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Secondary schools efficiencyand non-controllable inputs: sensibility of the results to different DEA model specifications

  • José Manuel Cordero Ferrera

    ()

    (Universidad de Extremadura)

  • Francisco Pedraja Chaparro

    (Universidad de Extremadura)

  • Javier Salinas Jiménez

    ()

    (Instituto de Estudios Fiscales. Universidad de Extremadura)

Registered author(s):

    The aim of this paper is to study how much sensitive efficiency scores are when different approaches proposed in the literature are used to include exogenous factors in efficiency analysis. Specifically, we will concentrate on two crucial issues. One the one hand, although we have an extensive data set on these variables derived from school surveys, it is not possible to use all these data, so we consider the possibility of either including the most relevant variables in the efficiency analysis or using Principal Components Analysis to summarise information contained in such variables. On the other hand, two alternative methodologies are considered to include these factors in efficiency analyisis, we will compare the approach according to which such factors must be taken into account to calculate the final efficiency indices and alternative multi-stage approaches. The analysis covers 79 public high schools in the region of Extremadura (Spain) for the 2001-02 school year.

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    File URL: http://www.ief.es/documentos/recursos/publicaciones/revistas/hac_pub/173_Eficiencia.pdf
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    Article provided by IEF in its journal Hacienda Pública Española/Revista de Economía Pública.

    Volume (Year): 173 (2005)
    Issue (Month): 2 (June)
    Pages: 61-83

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    Handle: RePEc:hpe:journl:y:2005:v:173:i:2:p:61-83
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    1. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-77, September.
    2. Cinzia Daraio & Leopold Simar, 2003. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," LEM Papers Series 2003/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. A. Bessent & W. Bessent & J. Kennington & B. Reagan, 1982. "An Application of Mathematical Programming to Assess Productivity in the Houston Independent School District," Management Science, INFORMS, vol. 28(12), pages 1355-1367, December.
    4. Bradley, Steve & Taylor, Jim, 2002. "The Effect of the Quasi-market on the Efficiency-Equity Trade-Off in the Secondary School Sector," Bulletin of Economic Research, Wiley Blackwell, vol. 54(3), pages 295-314, July.
    5. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    6. Hanushek, Eric, 1971. "Teacher Characteristics and Gains in Student Achievement: Estimation Using Micro Data," American Economic Review, American Economic Association, vol. 61(2), pages 280-88, May.
    7. B. Hollingsworth & P. Smith, 2003. "Use of ratios in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 10(11), pages 733-735.
    8. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    9. Muniz, M. A., 2002. "Separating managerial inefficiency and external conditions in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(3), pages 625-643, December.
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