. Economics Assistant Professor of Agricultural Economics, Purdue University, Aug., 1973- June, 1974 Assistant Professor of Agricultural Economics, University of Kentucky, June, 1974- July, 1976 Associate Professor of Agricultural Economics, University of Kentucky, July, 1976- July, 1979 Professor of Agricultural Economics, University of Kentucky, July, 1979- present Co-editor, Journal of Agricultural and Applied Economics (Formerly Southern Journal of Agricultural Economics) 1993-1995 Volumes Honors and Awards: Phi Kappa Phi (Graduate fellow, 1969-70), Phi Eta Sigma, Gamma Sigma Delta, Univ. of KY Excellence in Undergraduate Teaching Award 1991; Southern Agricultural Economics Association, Distinguished Professional Contribution in Undergraduate Teaching, 1992 Recent Grants and Research Projects USDA CSRS National Research Initiative Competitive Grants Program "County-Level Determinants of Economic Growth in the U.S. South." (Co-PI Joint with S.J. Goetz) July, 1993-June, 1995 $115,300. Southern Experiment Station Directors "Identifying Locations in the Southeast For Sustainable Agriculture Projects (Principal Investigator-Joint with Dr. Pagoulatos) $37,000 1993-94 (Joint with the Community Farm Alliance and the University of Georgia, Dept of Anthropology) Southern Rural Development Center competitive grant (Principle Co-investigator with S.J. Goetz) "The State of Human Capital in the South, Oct. 1992-Sept., 1993. $13,000 (One of 2 selected for funding from 13 applicants) UK KERA Grant "Economic Dimensions of the Implementation of High School Education Reform in Rural Areas" $5000, Sept. 1992-January, 1993 Principal Co-investigator joint with S.J. Goetz. UK/U of L Joint Center for the Study of Education Policy "An Analysis of Socioeconomic Factors Affecting School District Responses to KERA" $9500, Sept. 1994-June, 1995 Principal Co- Investigator joint with S.J. Goetz. Hatch Projects 93 An analysis of finance, efficiency and socioeconomic influences in urban and rural public schools (Joint with Dr. Goetz) 94 Development of multi-objective decision criteria models for agricultural investment appraisal (joint with Dr. Pagoulatos) Manuscripts in refereed scientific journals: 1991-present Debertin, David L. and Angelos Pagoulatos. "Categorizing State Economies and Forecasting Differential Economic Growth Rates." Best Papers, Atlantic Economic Society. January, 1991. Debertin, David L., Angelos Pagoulatos and Garnett L. Bradford. "New Applications of Three- Dimensional Computer Graphics in Production Economics." Review of Agricultural Economics 13:1 January, 1991. Debertin, David L. and Larry D. Jones. "Applications of Computer Graphics to Undergraduate Instruction in Agricultural Economics." American Journal of Agricultural Economics. 73:1. Feb. 1991. Debertin, David L. and Angelos Pagoulatos. " Research in Agricultural Economics, 1919-1990: Seventy-two Years of Change." Review of Agricultural Economics 14:1 January, 1992 (in press). Goetz, Stephan J. and David L. Debertin. "A Caution About Measuring School Outputs in Educational Production Functions: An Anthology. Atlantic Economic Journal 19:4, Dec. 1991. Goetz, Stephan J. and David Debertin."Regional Analysis of Kuznet's Hypothesis Using County- Level Data, Atlantic Economic Journal Best Papers, 2:1, January, 1992, pp 206-210. Goetz, Stephan J. and David L. Debertin, "Rural Areas and Educational Reform in Kentucky: an Early Assessment of Revenue Equalization," Journal of Educational Finance 18:2, Fall, 1992, 163- 79. Debertin, David L. "An Animated Instructional Module for Teaching Production Economics with 3-D Graphics." American Journal of Agricultural Economics. 75:2. May, 1993 485-91. Goetz, Stephan J. and David L. Debertin. "Estimating County-Level Demands for Educational Attainment." Socioeconomic Planning Sciences Journal. 