An extensive data set on upstate New York school district inputs and outputs is used to measure the technical efficiency of public school districts and to test whether certain institutional arrangements, including more public and private competition, can enhance various measures of high school outputs. The technique used involves stochastic frontier production functions. Whereas increased public school competition enhances output, the effect of private schools is sensitive to the output measure.
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References
1.
Aigner, D. J., C.A.K. Lovell, and P. Schmidt. 1977. Formulation and estimator of stochastic frontier production function method. Journal of Econometrics6:21-37.
2.
Arrow, K. J.1985. The economics of agency. In Principals and agents: The structure of business, edited by J. W. Pratt and R. J. Zeckhauser, 37-51. Boston: Harvard Business School Press.
3.
Banker, R. D., V. M. Gadh, and W. L. Gorr. 1993. A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis. European Journal of Operational Research67:332-343.
4.
Barrow, M. M.1991. Measuring local education authority performance: A frontier approach. Economics of Education Review10:19-27.
5.
Battese, G. E., and T. J. Coelli. 1993. A stochastic frontier production function incorporating a model for technical inefficiency effect. Working paper in econometrics and applied statistics 69, Department of Econometrics, University of New England, Armidale, Australia.
6.
Battese, G. E., and T. J. Coelli. 1995. A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics20: 325-332.
7.
Bauer, P. W.1990. Recent developments in the econometric estimation of frontiers. Journal of Econometrics46:39-56.
8.
Bessent, A., and E. Bessent. 1980. Determining the comparative efficiency of schools through data envelopment analysis. Educational Administration Quarterly16:74-84.
9.
Bessent, A. M., E. W. Bessent, J. Kennington, and B. Reagan. 1982. An application of mathematical programming to assess productivity in the Houston independent school district. Management Science28:1355-1367.
10.
Bimber, B.1993. School decentralization: Lessons from the study of bureaucracy. Santa Monica, CA: RAND.
11.
Borland, M. V., and R. M. Howsen. 1992. Student academic achievement and the degree of market concentration in education. Economics of Education Review11:31-39.
12.
Borland, M. V., and R. M. Howsen. 1993. On the determination of the critical level of market concentration in education. Economics of Education Review11:165-169.
13.
Borland, M. V., and R. M. Howsen. 1996. Competition, expenditures and student performance in mathematics; a comment on Couch et al. Public Choice87:395-400.
14.
Bradly, M. B. ed. 1992. Churches and Church Memberships in the United States. Atlanta, GA: Glenmary Research Center.
15.
Caudill, S. B., J. M. Ford, and D. M. Gropper. 1995. Frontier estimation and firm-specific inefficiency measures in the presence of heteroscedasticity. Journal of Business & Economic Statistics13:105-111.
16.
Coelli, T. J.1994. A guide to FRONTIER version 4.1: A computer program for frontier production function estimation. Department of Econometrics, University of New England, Armidale, Australia. Mimeographed.
17.
Cooper, S. T., and E. Cohn. 1997. Estimation of a frontier production function for the South Carolina education process. Economics of Education Review16:313-327.
18.
Couch, J. F., W. F. Shugart, and A. L. Williams. 1993. Private school enrollment and public school performance. Public Choice76:301-312.
19.
Dee, T. S.1996. Expense preference and student achievement in school districts. Working paper, Department of Economics, University of Maryland, College Park.
20.
Deller, S. C., and E. Rudnicki. 1993. Production efficiency in elementary education: The case of Maine public schools. Economics of Education Review12:45-57.
21.
Downes, T. A.1996. An estimation of the structure of governance in California school districts before and after Proposition 13. Public Choice86:279-307.
22.
Duncombe, W., J. Miner, and J. Ruggiero. 1997. Empirical evaluation of bureaucratic models of inefficiency. Public Choice93:1-18.
23.
Eberts, R. W., E. K. Schwartz, and J. A. Stone. 1990. School reform, school size and student achievement. Economic Review26:2-15.
24.
