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Assessing the evolution of school performance and value-added: trends over four years

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  • M. Portela
  • A. Camanho

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  • A. Keshvari

Abstract

This paper explores the changes in value added (VA) of a sample of schools for cohorts of students finishing secondary education between 2005 and 2008. VA estimates are based on distance measures obtained from DEA models. These measures are computed for each pupil in each school, and evaluate the distance between the school frontier in a given year and a pooled frontier comprising all schools analysed. The school VA is then computed by aggregating the VA scores for the cohort of pupils attending that school in a given year. The ratio between VA estimates for two consecutive cohorts, that attended the school in different years, is taken as the index of VA change. However, the evolution of school performance over time should consider not only the movements of the school frontier, but should also take into account other effects, such as the proximity of the students to the best-practices, represented by the school frontier, observed over time. For that purpose we developed an enhanced Malmquist index to evaluate the evolution of school performance over time. One of the components of the Malmquist index proposed measures VA change, and the other measures the ability of all school students to move closer to their own school best practices over time. The approach developed is applied to a sample of Portuguese secondary schools. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • 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.
  • Handle: RePEc:kap:jproda:v:39:y:2013:i:1:p:1-14
    DOI: 10.1007/s11123-012-0263-5
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    References listed on IDEAS

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    1. M C A S Portela & E Thanassoulis & A Horncastle & T Maugg, 2011. "Productivity change in the water industry in England and Wales: application of the meta-Malmquist index," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2173-2188, December.
    2. Kirjavainen, Tanja & Loikkanent, Heikki A., 1998. "Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis," Economics of Education Review, Elsevier, vol. 17(4), pages 377-394, October.
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    8. A. Camanho & R. Dyson, 2006. "Data envelopment analysis and Malmquist indices for measuring group performance," Journal of Productivity Analysis, Springer, vol. 26(1), pages 35-49, August.
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    10. Laurens Cherchye & Kristof De Witte & Erwin Ooghe, 2008. "Equity and efficiency in private and public education: a nonparametric comparison," Working Papers of Department of Economics, Leuven ces0725, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    11. Ladd, Helen F. & Walsh, Randall P., 2002. "Implementing value-added measures of school effectiveness: getting the incentives right," Economics of Education Review, Elsevier, vol. 21(1), pages 1-17, February.
    12. Shawna Grosskopf & Kathy J. Hayes & Lori L. Taylor & William L. Weber, 1999. "Anticipating the Consequences of School Reform: A New Use of DEA," Management Science, INFORMS, vol. 45(4), pages 608-620, April.
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    14. M. C. Portela & A. S. Camanho, 2007. "Performance Assessment of Portuguese Secondary Schools," Working Papers de Economia (Economics Working Papers) 07, Católica Porto Business School, Universidade Católica Portuguesa.
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    Cited by:

    1. Aparicio, Juan & Crespo-Cebada, Eva & Pedraja-Chaparro, Francisco & Santín, Daniel, 2017. "Comparing school ownership performance using a pseudo-panel database: A Malmquist-type index approach," European Journal of Operational Research, Elsevier, vol. 256(2), pages 533-542.
    2. Laura López Torres & Diego Prior, 2014. "Measuring school demand in the presence of spatial dependence. A conditional approach," Investigaciones de Economía de la Educación volume 9, in: Adela García Aracil & Isabel Neira Gómez (ed.),Investigaciones de Economía de la Educación 9, edition 1, volume 9, chapter 4, pages 117-141, Asociación de Economía de la Educación.
    3. Kristof de Witte & Laura López-Torres, 2015. "Efficiency in Education. A Review of Literature and a Way Forward," Working Papers 1501, Departament Empresa, Universitat Autònoma de Barcelona, revised Apr 2015.
    4. Aparicio, Juan & López-Torres, Laura & Santín, Daniel, 2018. "Economic crisis and public education. A productivity analysis using a Hicks-Moorsteen index," Economic Modelling, Elsevier, vol. 71(C), pages 34-44.
    5. Blackburn, Vincent & Brennan, Shae & Ruggiero, John, 2014. "Measuring efficiency in Australian Schools: A preliminary analysis," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 4-9.
    6. Tommaso Agasisti, 2014. "How does schools’ efficiency look like across Europe? An empirical analysis of Germany, Spain, France, Italy and UK using OECD PISA2012 data," Working papers 9, Società Italiana di Economia Pubblica.

    More about this item

    Keywords

    Data envelopment analysis; Malmquist index; Secondary education; School value-added; C61; C67; I21;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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