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Efficiency Aspects of Government Secondary School Finances in New South Wales: Results from a Two-Stage Double-Bootstrap DEA at the School Level

  • Alfred A. Haug

    ()

    (Department of Economics, University of Otago, New Zealand)

  • Vincent C. Blackburn

    ()

    (Finance and Investment New South Wales, Department of Education and Communities)

This study measures the efficiency of government secondary schools in New South Wales, Australia, using a recently developed methodology of two-stage semi-parametric modeling. In contrast to previous research comparing school performance, we control for prior academic achievement of students by looking at the changes in academic achievements over a two year period, at the school level, from 2008 to 2010, and employ detailed financial data for deriving the envelope for the production frontier of the schools. Using Simar and Wilson's (2007) double bootstrap procedure for data envelopment analysis (DEA), the study finds that schools with higher student retention rates, higher total student numbers, boys or girls only, and selective admissions do better than other schools. On the other hand, a negative influence comes from a school's location in provincial and outer metropolitan areas, a higher ratio of disadvantaged students at a school, and a school's specialization in areas such as languages, performing arts, sports, etc. A surprising result is that the socio-economic characteristics of the families of students attending the school has no significant effect on their academic performance, nor does the average of the years of service of the teachers at a specific school.

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Paper provided by University of Otago, Department of Economics in its series Working Papers with number 1316.

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Length: 29 pages
Date of creation: Nov 2013
Date of revision: Nov 2013
Handle: RePEc:otg:wpaper:1316
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  1. W. Alexander & Alfred Haug & Mohammad Jaforullah, 2010. "A two-stage double-bootstrap data envelopment analysis of efficiency differences of New Zealand secondary schools," Journal of Productivity Analysis, Springer, vol. 34(2), pages 99-110, October.
  2. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
  3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
  4. Cummins, J. David & Weiss, Mary A. & Xie, Xiaoying & Zi, Hongmin, 2010. "Economies of scope in financial services: A DEA efficiency analysis of the US insurance industry," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1525-1539, July.
  5. Chang, Hsihui & Chang, Wen-Jing & Das, Somnath & Li, Shu-Hsing, 2004. "Health care regulation and the operating efficiency of hospitals: Evidence from Taiwan," Journal of Accounting and Public Policy, Elsevier, vol. 23(6), pages 483-510.
  6. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
  7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
  8. Steve Bradley & Mirko Draca & Colin Green, 2004. "School Performance in Australia: Is There a Role for Quasi-Markets?," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 37(3), pages 271-286, 09.
  9. Otgontsetseg Erhemjamts & J. Tyler Leverty, 2010. "The Demise of the Mutual Organizational Form: An Investigation of the Life Insurance Industry," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(6), pages 1011-1036, 09.
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