27: 1993 pp. 25-34. Debertin, David L. "Rural Development Issues for Agricultural Economists in the Year 2000: Discussion." American Journal of Agricultural Economics 75:5 December, 1993. Debertin, David L. , E. Jane Luzar, and Orlando D. Chambers. "The Need for a Protocol or a Set of Standards to Guide Agricultural Economics Research." Journal of Agricultural and Resource Economics 20:1, 1995. Goetz, Stephan J. and David L. Debertin. "Rural-Urban Locational Choices of Medical Doctors: County-Level Analysis. Review of Agricultural Economics 16:3 (September, 1996 (Forthcoming). Mwana N. Mawampanga and David L. Debertin. "Choosing Between Alternative Farming Systems:An Application of the Analytic Hierarchy Process" Review of Agricultural Economics 16:2 May, 1996 (Forthcoming). Goetz, Stephan J. and David L. Debertin. "Rural Population Decline in the 1980s: Impacts of Farm Structure and Federal Farm Programs." American Journal of Agricultural Economics ( (forthcoming, 1996) Other Publications bearing on the Grant Proposal Debertin, David L., Craig L. Infanger and Stephan J. Goetz. "The Viability of Rural Communities: Challenges for the 90s and Beyond." Proceedings: Rural Planning and Development: Visions of the 21st Century, Orlando FL, 1991. Debertin, David L. ed. Proceedings of a Symposium: Education, Off-Farm Employment and Rural Economic Development: Perspectives from States in the Southeast, Southern Rural Development Center (Forthcoming, 1992) Goetz, Stephan J. and David L. Debertin. "Rural Education and the 1990 Kentucky Educational Reform Act: Funding, Implementation and Research Issues." Agricultural Economics Research Report, August, 1991. Debertin, David L. and Stephan J. Goetz. "Estimating State and County-Level Demands for Educational Attainment. [Abstract of Paper presented at the AAEA meetings, 1991, Manhattan, KS] Am. J. Agr. Econ. 73:5 Dec. 1991 Debertin, David L. and Angelos Pagoulatos, "Forecasting Economic Growth Rates Across States: Are States with Ag-Dependent Economies Lagging?" [Poster Session Abstract] Southern Journal of Agricultural Economics 13:1, July, 1991. Debertin, David L. and Stephan J. Goetz. "Computer Cartography and the Display of Rural Economic Information." [Abstract--Poster Session] American Journal of Agricultural Economics 73:51991. Goetz, Stephan J. and David L. Debertin. "Education and Poverty in Rural Kentucky." [Abstract--Poster Session] American Journal of Agricultural Economics 73:5 1991. Abbreviated CV for Stephan J. Goetz 컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴 Professional Experience 1994- Associate Professor, Agricultural Economics, University of Kentucky 1990-94 Assistant Professor, Agricultural Economics, University of Kentucky 1984-90 Graduate Research Assistant and Visiting Specialist, Department of Agricultural Economics, Michigan State University. 컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴 Education 1990 Ph.D. Agricultural Economics Michigan State University 1986 M.Sc. Agricultural Economics Michigan State University 1984 B.Sc. Agriculture/Agricultural EconomicsUniversity of Guelph (Canada) 컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴 Honors and Awards Listed In Who's Who in the South and Southwest, 1995-96, 24th edition. Outstanding Ph.D. Dissertation Award, Dept. Agric. Econ., Michigan State Univ., 1990. Member of Phi Kappa Phi National Honor Society (since 1985); Gamma Sigma Delta (since 1993). Graduation with distinction from undergraduate program. 컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴 Selected Research Grants and Projects Principal Investigator and Project Director, USDA/CSRS National Research Initiative Competitive Grants Program (NRI-CGP), "County-level Determinants of Economic Growth in the U.S. South," July 1993�June 1995 [$115,300]. Principal