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Measuring efficiency in Australian Schools: A preliminary analysis

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  • Blackburn, Vincent
  • Brennan, Shae
  • Ruggiero, John

Abstract

In this paper, we apply a public sector Data Envelopment Analysis model to estimate the efficiency of Australian primary and secondary schools. Standard microeconomic production theory showing the transformation of inputs into outputs is extended to allow nondiscretionary environmental variables characteristic of educational production. Failure to properly control for the socioeconomic environment leads to inappropriate comparisons and biased efficiency estimates. We employ a conditional estimator that does not allow a school with a better environment to serve as a benchmark for a school with a worse environment. The results suggest that Australian schools are moderately inefficient and that efficiency increases for the quintile of schools with the most favorable environment. Further, efficiency gains are realized with increasing enrollment.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:soceps:v:48:y:2014:i:1:p:4-9
    DOI: 10.1016/j.seps.2013.08.002
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    4. Kalyan Chakraborty & Richard K. Harper, 2017. "Measuring the Impact of Socio-Economic Factors on School Efficiency in Australia," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 45(2), pages 163-179, June.
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    6. 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.
    7. Olesen, Ole Bent & Petersen, Niels Christian & Podinovski, Victor V., 2017. "Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs," European Journal of Operational Research, Elsevier, vol. 261(2), pages 640-655.
    8. 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.
    9. Carla Haelermans & John Ruggiero, 2017. "Non-parametric estimation of the cost of adequacy in education: the case of Dutch schools," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 390-398, April.
    10. Fritz Schiltz & Kristof Witte & Deni Mazrekaj, 2020. "Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis," Annals of Operations Research, Springer, vol. 288(2), pages 529-546, May.
    11. K. Kounetas & G. Androulakis & M. Kaisari & G. Manousakis, 2023. "Educational reforms and secondary school's efficiency performance in Greece: a bootstrap DEA and multilevel approach," Operational Research, Springer, vol. 23(1), pages 1-29, March.
    12. Aatzaz Hassan & Muhammad Ramzan Sheikh & Rana Zafar Hayat & Neelam Asghar Ali, 2022. "An Efficiency Analysis of Public and Private Elementary Schools in Dera Ghazi Khan," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 8(3), pages 135-150, September.
    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. Konrad, Renata A. & Trapp, Andrew C. & Palmbach, Timothy M. & Blom, Jeffrey S., 2017. "Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications," European Journal of Operational Research, Elsevier, vol. 259(2), pages 733-745.
    15. Rebai, Sonia & Ben Yahia, Fatma & Essid, Hédi, 2020. "A graphically based machine learning approach to predict secondary schools performance in Tunisia," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    16. Manuel Salas‐Velasco, 2020. "Assessing the performance of Spanish secondary education institutions: Distinguishing between transient and persistent inefficiency, separated from heterogeneity," Manchester School, University of Manchester, vol. 88(4), pages 531-555, July.
    17. López-Torres, Laura & Nicolini, Rosella & Prior, Diego, 2017. "Does strategic interaction affect demand for school places? A conditional efficiency approach," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 89-103.

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