The differential effects of competitive funding on the production frontier and the efficiency of universities

Abstract

European governments increasingly employ competitive university funding to improve performance in higher education. The framework that is developed in this paper suggests a donor-specific trade-off between fostering best performing universities and increasing university efficiency when introducing competitive funding in the university sector. We test this assertion based on a university-level panel dataset across eight European countries from 1994-2006. Estimating a simultaneous two-stage Stochastic Frontier Approach, we find that international public funds decrease the productivity of the best performing universities, which suggests a non-negligible effect because of the administrative burden induced by competitive funding. However, the competition for international public funds also disciplines universities as evidenced by a positive impact on efficiency. Conversely, tuition fees enhance the productivity of the best performing universities but increase the spread of universities with lower productivity, which suggests a strong sorting effect

The Index Number Problem with DEA: Insights from European University Efficiency Data

“…This led to the specific DEA method suggestion by Charnes, Cooper, and Rhodes in 1978 [24]. Reasons for the increasing use of this efficiency analysis technique in higher education research are the fact that no a priori knowledge about a production function is required, only real-life data is used, and a multitude of inputs can be combined with a multitude of outputs, which is very typical for universities as "multi-product-organisations" [68][69][70][71][72][73].…”

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

“…This led to the specific DEA method suggestion by Charnes, Cooper and Rhodes in 1978 [68]. Advantages of the increasing use in management research are the facts that no a priori existing knowledge of a production function is required, only real-life data is used (no hypothetical production function or efficiency values); and a multitude of inputs can be combined with a multitude of outputs, which is very typical for LSP as complex and high-level service providers as well as other service industries like health care or higher education [69][70][71][72][73].…”

Do Forwarders Improve Sustainability Efficiency? Evidence from a European DEA Malmquist Index Calculation

“…For third party funding, for example, it is acknowledged in university efficiency analysis that this special area of analysis has input characteristics (financing further input factors like personnel or research expenses) but is at the same time in the majority of applications used as a suitable quantitative indicator for research output and excellence, cp. [148]. This could be applied to the question of employment and FTE indicators in a comprehensive sustainability evaluation in the same fashion.…”

“…This led to the specific DEA method suggestion by Charnes, Cooper, and Rhodes [24]. The advantages of its increasing use in higher education research are the fact that no a priori existing knowledge of a production function is required, only real-life data is used (no hypothetical production function or efficiency values), and a multitude of inputs can be combined with a multitude of outputs, which is very typical for LSP, as complex and high-level service providers as well as other industries like health care or higher education [147][148][149][150][151] ( Bessent et al, 1983). DEA studies Decision Making Units (DMUs), which can be seen as the entities responsible for input, throughput, and output decision making [152] (p. 22); DMUs like LSP can be evaluated and compared, showing a specific level of decision making success in terms of overall efficiency.…”