Investigator; KY Ag. Exp. Station Hatch Project, 1992�1997. Principal Co-Investigator, USDA/ERS/CED, cooperative agreement; 1993�1994 [$12,500]. Principal Co-Investigator; Southern Rural Development Ctr., competitive grant, 1992�1993 [$13,000]. Technical Committee Chair, 1994-95, and Principal Co-Investigator, NE-162 (Renewed), Regional project, "Nonmetropolitan Economic Development: Alternatives in the New Competitive Environment;" 1992�1997. 컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴컴 Refereed Journal Articles Goetz, Stephan J. and David L. Debertin. "Rural Population Decline in the 1980s: Impacts of Farm Structure and Federal Farm Programs." American Journal of Agricultural Economics forthcoming. Goetz, Stephan J. and Dayuan Hu. "Economic Growth and Human Capital Accumulation: Simultaneity and Expanded Convergence Tests." Economics Letters forthcoming. Goetz, Stephan J. and Donald J. Kemlage. "TSD Facilities Location and Environmental Justice." Review of Regional Studies forthcoming. Goetz, Stephan J. and David L. Debertin, "Rural-Urban Locational Choices of Medical Doctors," Review of Agricultural Economics 18(1996):forthcoming. Goetz, Stephan J. and Richard C. Ready, "Economic Growth vs. Environmental Conditions: A State- Level Analysis," Growth and Change 27(1996):forthcoming. Goetz, Stephan J. and Richard C. Ready, "Modeling Economic Growth with Unpredictable Shocks: A State-Level Application for 1960�90," Journal of Agric. and Applied Econ. 27 (1995):400-8. Goetz, Stephan J. and Shannon R. Morgan, "State-Level Locational Determinants of Biotechnology Firms," Economic Development Quarterly 9(1995):174-84. Gallacher, Marcos, Stephan J. Goetz and David L. Debertin, "Managerial Form, Ownership and Efficiency: A Case Study of Argentine Agriculture," Agric. Economics 11(1994):289-99. Goetz, Stephan J. and Haiping Luo, "Public School Frontier Production Function Estimation with Time- Varying Inefficiency," KY Jrnl. of Business and Economics 13(1994):67-77. Goetz, Stephan J., "Human Capital and Rural Labor Issues," American Journal of Agricultural Economics 75(1993):1164-8. Goetz, Stephan J., "On the Existence of Stable Equilibria in Agriculture," Journal of Agricultural and Applied Economics 25(1993):25-34. Goetz, Stephan J. and David L. Debertin, "Estimating County-Level Demand for Educational Attain- ment," Socio-Economic Planning Sciences 27(1993):25-34. Goetz, Stephan J., "Interlinked Markets and the Cash Crop-Food Crop Debate in Land-Abundant Tropical Agriculture," Economic Development and Cultural Change 41(1993):343-61. Goetz, Stephan J. and David L. Debertin, "Rural Areas and Educational Reform in Kentucky: An Early Assessment of Revenue Equalization," Journal of Education Finance 18(1992):163-79. Goetz, Stephan J., "Economies of Scope and the Cash Crop-Food Crop Debate in Senegal," World Development 20(1992):727-734. Goetz, Stephan J., "A Selectivity Model of Household Food Marketing Behavior in Sub-Saharan Africa," American Journal of Agricultural Economics 74(1992):444-452. Goetz, Stephan J., and David L. Debertin, "Regional Analysis of Kuznet's Hypothesis Using County- Level Data," Atlantic Economic Society Best Papers 2(1992):206-10. Goetz, Stephan J., and David L. Debertin, "A Caution About Using School Outputs in Educational Production Functions," [Anthology] Atlantic Economic Journal 19(1991):62. Selected Recent Publications Goetz, Stephan J. "Labor Unions in Rural America," Ch. in Encyclopedia of Rural America, edited by G.A. Goreham, New York: Garland Publ. Inc., forthcoming, 1996. Goetz, Stephan J. "Markets, Transaction Costs and Selectivity Models in Economic Development," Ch. 17 in Gregory J. Scott, editor, Prices, Products, and People: Analyzing Agricultural Markets in Developing Countries, Colorado: Lynne Rienner Publishers, Inc., 1995 (pp. 383-402). Goetz, Stephan J., David L. Debertin and Angelos Pagoulatos, "Linkages Between Human Capital and the Environment: Implications for Sustainable Economic Development," in Proceedings of the International Association of Agricultural Econ., ed. by G.H. Peters, 1996 forthcoming. Gallacher, Marcos, Stephan J. Goetz and David L. Debertin, "Efficiency Effects of Institutional Factors: Limited-Resource Farms in Northeast Argentina," in Proceedings of the International Association of Agricultural Economists, ed. by G.H. Peters, 1996 forthcoming. Goetz, Stephan J. "Finance," in Proceedings of the Conference on Education in Kentucky: Current Results, Future Visions, spons. by the Univ. of Kentucky/Univ. of Louisville Joint Center for the Study of Educational Policy, Radisson Hotel, Lexington, KY, Feb. 8, 1995, pp. 42-48. Goetz, Stephan J., "Transactions Costs and Farm Labor Supply and Demand: Some Implications for Rural Economic Development," in Education, Off-Farm Employment and Rural Economic Develop- ment: Perspectives from States in the Southeast, Proc., Rural Dev. Symp. at 1992 Southern Agric. Econ. Assoc. meeting; South. Rural Develop. Center, SRDC Publ. No. 165, Jan. 1993, pp. 30-42. Debertin, David L., Craig L. Infanger and Stephan J. Goetz, "The Viability of Rural Communities: Challenges for the 1990s and Beyond," in Rural Planning and Development: Visions of the 21st Century, Vol. 1, February 1991, Orlando, FL, pp. 289-298. Goetz, Stephan J. and David L. Debertin, "Rural Education and the Kentucky Educational Reform Act of 1990: Funding and Implementation Issues," in Rural Infrastructure as a Cause and Consequence of Rural Economic Development and Quality of Life, SRIEG-53 annual conference, Southern Rural Development Center, May 1991, Atlanta, GA, pp. 23-54. Recent Abstracts in Refereed Journals of Papers Presented at Professional Meetings [*=presented by Goetz] *Goetz, Stephan J. and David L. Debertin, "Rural Population Decline in the 1980s: Impacts of Farm Structure & Federal Farm Programs," 1995 AAEA mtg., Indianapolis, IN; in AJAE 77(1995):in press *Kemlage, Donald and Stephan J. Goetz, "County-Level Determinants of Food Manufacturing Firm Locations," 1995 AAEA mtg., Indianapolis, IN; in AJAE 77(1995):in press Debertin, David L. and Stephan J. Goetz, "Rural-Urban Location Decisions of Physicians," 1995 AAEA mtg., Indianapolis, IN; in AJAE 77(1995):in press *Goetz, Stephan J., and David L. Debertin, "Implications of KERA for Education Funding in the U.S. South," symposium paper pres. at 1994 SAEA mtg., Nashville, TN; in JAAE 26(1994):340. *Goetz, Stephan J. and Richard C. Ready. "A Frontier Economic Growth Model for U.S. States: 1950- 90," 1994 SAEA mtg., Nashville, TN; in JAAE 26(1994):316. Goetz, Stephan J., Richard C. Ready and Brad Stone, "Economic Growth vs. Environmental Quality: A State-Level Analysis for 1988-90" 1993 SAEA mtg., Tulsa, OK, in JAAE 25(1993):287-8. *Goetz, Stephan J., "A Note on Agricultural Disequilibrium and Instability," 1992 AAEA meeting, Balti- more, MD; in AJAE 74(1992):1306. Debertin, David L. and Stephan J. Goetz, "Education and Economic Growth," symposium paper pres. at 1992 AAEA ann. mtg., Baltimore, MD; in AJAE 74(1992):1263. *Goetz, Stephan J., Huoying Wu, and Jerry R. Skees, "Human Capital and the Distribution of Farm Income: A Multinomial Logit Analysis," South. Jrnl. of Agric. Econ., 24 (1), July 1992. *Goetz, Stephan J. and David L. Debertin, "Regional Analysis of Kuznet's Hypothesis Using County- Level Data," Atlantic Economic Journal, 20 (1) March, 1992. *Goetz, Stephan J., "Single- and Multi-Dimensional Theil Inequality Measures: An Application to Farm Households," American Journal of Agric. Economics, 73 (5), December 1991, p.1554. *Goetz, Stephan J. and David L. Debertin, "Education and Poverty in Rural