Abstract
The university efficiency indicators, computed as partial indices following the input–output approach, are subject to criticism mainly concerning the problem of comparability of institutions due to the influence of several environmental factors. The aim of this study is to construct comparable efficiency indicators for the university educational processes by using frontier production methods which enable us to solve the problem. The indicators are computed for the Italian State Universities by using a new data set referring to the cohort of students enrolled in the academic year 2004/2005. A comparison with the corresponding partial indicators usually employed is presented.
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- 1.
The faculty is the entity of a university that organizes teaching activities in a specific area (study subject). We are aware that there are various degree courses with different educational objectives within a faculty but it was not possible to consider them in our study due to lack of disaggregated data.
- 2.
After examining the reliability and quality of the data, two universities were excluded from the analysis.
- 3.
Although the number of graduates within the institutional time is the real output of the process, the indicator G1L can be considered as a second best result of the entire formation process bearing in mind the fact that some students take longer than three years to obtain their degrees.
- 4.
The results of the models FCES2, FCES3 and G1L are available from the authors on request.
References
Boero, G., Broccolini, C., Laureti, T., Naylor, R.: Velocità di progressione negli studi universitari: un confronto tra coorti pree post-riforma in Performance accademica e tassi di abbandono: una analisi dei primi effetti della riforma universitaria, a cura di Boero G. e Staffolani, S., Edizioni Cuec (2007)
European University Association (EUA): A Reference System for Indicators and Evaluation Procedures, by Tavenas T., Brussels (2004)
Goldstein, H., Spiegelhalter, D.J.: League tables and their limitations: statistical issues in comparisons of institutional performance (with discussion). J. R. Stat. Soc. A 159, 385–443 (1996)
Greene, W.: The econometric approach to efficiency analysis. In: Fried, O.H., Lovell, C.A.K., Schimdt, S. (eds.) The Measurement of Productive Efficiency and Productivity Growth. Oxford University Press, Oxford (2008).
Hadri, K.: Estimation of a doubly heteroscedastic frontier cost function. J. Bus. Econ. Stat. 17(3), 359–363 (1999)
Jondrow, J., Lovell, C.A.K., Materov, I.S., Schimdt, P.: On the estimation of technical inefficiency in the stochastic frontier production function model. J. Econometrics 19, 233–238 (1982)
Kumbhakar, S.C., Lovell, C.A.K.: Stochastic Frontier Analysis, Cambridge Books. Cambridge University Press, Cambridge (2000)
Laureti, T.: Modelling exogenous variables in human capital formation through a heteroscedastic stochastic frontier. Int. Adv. Econ. Res. 14 (1), 76–89(2008)
Laureti, T., Secondi, L.: Constructing university performance indicators in Italy: a comparative approach. In: Proceedings of the Business and Economic Statistics Section, JSM, 2009, pp. 4542–4554
Stevens, P.A.: The Determinants of Economic Efficiency in English and Welsh Universities, National Institute of Economic and Social Research, Discussion Paper N.185 (2001)
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Biggeri, L., Laureti, T., Secondi, L. (2013). Evaluating the Efficiency of the Italian University Educational Processes through Frontier Production Methods. In: Torelli, N., Pesarin, F., Bar-Hen, A. (eds) Advances in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35588-2_41
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