Efficiency of university education: A partial frontier analysis


  • Rafael Antonio Viana Faculty of Human Sciences. Department of Economics. Universidad Industrial de Santander.
  • José M. Arranz Department of Economics. Faculty of Economics, Business and Tourism. University of Alcalá https://orcid.org/0000-0001-8112-2867
  • Carlos García-Serrano Department of Economics. Faculty of Economics, Business and Tourism. University of Alcalá




efficiency, tertiary education, order m and meta-frontier models


This article investigates the efficiency of the university education using two linked databases (Saber Pro and Saber 11) from the Colombian Institute for Evaluation of Education (ICFES) corresponding to 2014. We use a non-parametric frontier approach that combines the “order m†technique with the concept of a meta-frontier to disaggregate students’ total efficiency in generic skills in quantitative reasoning, critical reading, and written communication, into the parts attributable to the students themselves and the university. The analysis is performed by academic programme and by education sector (public vs. private). Results indicate that most of the inefficiency of students in the assessment of generic skills in higher education is attributable to the students themselves and a significant number of students could improve their performance in the assessment in each of the academic programmes if they performed as efficiently as those located on the frontier. Furthermore, the inefficiency share of students varies between academic programmes and university sectors, with students in the private sector more inefficient than those in the public sector in some and less inefficient in others. This research constitutes the first application of the technique of “order m†with the approach of the meta-frontier for the analysis of educational efficiency using data at the student and university levels.


Abbott, M., & Doucouliagos, C. (2003). The efficiency of Australian universities: a data envelopment analysis. Economics of Education Review, 22(1), 89-97. https://doi.org/10.1016/s0272-7757(01)00068-1

Abramo, G., Cicero, T., & D’Angelo, C. A. (2011). A field-standardized application of DEA to national-scale research assessment of universities. Journal of Informetrics, 5(4), 618-628. https://doi.org/10.1016/j.joi.2011.06.001

Ahn, T., Charnes, A., & Cooper, W. W. (1988). Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning. Socio-Economic Planning Sciences, 22(6), 259-269. https://doi.org/10.1016/0038-0121(88)90008-0

Battese, G. E., & Rao, D. S. P. (2002). Technology Gap, Efficiency and a Stochastic Metafrontier Function. International Journal of Business and Economics 1(2), 1–7.

Battese, G. E., Rao, D. S. P., & O’Donnell, C. J. (2004). A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies. Journal of Productivity Analysis, 21(1), 91-103. https://doi.org/10.1023/b:prod.0000012454.06094.29

Black, H. T., & Duhon, D. L. (2003). Evaluating and Improving Student Achievement in Business Programs: The Effective Use of Standardized Assessment Tests. Journal of Education for Business, 79(2), 90-98. https://doi.org/10.1080/08832320309599095

Cazals, C., Florens, J.-P., & Simar, L. (2002). Nonparametric frontier estimation: a robust approach. Journal of Econometrics, 106(1), 1-25. https://doi.org/10.1016/s0304-4076(01)00080-x

Chakraborty, K. (2009). Efficiency in Public Education - The role of socio-economic variables. Research in Applied Economics, 1(1), 1-18. https://doi.org/10.5296/rae.v1i1.137

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of DMUs, European Journal of Operational Research 2, 429-444.

Cordero, J. M., & Simancas, R. R. (2013). Separating the school effect from students’ performance: Evidence from Spanish PISA data. XXII Jornadas de la Asociación de Economía de la Educación, 1-22. A. Coruña.

Daraio, C., & Simar, L. (2010). Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications. Springer.

De Borger, B., Kerstens, K., Moesen, W., & Vanneste, J. (1994). A non-parametric Free Disposal Hull (FDH) approach to technical efficiency: an illustration of radial and graph efficiency measures and some sensitivity results. Swiss Journal of Economics and Statistics 130(4), 647-667.