Kentucky," [Poster] American Journal of Agricultural Economics, 73 (5), December 1991, p.1556. Debertin, David L. and Stephan J. Goetz, "Computer Cartography and the Display of Rural Economic Information," [Poster] American Journal of Agricultural Economics, 73 (5), December 1991, p.1558. Debertin, David L. and Stephan J. Goetz, "Education and Economic Growth," Symposium Abstract in Amer. Jrnl. of Agric. Econ., 74 (5) Dec., 1992., [1992 AAEA meeting]. Budget Year 1 Budget Year 2 Summary Budget Budget Justification The budget consistes of a request for funds to fund the following. (1) A 3/4 time research assistant is assist in conducting the research for the duration of the proposal (24 months); (2) Funds for travel to professional meetings to present the results of the analysis; and (3) Funds to keep the computing technology used in the project current. Justification for Equipment Expenditure Although both investigators have computing resources available to carry out most of the research, one additional PC with a large amount of RAM, disk space and processing power (P6 or RISC chip) is needed for two reasons. First, a DOS-based machine with large memory capacity is needed to run the spatial econometrics software from NCGIA. The large amounts of memory are necessary to accommo- date the spatial weights matrices, which are very large (with dimensions of up to 3,100x3,100 counties). Second, a computer is needed for the Research Associate. Current and Pending Support and Objectives Attachment to Current and Pending Support (Form CSRS-663) Research objectives for: County-Level Determinants of Economic Growth in the U.S. South [USDA/CSRS NRI-CGP; July 1993-June 1995] The long-term objective of this study is to identify strategic public policy levers which may be used by decisionmakers to accomplish rural economic growth objectives, especially as they relate to enhancing manufacturing competitiveness in rural areas (including the manufacture of food and kindred products). Specific objectives include finding answers to the following questions: [1]Does faster per capita income growth lead to higher investments in education and subsequent educational attainment, or does greater investment in education lead to faster income and job growth, or both? If there is a role for state and local government, should government focus more on job creation and income-enhancing programs, or more on investing in education? [2]Does more and higher-quality education serve to attract new businesses and firms to a region, or is it only through the introduction of new firms and businesses that education and human capital stocks improve? [3]How effective have state incentive programs, and the general "business climate", been in achieving faster growth in rural areas? How does the effectiveness of such programs compare with investments in physical infrastructure and education? [4]Does the sectoral composition of the local economy, and its change over time, affect income growth and investments in education? Conversely, to what extent does investing in education by state and local governments affect the economy's composition and subsequent income growth? [5]What is the (opportunity) cost over time of not investing in lagging rural communities, as measured by welfare payments and other public transfers of funds into these communities? To what extent do such communities absorb income from other counties in the same state as well as the nation? Conflict of Interest List for Goetz and Debertin Kurt R. Anschel Robert Armstrong G. Bradford Orlando Chambers Marcos Gallacher Dayuan Hu Craig L. Infanger Larry D. Jones Donald Kemlage Phil Kenkel Noor Khan Haiping Luo E. Jayne Luzar R. Shannon Morgan Octavian Ngarambe Angelos Pagoulatos Emilio Pagoulatos Richard C. Ready Jerry R. Skees Eldon D. Smith Ronald Young Houying Wu