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Measuring efficiency of Tunisian schools in the presence of quasi-fixed inputs: A bootstrap data envelopment analysis approach

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  • Essid, Hédi
  • Ouellette, Pierre
  • Vigeant, Stéphane

Abstract

The objective of this paper is to measure the efficiency of high schools in Tunisia. We use a statistical data envelopment analysis (DEA)-bootstrap approach with quasi-fixed inputs to estimate the precision of our measure. To do so, we developed a statistical model serving as the foundation of the data generation process (DGP). The DGP is constructed such that we can implement both smooth homogeneous and heterogeneous bootstrap methods. Bootstrap simulations were used to estimate and correct the bias, and to construct confidence intervals for the efficiency measures. The simulation results show that the efficiency measures are subject to sampling variations. The adjusted measure reveals that high schools with residence services would have to give up less than 12.1% of their resources on average to be efficient.

Suggested Citation

  • Essid, Hédi & Ouellette, Pierre & Vigeant, Stéphane, 2010. "Measuring efficiency of Tunisian schools in the presence of quasi-fixed inputs: A bootstrap data envelopment analysis approach," Economics of Education Review, Elsevier, vol. 29(4), pages 589-596, August.
    • Handle: RePEc:eee:ecoedu:v:29:y:2010:i:4:p:589-596
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    1. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    2. Lee, Boon L. & Worthington, Andrew C., 2014. "Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 15-20.
    3. Luque, Mariano & Marcenaro-Gutierrez, Oscar D. & Ruiz, Ana B., 2020. "Evaluating the global efficiency of teachers through a multi-criteria approach," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    4. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2020. "Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    5. Ben Yahia, Fatma & Essid, Hédi & Rebai, Sonia, 2018. "Do dropout and environmental factors matter? A directional distance function assessment of tunisian education efficiency," International Journal of Educational Development, Elsevier, vol. 60(C), pages 120-127.
    6. Ana B. Ruiz & Mariano Luque & Oscar D. Marcenaro-Gutierrez, 2022. "On the use of Synthetic Indexes Based on Multi-Criteria Decision Making to Study the Efficiency of Teachers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(3), pages 1269-1300, October.
    7. Venkatesh, Anand & Kushwaha, Shivam, 2018. "Short and long-run cost efficiency in Indian public bus companies using Data Envelopment Analysis," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 29-36.
    8. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    9. Agasisti, Tommaso & Zoido, Pablo, 2019. "The efficiency of schools in developing countries, analysed through PISA 2012 data," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    10. Touati-Tliba, Mohamed, 2024. "Comparative performance of Algeria's education districts: The Influence of colonial legacy through cultural capital," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    11. Boon Lee & Andrew Worthington, 2011. "Operational performance of low-cost carriers and international airlines: New evidence using a bootstrap truncated regression," School of Economics and Finance Discussion Papers and Working Papers Series 271, School of Economics and Finance, Queensland University of Technology.
    12. H餩 Essid & Pierre Ouellette & St鰨ane Vigeant, 2013. "Small is not that beautiful after all: measuring the scale efficiency of Tunisian high schools using a DEA-bootstrap method," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1109-1120, March.
    13. Yahia, F.B. & Essid, H., 2019. "Determinants of Tunisian Schools’ Efficiency: A DEA-Tobit Approach," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(1), pages 44-56, February.
    14. Giuseppe Di Giacomo & Aline Pennisi, 2015. "Assessing Primary and Lower Secondary School Efficiency Within Northern, Central and Southern Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(2), pages 287-311, July.
    15. Yang, Jun & Zhang, Tengfei & Sheng, Pengfei & Shackman, Joshua D., 2016. "Carbon dioxide emissions and interregional economic convergence in China," Economic Modelling, Elsevier, vol. 52(PB), pages 672-680.
    16. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.

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    More about this item

    Keywords

    Educational economics Efficiency Productivity Data envelopment analysis Bootstrap Quasi-fixed inputs;

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • I2 - Health, Education, and Welfare - - Education

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