De Witte, K., Thanassoulis, E., Simpson, G., Battisti, G., & Charlesworth-May, A. (2010). Assessing pupil and school performance by non-parametric and parametric techniques. Journal of the Operational Research Society, 61(8), 1224-1237. https://doi.org/10.1057/jors.2009.50

Deprins, D., Simar, L., & Tulkens, H. (1984). Measuring Labor Inefficiency in Post Offices. In Marchand, P., Pestieau, P., & Tulkens, H. (Eds.) Concepts and Measurements, Amsterdam, North Holland, 243-267.

Diamond, A. M., & Medewitz, J. N. (1990). Use of Data Envelopment Analysis in an Evaluation of the Efficiency of the DEEP Program for Economic Education. The Journal of Economic Education, 21(3), 337-354. https://doi.org/10.1080/00220485.1990.10844680

Diewert, W. E., & Fox, K. J. (2014). Reference technology sets, Free Disposal Hulls and productivity decompositions. Economics Letters, 122(2), 238-242. https://doi.org/10.1016/j.econlet.2013.11.026

Gupta, S., Honjo, K., & Verhoeven, M. (1997). The Efficiency of Government Expenditure: Experiences from Africa. IMF.

Johnes, J. (2006a). Data envelopment analysis and its application to the measurement of efficiency in higher education. Economics of Education Review, 25(3), 273-288. https://doi.org/10.1016/j.econedurev.2005.02.005

Johnes, J. (2006b). Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education. Bulletin of Economic Research, 58(2), 75-104. https://doi.org/10.1111/j.0307-3378.2006.00238.x

Johnes, J., & Taylor, J. (1987). Degree quality: An investigation into differences between UK universities. Higher Education, 16(5), 581-602. https://doi.org/10.1007/bf00128423

Kuah, C. T., & Wong, K. Y. (2011). Efficiency assessment of universities through data envelopment analysis. Procedia Computer Science, 3, 499-506. https://doi.org/10.1016/j.procs.2010.12.084

O’Donnell, C. J., Rao, D. S. P., & Battese, G. E. (2007). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics, 34(2), 231-255. https://doi.org/10.1007/s00181-007-0119-4

Rodgers, T., & Ghosh, D. (2001). Measuring the determinants of quality in UK higher education: a multinomial logit approach. Quality Assurance in Education, 9(3), 121-126. https://doi.org/10.1108/09684880110399059

Silva Portela, M. C. A., & Thanassoulis, E. (2001). Decomposing school and school-type efficiency. European Journal of Operational Research, 132(2), 357-373. https://doi.org/10.1016/


Thanassoulis, E. (1999). Setting Achievement Targets for School Children. Education Economics, 7(2), 101-119. https://doi.org/10.1080/09645299900000010

Thanassoulis, E., Da Conceição, M., & Silva Portela, A. (2002). School Outcomes: Sharing the Responsibility Between Pupil and School1. Education Economics, 10(2), 183-207. https://doi.org/10.1080/09645290210126913

Thieme, C., Prior, D., & Tortosa-Ausina, E. (2013). A multilevel decomposition of school performance using robust nonparametric frontier techniques. Economics of Education Review, 32, 104-121. https://doi.org/10.1016/j.econedurev.2012.08.002

Zhang, Y., & Bartels, R. (1998). The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand. Journal of Productivity Analysis 9, 187-204. https://doi.org/10.1023/A:1018395303580

Zoghbi, A. C., Rocha, F., & Mattos, E. (2013). Education production efficiency: Evidence from Brazilian universities. Economic Modelling, 31, 94-103. https://doi.org/10.1016/j.econmod.2012.11.018






Regular articles

How to Cite

Efficiency of university education: A partial frontier analysis. (2020). Latin American Economic Review, 29, 1-16. https://doi.org/10.47872/laer.v29.3

Similar Articles

1-10 of 11

You may also start an advanced similarity search for this article.