Evans, W. N., and R. M. Schwab. 1995. Finishing high school and starting college: Do Catholic schools make a difference. Quarterly Journal of Economics110:941-974.
25.
Fare, R., S. Grosskopf, and W. Weber. 1989. Measuring school district performance. Public Finance Quarterly17:409-428.
26.
Gramlich, E., and H. Galper. 1973. State and local fiscal policy and federal grant policy. Brookings Papers on Economic Activity1:15-58.
27.
Greene, K. V., and B. G. Kang. 1997. Public and private competition and the search for their effects on school outputs in New York State. Working paper 711, Department of Economics, State University of New York at Binghamton.
28.
Greene, W. H.1993. The econometric approach to efficiency analysis, In The measurement of productive efficiency, edited by H. O. Fried, C.A.K. Lovell, and S. S. Schmidt, 68-119. New York: Oxford University Press.
29.
Hoxby, C. M.1994a. Do private schools provide competition for public schools? Working paper 4978, National Bureau of Economic Research, Cambridge, MA.
30.
Hoxby, C. M.1994b. Does competition among public schools benefit students and taxpayers? Evidence from natural variance in school districting. Working paper 4979, National Bureau of Economic Research, Cambridge, MA.
31.
Jondrow, J., C.A.K. Lovell, I. S. Materov, and P. Schmidt. 1982. On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics19:233-238.
32.
Kumbhakar, S. C., S. Ghosh, and J. T. McGuckin. 1991. A generalized production frontier approach for estimating determinants of inefficiency in U.S. dairy farms. Journal of Business & Economic Statistics9:279-286.
33.
Lovell, C.A.K.1993. Production frontiers and productive efficiency. In The measurement of productive efficiency, edited by H. O. Fried, C.A.K. Lovell, and S. S. Schmidt, 3-67. New York: Oxford University Press.
34.
McCarty, T., and S. Yaisawarng. 1993. Technical efficiency in New Jersey school districts. In The measurement of productive efficiency, edited by H. O. Fried, C.A.K. Lovell, and S. S. Schmidt, 271-287. New York: Oxford University Press.
35.
Meeusen, W., and J. van den Broeck. 1977. Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review18:435-444.
36.
Newmark, C. M.1995. Another look at whether private schools influence public school quality: Comment. Public Choice82:365-373.
37.
Olmsted, G. M., A. T. Denzau, and J. A. Roberts. 1993. We voted for this? Institutions and educational spending. Journal of Public Economics52:363-376.
38.
Reifschneider, D., and R. Stevenson. 1991. Systematic departures from the frontier: A framework for the analysis of firm inefficiency. International Economic Review32:715-723.
39.
Ruggiero, J.1996a. Efficiency of educational production: An analysis of New York school districts. Review of Economics and Statistics78:499-509.
40.
Ruggiero, J.1996b. On the measurement of technical efficiency in the public sector. European Journal of Operational Research90:553-565.
41.
Seiford, L. M., and R. M. Thrall. 1990. Recent development in DEA: The mathematical approach to frontier analysis. Journal of Econometrics46:7-38.
42.
U.S. Department of Commerce. 1995. County and City Data Book 1994. Washington, DC: Bureau of the Census.
43.
U.S. Department of Education. 1994. School District Data Book. Washington, DC: National Center for Education Statistics.
44.
Wildasin, D. E.1986. Urban public finance. New York: Hardwood.
45.
Wise, C. R.1990. Public service configurations and public organization: Public organization design in the post-privatization era. Public Administration Review50:141-155.
46.
Wyckoff, J. H., and J. Lavigne. 1992. The technical inefficiency of public elementary school in New York. Working paper, State University of New York at Albany.
47.
Yuengert, A. W.1993. The measurement of efficiency in life insurance: Estimates of a mixed normal-gamma error model. Journal of Banking and Finance17:483-496.
48.
Zimmerman, D.1983. Resource misallocation from interstate tax exportation: Estimates of excess spending and welfare loss in a median framework. National Tax Journal36:183-201.