Efficiency, costs, rankings and heterogeneity: the case of US higher education

Abstract

Among the major trends in the higher education (HE) sector, the development of rankings as a policy and managerial tool is of particular relevance. However, despite the diffusion of these instruments, it is still not clear how they relate with traditional performance measures, like unit costs and efficiency scores. In this paper, we estimate a variety of models to evaluate costs in US higher education institutions. A particularly innovative feature of our approach involves the estimation of latent class and random parameter stochastic frontier models of a multiproduct cost function: this allows us fully to accommodate both the heterogeneity across institutions and the presence of technical inefficiencies. Such methodological strategy is essential in analyzing the US HE system, which is characterized by a strong internal differentiation. Our main findings are two. First, on a public policy ground, the estimates suggest that global economies could be achieved by effecting a reduction in the number of institutions providing undergraduate instruction, while increasing the number of institutions engaged in postgraduate activity. Second, the current existing rankings turn out as coherent with ratings provided by the calculation of efficiency scores.

Keywords:

• costs
• efficiency
• rankings
• stochastic frontier
• latent class
• random parameter

Notes

1. Multiproduct organizations have been the subject of much research since the seminal contribution of Baumol, Panzar, and Willig (1982). This topic is particularly interesting for policy and practice; such organizations enjoy different resource endowments and so specialize in the production of different outputs. The structure of costs in these organizations likely differs across firms, and this heterogeneity gives rise to some interesting issues surrounding the evaluation of overall organizational performance.

2. The academic literature also pointed out that universities could contribute to the economic growth of the territories in which they operate; see Huggins and Johnston (2009).

3. Nevertheless, given the difficulty of identifying proper measures for the ‘third mission’ work of this kind, estimated cost functions usually include only measures of teaching and research; indeed only a very few attempts have been made to include proxy for the ‘third mission’ (an exception is G. Johnes et al. 2005; J. Johnes, Johnes, and Thanassoulis 2008).

4. G. Johnes et al. (2005) also include a quality measure in their work. Collinearity problems often preclude this.

5. The definition is slightly different, albeit equivalent, for public universities on the one hand and private universities on the other. This is because accounting principles for the former follow the guidelines of the Governmental Accounting Standards Board while those for the latter follow the guidelines of the Financial Accounting Standards Board.