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Income Growth in the Rural Midwest: Where Is There a Problem?

Income Growth in the Rural Midwest: Where Is There a Problem?. John Miranowski Co-Authors: Bruce Babcock, Dermot Hayes, and Daniel Monchuk. Introduction. Origins of Study Why are many rural counties left behind? What drives rural economic development in Midwestern counties?

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Income Growth in the Rural Midwest: Where Is There a Problem?

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  1. Income Growth in the Rural Midwest: Where Is There a Problem? John Miranowski Co-Authors: Bruce Babcock, Dermot Hayes, and Daniel Monchuk

  2. Introduction • Origins of Study • Why are many rural counties left behind? • What drives rural economic development in Midwestern counties? • Analysis to identify important policy or control variables for rural development in Midwest • “People-based” vs. “Place-based” vs. “Business-based” policies

  3. Current Value Added Approach in Rural Midwest • Local, State and USDA groups focus on subsidizing investments in businesses, such as ethanol and bio-diesel • Some recent interest in water and land based recreation, including bike trails • Commodity groups are turning their focus to livestock and biofuels • Governor and State leaders are interested in biotech and crop transformation, as well as some interest in reducing taxes • ISU research and extension in farmers markets, specialty crops, and sustainable agriculture systems

  4. The Problem • Isolated rural counties in the Midwest fail to attract investment capital due to lack of agglomeration economies and market access • Agriculturally dependant counties in the Midwest typically do not generate enough economic activity to retain the human capital they produce and may not provide attractive environment for investment

  5. Approach • Take a broad, data-based approach to Midwest county income growth: 1) examine a range of variables 2) address spatial aspects associated with local and regional economic growth • Attempt to explain total county income growth for the period 1990-2001, based on initial conditions in 1990 • Minnesota, Wisconsin, Illinois, Iowa, Missouri, Kansas, Nebraska, and South Dakota

  6. Measure of Success • Considered alternative measures local/county economic vitality • Settled on growth in Total County Income • Measure captures both population and per capita income growth • Measure ignores the investment in human capital of those who are educated and leave

  7. - 0 . 8 2 2 - 0 . 3 4 9 0 . 3 4 9 - 0 . 4 5 5 0 . 4 5 5 - 0 . 5 6 7 0 . 5 6 7 - 1 . 0 8 5 Total County Income Growth1990-2001

  8. 4 6 2 - 6 7 5 0 6 8 4 8 - 1 4 8 3 5 1 4 9 0 9 - 3 2 4 9 8 3 2 5 0 8 - 5 1 0 5 0 6 7 1990 County Population

  9. 1 - 1 1 0 1 1 1 - 3 7 0 3 7 1 - 6 2 9 6 3 0 - 7 3 9 1990 Dependence on County Income from Farming

  10. - 2 . 1 2 3 6 2 - - 0 . 2 7 9 6 8 3 - 0 . 2 7 9 6 8 3 - - 0 . 0 7 7 3 0 8 - 0 . 0 7 7 3 0 8 - 0 . 1 2 7 9 6 1 0 . 1 2 7 9 6 1 - 2 . 4 0 1 0 0 8 Growth Livestock Cash Receipts

  11. 1 - 1 1 0 1 1 1 - 3 7 0 3 7 1 - 6 3 0 6 3 1 - 7 3 9 Recreation Amenity index (own and surrounding counties)

  12. 0 1 - 2 3 - 6 7 - 2 4 COE Swimming Area (own and surrounding counties)

  13. 0 . 0 3 1 - 0 . 4 8 4 0 . 4 8 4 - 0 . 6 2 7 0 . 6 2 7 - 0 . 7 9 5 0 . 7 9 5 - 2 . 7 6 6 Property Taxes per Capita

  14. State Income Taxes per Capita

  15. Summary and Policy Implications • Recreational amenities and bike trails have positive impacts on county income growth • Amenities in surrounding counties also important – regional vs. local approach to amenity development • Counties with reliance on farm income (and commodity program payments) have not performed well • Not a viable rural development strategy as frequently advocated • However, counties with growing livestock revenues (value adding on-farm) have experienced greater county income growth • Subject to being accomplished in environmentally-sensitive manner

