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Evaluating the performance of higher institutions in Europe. A nonparametric efficiency analysis of 944 institutions

Artikel i vetenskaplig tidskrift
Författare Ann Veiderpass
Maureen McKelvey
Publicerad i Applied Economics
Volym 48
Nummer/häfte 16
Sidor 1504-1514
ISSN 0003-6846
Publiceringsår 2016
Publicerad vid Institutionen för ekonomi och samhälle, Innovation and Entrepreneurship (IIE)
Institutionen för nationalekonomi med statistik
Sidor 1504-1514
Språk en
Länkar dx.doi.org/10.1080/00036846.2015.11...
Ämnesord Higher education institutions, OECD countries, technical efficiency, non-parametric analysis, bootstrapping, Eumida database
Ämneskategorier Ekonomi och näringsliv

Sammanfattning

Although a long tradition exists of studying the economics of education, performance comparisons of different kinds have traditionally been difficult to undertake. An important impediment has been the lack of comparable data. To a large extent, this study remedies the shortcomings of earlier studies. Our contribution is two-fold. First, the current higher education policy of contraction and economizing common to most European countries, make knowledge of potential efficiency gains crucial. Second, a unique database allows us to study a broad diversity of organizations as well as organizations located in a number of different European countries. The study suggests evaluating Higher Education Institution (HEI) performance in a production theory context, applying the well-known Data Envelopment Analysis (DEA) method to a cross section of 944 HEIs in 17 European countries. The DEA approach is particularly suitable in this context where little is known about production technologies and economic behaviour of the HEIs. On average, provision of education is found to be most efficient in the Slovak Republic followed by Belgium and Latvia, while Denmark and Norway display the lowest efficiency. The study also indicates a positive relation between efficiency and HEI size and efficiency and research intensity. Furthermore, the study points to the importance of continued data collection.

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