Abstract
This paper examines the relationship between local financing of education and school district efficiency. In a system of local school finance, the capitalization of school quality in housing prices provides homeowners with verifiable information regarding the impact of school officials’ actions and strong incentives to act upon that information. I find evidence that school districts with a higher percentage of revenues from local sources perform better on state math tests. In addition, the amount of residential property within a school district is positively related to math test passage rates.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
In 2006, the Cupp Report was renamed “Finance and Other Data.”
In Ohio, the fiscal year is named for the year in which the period ends. Thus, FY 2000 corresponds to the fiscal year beginning July 1, 1999 and ending June 30, 2000.
The district is College Corner Local School District.
Residential and agricultural properties are classified as Class 1 properties for taxation purposes and the Cupp Report only lists the valuations by property class.
It is important to note that the presence of commercial property in a district is not a “free lunch.” Homeowners are willing to pay more to live in districts with large amounts of commercial property. Other things equal, homes should be more expensive in areas with large amounts of commercial property as homeowners are willing to pay more for the ability to have others support their schools.
Substituting in other subject tests or graduation rates does not substantially change the results of this paper. The primary effect of using other tests, such as writing, is that the predictive power of the model declines because the subjective nature of the grading introduces measurement error.
Qualitatively similar results were obtained using other available measures of school quality, such as math tests at the fourth, fifth and twelfth grade levels and reading, science, writing, and citizenship tests at the tenth grade level.
The negative sign on college appears to be the result of collinearity between median income per tax return and the number of district residents with college degrees. The simple correlation between these two variables is 0.82, indicating a reasonably high level of collinearity (Kennedy 2003). The decision to retain college as an explanatory variable despite the multicollinearity was made after considering the options presented by Kennedy (2003, pp. 210–211). Dropping the college variable would not appear to reduce the variance of the remaining variables enough to overcome the bias introduced by the specification error.
\( 17.2 \times 0.153516 = 2.64 \)
\( - 8.01 \times - 0.141946 = 1.14 \)
It is likely that the percentage of district students that are non-white is picking up the effect of poverty, not discrimination or racial fractionalization, given the high correlation between the non-white variable and Ohio’s large, high poverty (but moderate income and valuation) urban school districts.
Property valuation can also be a choice variable in the long run for local voters to the extent that local zoning decisions affect property valuation within a district. Exurban school district, for example, struggle with the trade-off between maintaining their semi-rural character and bringing in development which raises property valuation and increases school district revenue per mill.
References
Brasington, D. M. (1999). Which measures of school quality does the housing market value? Spatial and non-spatial evidence. Journal of Real Estate Research, 18, 395–413.
Brasington, D. M. (2003). The supply of public school quality. Economics of Education Review, 22, 367–377.
Fischel, W. A. (1997). Homevoters, municipal corporate governance, and the benefit view of the property tax. National Tax Journal, 54, 157–173.
Fischel, W. A. (2001). The homevoter hypothesis: how home values influence local government taxation, school finance, and land-use policies. Cambridge: Harvard University Press.
Fischel, W. A. (2006). The courts and public school finance: Judge-made centralization and economic research. In E. A. Hanushek & F. R. Welch (Ed.), The handbook on the economics of education. Amsterdam: North Holland.
Fuchs, V. R., & Reklis, D. M. (1994). Mathematical achievement in eighth grade: interstate and racial differences. National Bureau of Economic Research working paper 4784. Cambridge: National Bureau of Economic Research
Hanushek, E. A. (1986). The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24, 1141–1177.
Hanushek, E. A. (1997). Assessing the effects of school resources on student performance: An update. Education Evaluation and Policy Analysis, 19, 141–164.
Haurin, D. R., & Brasington, D. M. (1996). School quality and real house prices: Inter- and intrametropolitan effects. Journal of Housing Economics, 5, 351–368.
Hoxby, C. M. (1996). Are efficiency and equity in school finance substitutes or compliments? Journal of Economic Perspectives, 10, 51–72.
Hoxby, C. M. (1999). The productivity of schools and other public goods producers. Journal of Public Economics, 74, 1–30.
Husted, T. A., & Kenny, L. W (2000). Evidence on the impact of state government on primary and secondary education and the equity–efficiency tradeoff. Journal of Law and Economics, 43, 285–308.
Kennedy, P. (2003). A guide to econometrics (5th ed.). Cambridge: MIT Press.
Lamdin, D. J. (1996). Evidence of student attendance as an independent variable in education production functions. Journal of Educational Research, 89, 155–162.
Ohio Department of Education (2002). The Cupp report [electronic file]. Columbus: Ohio Department of Education.
Peltzman, S. (1993). The political economy of the decline of American education. Journal of Law and Economics, 36, 73–120.
Peltzman, S. (1996). Political economy of public education: Non-college bound students. Journal of Law and Economics, 39, 73–120.
Ruggiero, J. (2001). Determining the base cost of an education: An analysis of Ohio School Districts. Contemporary Economic Policy, 19, 268–279.
Russell, W., Driscoll, W., & Fleeter, H. (2003). Making sense of out of school finance. Columbus: Ohio School Boards Association.
Southwick, L., & Gill, I. S. (1997). Unified salary schedule and student SAT scores: Adverse effects of adverse selection in the market for secondary school teachers. Economics of Education Review, 16, 143–153.
U.S. Census Bureau. (2000). Census 2000 school district tabulation [electronic file]. Washington, DC: U.S. Census Bureau.
Zaino, T. M. (2003). Property taxation and school funding. Presentation to the Governor’s Blue Ribbon Task Force on funding student success.
Acknowledgement
I would like to thank Russell Sobel, Milton Friedman, John Merrifield, Santiago Pinto, Mark Gillis, an anonymous referee, and participants at the 2005 Western Economic Association meetings for their helpful comments and suggestions. I would also like to acknowledge the financial support of the H.B. Earhart and Dan Searle Fellowships and the Kendrick Fund.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hall, J. Local School Finance and Productive Efficiency: Evidence from Ohio. Atl Econ J 35, 289–301 (2007). https://doi.org/10.1007/s11293-007-9077-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11293-007-9077-7