Advanced indicators of productivity of universities. An application of robust nonparametric methods to italian data
(2004) , 41 pages
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- Abstract
- In recent years the pressure on public budgets in almost all industrialised countries has lead governments to pursue efficiency in the allocation and management of resources trying to apply to scientific research and higher education some fundamental ideas of the economic analysis such as the concepts of economies of scale and scope. This paper explores scale, scope and trade-off effects in scientific research and education. Advanced productivity methods are used to analyse the Italian system of universities. In particular, robust methods based on the concept of order −m frontiers (Cazals, Florens and Simar, 2002) are really useful in this framework for their properties of not being influenced by extremes and noise in the data. Furthermore, in the field of science and education, external factors and environmental conditions may be cause of heterogeneity and influence dramatically the performance of universities. Hence, we apply the Daraio and Simar (2003) full nonparametric methodology (that overcomes most limitations of previous one or two-stage approaches) to robustly take into account external environmental factors. From a preliminary investigation on Italian data we find that economies of scale and scope are not significant factors in explaining research and education productivity. We do not find any evidence of the trade-off research vs teaching: on the contrary, increasing scientific quality improves educational efficiency; on the other hand, a good educational efficiency does not deteriorate research efficiency. About the trade-off academic publications vs industry oriented research, local effects of a complementarity/rivalry relation seem to emerge: it seems that initially, collaboration with industry may improve productivity, but beyond a certain level the compliance with industry expectations may be too demanding and deteriorate the publication profile. Nevertheless, the existence of an inverted U−shaped relation should be confirmed by more evidence. Advanced robust methods in efficiency analysis are shown as useful tools for measuring and explaining the performance of a public research system of universities. Further developments of the analysis are outlined.
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Bonaccorsi, A., Daraio, C., & Simar, L. (2004). Advanced indicators of productivity of universities. An application of robust nonparametric methods to italian data (STAT Discussion Papers 0426). https://hdl.handle.net/2078.5/34933