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Competing in the Higher Education Market: Empirical Evidence for Economies of Scale and Scope in German Higher Education Institutions

Author Info

Listed author(s):
  • Maria Olivares

    ()

    (University of Zuerich, Department of Business Administration, Switzerland)

  • Heike Wetzel

    ()

    (University of Cologne, Institute of Energy Economics, Germany)

Abstract

Since the late 1990s, the European higher education system has had to face deep structural changes. With the public authorities seeking to create an environment of quasi-markets in the higher education sector, the increased competition induced by recent reforms has pushed all publicly financed higher education institutions to use their resources more efficiently. Higher education institutions increasingly now aim at differentiating themselves from their competitors in terms of the range of outputs they produce. Assuming that different market positioning strategies will have different effects on the performance of higher education institutions, this paper explores the existence of economies of scale and scope in the German higher education sector. Using an input-oriented distance function approach, we estimate the economies of scale and scope and the technical efficiency for 154 German higher education institutions from 2001 through 2007. Our results suggest that comprehensive universities should indeed orientate their activities to the concept of a full-university that combines teaching and research activities across a broad range of subjects. In contrast, praxis-oriented small and medium-sized universities of applied sciences should specialise in the teaching and research activities they conduct.

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Paper provided by University of Lüneburg, Institute of Economics in its series Working Paper Series in Economics with number 223.

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Length: 37 pages
Date of creation: Dec 2011
Handle: RePEc:lue:wpaper:223
Contact details of provider: Web page: http://leuphana.de/institute/ivwl.html

Keywords: Higher Education Production; Economies of Scale and Scope; Technical Efficiency; Stochastic Frontier Analysis; Input Distance Function;

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Find related papers by JEL classification:
  • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
  • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
  • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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  1. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
  2. Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
  3. Schubert, Torben, 2009. "Empirical observations on New Public Management to increase efficiency in public research--Boon or bane?," Research Policy, Elsevier, vol. 38(8), pages 1225-1234, October.
  4. Tommaso Agasisti & Geraint Johnes, 2010. "Heterogeneity and the evaluation of efficiency: the case of Italian universities," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1365-1375.
  5. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
  6. Johnes, Geraint, 1997. "Costs and Industrial Structure in Contemporary British Higher Education," Economic Journal, Royal Economic Society, vol. 107(442), pages 727-737, May.
  7. Philippe K Widmer & Peter Zweifel & Mehdi Farsi, 2010. "Accounting For Heterogeneity In The Measurement of Hospital Performance," Economics Discussion / Working Papers 10-21, The University of Western Australia, Department of Economics.
  8. Hajargasht, Gholamreza & Coelli, Tim & Rao, D.S. Prasada, 2008. "A dual measure of economies of scope," Economics Letters, Elsevier, vol. 100(2), pages 185-188, August.
  9. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
  10. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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Cited by:

  1. Calogero Guccio & Marco Ferdinando Martorana & Luisa Monaco, 2016. "Evaluating the impact of the Bologna Process on the efficiency convergence of Italian universities: a non-parametric frontier approach," Journal of Productivity Analysis, Springer, vol. 45(3), pages 275-298, June.
  2. Maria Olivares & Andrea Schenker-Wicki, 2012. "The Dynamics of Productivity in the Swiss and German University Sector: A Non-Parametric Analysis that Accounts for Heterogeneous Production," Working Papers 309, University of Zurich, Department of Business Administration (IBW).
  3. Thomas Bolli & Mehdi Farsi, 2015. "The dynamics of productivity in Swiss universities," Journal of Productivity Analysis, Springer, vol. 44(1), pages 21-38, August.
  4. Solange Alfinito & Manoel Brod Siqueira & Claudio V. Torres, 2016. "The student’s choice based on consumer psychology: an analysis applied to higher education institutions of Brazil," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 13(2), pages 185-201, July.
  5. Gralka, Sabine, 2016. "Persistent inefficiency in the higher education sector: Evidence from Germany," CEPIE Working Papers 06/16, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
  6. Wohlrabe, Klaus & Bornmann, Lutz & de Moya Anegon, Felix, 2017. "Wie effizient sind Universitäten in Deutschland, deren Zukunftskonzepte im Rahmen der Exzellenzinitiative ausgezeichnet wurden? Ein empirischer Vergleich von Input- und Output-Daten zur Forschung
    [    ," MPRA Paper 76218, University Library of Munich, Germany.
  7. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza, 2016. "Efficiency assessment and convergence in teaching and research in Italian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1063-1094, June.

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