In this paper we show the usefulness of recent advanced nonparametric efficiency techniques to model the performance of universities in the presence of observed and unobserved heterogeneity. Using directional distances for benchmarking purposes, we identify a latent heterogeneity factor related to the human capital of the universities and their management, that is independent from their size, and interpret the identified latent factor as a “quality” factor of the universities. After testing the significance of this latent factor, we investigate its impact on the boundary of the production set (efficient frontier) and on the distances of the units from the efficient frontier. The frontier and the efficiency distribution of our European Universities sample appear influenced by our estimated latent quality factor. We investigate these impacts from various points of view, including the trade-off between our quality factor and efficiency as well as the roles of size and specialization.

在本文中，我们显示了在存在观察到的和未观察到的异质性的情况下，最新的先进非参数效率技术对大学绩效进行建模的有用性。使用方向距离进行基准测试，我们确定了与大学及其管理的人力资本相关的潜在异质性因素，该异质性因素与它们的规模无关，并将识别出的潜在性因素解释为大学的“质量”因素。在测试了该潜在因素的重要性之后，我们研究了其对生产集边界（有效边界）以及单位与有效边界之间距离的影响。欧洲大学样本的边界和效率分布似乎受到我们估计的潜在质量因子的影响。