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Efficiency and Equity in School Funding: A Case Study for Kansas

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  • Kalyan Chakraborty
  • John Poggio

Abstract

This study measures cost inefficiency of Kansas public school districts and applied both mathematical programming and stochastic frontier approach. The empirical study uses two-stage data envelopment analysis model and the cost inefficiency effects model proposed by Battese and Coelli (Empirical Economics 24:325–332, 1995 ) and applied to a panel data. The results found mean inefficiencies from these two models are very close. The results indicate that Kansas school districts, on average, exhibit cost inefficiency in their operations, however, there is a tendency for inefficiencies to decline over time. The study does not find any strong evidence for lower efficiency due to lower expenditure per-pupil. Instead, we found inconclusive evidences where lower efficiency for certain school districts could be assigned to unfavorable environmental cost conditions. Copyright International Atlantic Economic Society 2008

Suggested Citation

  • Kalyan Chakraborty & John Poggio, 2008. "Efficiency and Equity in School Funding: A Case Study for Kansas," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(2), pages 228-241, May.
    • Handle: RePEc:kap:iaecre:v:14:y:2008:i:2:p:228-241:10.1007/s11294-008-9137-z
    DOI: 10.1007/s11294-008-9137-z
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    References listed on IDEAS

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    1. Kalyan Chakraborty & Basudeb Biswas & W. Cris Lewis, 2001. "Measurement of Technical Efficiency in Public Education: A Stochastic and Nonstochastic Production Function Approach," Southern Economic Journal, John Wiley & Sons, vol. 67(4), pages 889-905, April.
    2. Shawna Grosskopf & Kathy J. Hayes & Lori L. Taylor & William L. Weber, 1997. "Budget-Constrained Frontier Measures Of Fiscal Equality And Efficiency In Schooling," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 116-124, February.
    3. Greene, William, 2001. "New Developments in the Estimation of Stochastic Frontier Models with Panel Data," Efficiency Series Papers 2001/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
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    5. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    6. Downes, Thomas A. & Pogue, Thomas F., 1994. "Adjusting School Aid Formulas for the Higher Cost of Educating Disadvantaged Students," National Tax Journal, National Tax Association;National Tax Journal, vol. 47(1), pages 89-110, March.
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    Cited by:

    1. Son Nghiem & Ha Trong Nguyen & Luke B. Connelly, 2016. "The Efficiency of Australian Schools: A Nationwide Analysis Using Gains in Test Scores of Students as Outputs," Economic Papers, The Economic Society of Australia, vol. 35(3), pages 256-268, September.
    2. Nghiem, Son & Nguyen, Ha & Connelly, Luke, 2014. "The Efficiency of Australian Schools: Evidence from the NAPLAN Data 2009-2011," MPRA Paper 56231, University Library of Munich, Germany.
    3. G. Sav, 2012. "Stochastic Cost Frontier and Inefficiency Estimates of Public and Private Universities: Does Government Matter?," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 18(2), pages 187-198, May.
    4. G. Thomas Sav, 2012. "Cost Efficiencies and Rankings of Flagship Universities," American Journal of Economics and Business Administration, Science Publications, vol. 3(4), pages 596-603, January.
    5. Kalyan Chakraborty & Vincent C. Blackburn, 2013. "Efficiency and Equity in Funding for Government Schools in Australia," Australian Economic Papers, Wiley Blackwell, vol. 52(3-4), pages 127-142, December.

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    More about this item

    Keywords

    Cost inefficiency; Stochastic cost frontier; Function; Public education; D2; I2; R0;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • I2 - Health, Education, and Welfare - - Education
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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