  16. Summary and Policy Implications • Government efforts and approaches to achieve rural development not well directed • High taxes, state transfers to counties, and local employee payrolls deter growth • Dramatic tax cuts are not realistic option • Taxes support education of those about to leave and community services for those unable to leave (aging population) • Age-challenged population deterrent to growth - lower tax base and greater reliance on state and federal transfers • Reorganizing local public services may offer option • Partnering, sharing, and regionalization of services • Political feasibility is the question for local community

  17. Unanswered Questions in Improving Rural Incomes • What about counties that do not want to change and grow – do not want to develop non-farm sector? • What about rural counties that lack necessary human capital -entrepreneurs, innovators, “shakers and movers”? • What about counties that are spatially and capital-challenged – human, natural, physical, and social?

  18. 0 . 2 1 9 - 0 . 5 0 5 0 . 5 0 5 - 0 . 6 1 8 0 . 6 1 8 - 0 . 9 1 0 . 9 1 - 2 . 2 3 5 State Transfers to Counties

  19. 0 . 2 9 3 - 0 . 7 4 3 0 . 7 4 3 - 0 . 8 9 5 0 . 8 9 5 - 1 . 0 4 5 1 . 0 4 5 - 3 . 8 0 8 Local Government Salaries and Wages per Capita

  20. 1 - 1 1 0 1 1 1 - 3 7 0 3 7 1 - 6 2 9 6 3 0 - 7 3 9 Percent of Population Aged 65+

  21. 0 . 0 1 1 9 3 9 - 0 . 0 7 2 9 1 4 0 . 0 7 2 9 1 4 - 0 . 0 8 2 6 2 8 0 . 0 8 2 6 2 8 - 0 . 0 9 1 6 3 6 0 . 0 9 1 6 3 6 - 0 . 1 0 2 4 1 9 0 . 1 0 2 4 1 9 - 0 . 1 8 8 3 8 6 Number of Non-farm Proprietors per Capita

  22. # 1 0 0 0 0 0 - 2 0 0 0 0 0 2 0 0 , 0 0 0 + ( County was Adjacent to a Metro County

  23. < 2 0 % 2 0 - 3 0 % 3 0 - 4 0 % 4 0 - 5 0 % + Percent of County Population Commuting 30+ Minutes

  24. Explanatory Variables • The empirical model ultimately used is a Cobb-Douglas type:

  25. Model • Take the ratio of this identity over two points in time and then take logs to get the following growth relationship • Total county income growth from t to t+1 is a function of population growth and per capita income growth

  26. Pi,t is the population of county i in year t; PCIi,t is the average per capita county income; is growth in livestock cash receipts over the period t to t+1 (LCRi,t is the total livestock cash receipts from within the county); TPPCi,t is transfer payments per capita; PPOP65i,t is the percent of the county population aged 65 plus; PPOP2034i,t is the percent of the county population aged between 20 and 34; PCOLi,t is the percent of the county population aged 25 -- with a college degree or higher; PPOPCOMi,t is the percent of the county population that commutes 30 minutes or more to work; NFPPCi,t is the number of non+farm proprietors per capita; AIi,home+4 is the combined amenity index for the home and 4 neighboring counties; COEi, home+4 is the number of COE swimming areas in the home and neighboring counties; PTPCi,t is property taxes per capita; TSWPCi,t is total government salaries and wages per capita; STPCi,t is state transfer payments per capita; STBPCi,t is the total state income (corporate and personal) tax burden per capita; PFINCi,t is the share of the counties income that came from farming; NMCi,t is a dummy =1 if the county was located adjacent to a metro county; UDi,t is a dummy variable =1 if the county had a population of 50k plus in t; Explanatory Variables

  27. IDi,t is a dummy variable =1 if the county has an interstate; UPi,t is a dummy variable if the county was home to a significant University and was not in a major metropolitan center; Sdi,k is a dummy variable indicating the county is present in one of the k states; and εi is a random error. Explanatory Variables

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