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Anticipating the Consequences of School Reform: A New Use of DEA

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Author Info

  • Shawna Grosskopf

    (Department of Economics, Oregon State University, Corvallis, Oregon 97331)

  • Kathy J. Hayes

    (Dedman College, Southern Methodist University, PO Box 750235, Dallas, Texas 75275-0235)

  • Lori L. Taylor

    (Research Department, Federal Reserve Bank of Dallas, 2200 North Pearl Street, Dallas, Texas 75201)

  • William L. Weber

    (Department of Economics, Southeast Missouri State University, Cape Girardeau, Missouri 63701)

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    Abstract

    We use DEA-type linear programming techniques to simulate a basic component of educational reform-eliminating restrictions on the allocation of school personnel. Our technique allows us to identify potential output gains (or equivalently potential cost savings) from reform. We can also identify which personnel groups are likely to gain and lose under this reform. When we apply our model to a sample of Texas school districts, we find evidence that the educational establishment has substantial economic rents to protect from school reform, and that the primary beneficiaries of reform are likely to be affluent school districts with few minority students. The technique, which relies on the relationship between the direct and indirect distance functions, can be easily generalized to measure the potential gains from removing other input restrictions such as union work rules, environmental regulations, or deed restrictions.

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    File URL: http://dx.doi.org/10.1287/mnsc.45.4.608
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 45 (1999)
    Issue (Month): 4 (April)
    Pages: 608-620

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    Handle: RePEc:inm:ormnsc:v:45:y:1999:i:4:p:608-620

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    Web page: http://www.informs.org/
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    Related research

    Keywords: data envelopment analysis; school reform; distance functions; school efficiency; measuring potential gains from reform; measuring economic rents; input deregulation;

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    Cited by:
    1. Primont, Diane F. & Domazlicky, Bruce, 2006. "Student achievement and efficiency in Missouri schools and the No Child Left Behind Act," Economics of Education Review, Elsevier, vol. 25(1), pages 77-90, February.
    2. Waldo, Staffan, 2006. "Competition and Public School Efficiency in Sweden," Working Papers 2006:7, Lund University, Department of Economics.
    3. Grosskopf, Shawna & Moutray, Chad, 2001. "Evaluating performance in Chicago public high schools in the wake of decentralization," Economics of Education Review, Elsevier, vol. 20(1), pages 1-14, February.
    4. E. Grifell-Tatje & C. A. K. Lovell, 2013. "Productivity, Price Recovery, Capacity Constraints and their Financial Consequences," CEPA Working Papers Series WP032013, School of Economics, University of Queensland, Australia.
    5. Waldo, Staffan, 2006. "School Vouchers and Public School Productivity - The Case of the Swedish Large Scale Voucher Program," Working Papers 2006:8, Lund University, Department of Economics.
    6. Cheng, Gang & Zervopoulos, Panagiotis & Qian, Zhenhua, 2011. "A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis," MPRA Paper 30951, University Library of Munich, Germany.
    7. Fukuyama, Hirofumi & Weber, William L., 2005. "Estimating output gains by means of Luenberger efficiency measures," European Journal of Operational Research, Elsevier, vol. 164(2), pages 535-547, July.
    8. Waldo, Staffan, 2002. "Efficiency in Public Education," Working Papers 2002:10, Lund University, Department of Economics.
    9. Grosskopf, Shawna & Hayes, Kathy J. & Taylor, Lori L. & Weber, William L., 2001. "On the Determinants of School District Efficiency: Competition and Monitoring," Journal of Urban Economics, Elsevier, vol. 49(3), pages 453-478, May.
    10. M. Portela & A. Camanho & A. Keshvari, 2013. "Assessing the evolution of school performance and value-added: trends over four years," Journal of Productivity Analysis, Springer, vol. 39(1), pages 1-14, February.
    11. Gary Ferrier & Hervé Leleu & Vivian Valdmanis, 2009. "Hospital capacity in large urban areas: is there enough in times of need?," Journal of Productivity Analysis, Springer, vol. 32(2), pages 103-117, October.
    12. Athanassopoulos, Antreas & Gounaris, Chrysostomos, 2001. "Assessing the technical and allocative efficiency of hospital operations in Greece and its resource allocation implications," European Journal of Operational Research, Elsevier, vol. 133(2), pages 416-431, January.
    13. Hirofumi Fukuyama & William L. Weber, 2008. "Indicators and indexes of directional output loss and input allocative inefficiency," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 565-574.
    14. W. Cooper & L. Seiford & K. Tone & J. Zhu, 2007. "Some models and measures for evaluating performances with DEA: past accomplishments and future prospects," Journal of Productivity Analysis, Springer, vol. 28(3), pages 151-163, December.
    15. Silva Portela, Maria Conceicao A. & Thanassoulis, Emmanuel, 2001. "Decomposing school and school-type efficiency," European Journal of Operational Research, Elsevier, vol. 132(2), pages 357-373, July.
    16. Dervaux, B. & Leleu, H. & Nogues, H. & Valdmanis, V., 2006. "Assessing French nursing home efficiency: An indirect approach via budget-constrained DEA models," Socio-Economic Planning Sciences, Elsevier, vol. 40(1), pages 70-91, March.
    17. Waldo, Staffan, 2000. "Municipalities as Educational Producers - An Efficiency Approach," Working Papers 2000:19, Lund University, Department of Economics, revised 25 Apr 2001.
    18. Athanassopoulos, Antreas D., 2004. "Using frontier efficiency models as a tool to re-engineer networks of public sector branches: An application to the Hellenic Tobacco Organization," European Journal of Operational Research, Elsevier, vol. 154(2), pages 533-547, April.
    19. Brockett, Patrick L. & Cooper, W.W. & Lasdon, Leon & Parker, Barnett R., 2005. "A note extending Grosskopf, Hayes, Taylor and Weber, "Anticipating the consequences of school reform: A new use of DEA"," Socio-Economic Planning Sciences, Elsevier, vol. 39(4), pages 351-359, December.

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