IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_11370.html
   My bibliography  Save this paper

The Market Power of Brazilian Private Higher Education Institutions: An Efficiency-Frontier Approac

Author

Listed:
  • Ana Maria de Paula Morais
  • Silvinha Vasconcelos
  • Marcelo Resende

Abstract

The Brazilian government started to implement, mainly from the 2000s onwards, mechanisms to stimulate the supply and demand for higher education in Brazil. Especially the offer of private higher education has shown strong growth in recent years as a result of systematic public policies, which has increased competition in this market. In this expansion scenario, it remains to be seen how the competitive market environment is configured in terms of market power. Therefore, this article intends to estimate the market power of Brazilian higher education institutions - HEIs from an alternative use of the stochastic frontier model, as proposed by Kumbhakar et. al (2012), for the period 2010 to 2019. This method is adopted because it solves the impasse of the lack of information on marginal costs, which prevents the application of other models for estimating market power. The results pointed to the presence of positive and significant market power of Brazilian HEIs, which may imply anti-competitive behavior.

Suggested Citation

  • Ana Maria de Paula Morais & Silvinha Vasconcelos & Marcelo Resende, 2024. "The Market Power of Brazilian Private Higher Education Institutions: An Efficiency-Frontier Approac," CESifo Working Paper Series 11370, CESifo.
    • Handle: RePEc:ces:ceswps:_11370
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp11370.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Flannery, Darragh & O’Donoghue, Cathal, 2013. "The demand for higher education: A static structural approach accounting for individual heterogeneity and nesting patterns," Economics of Education Review, Elsevier, vol. 34(C), pages 243-257.
    2. Jeffrey Perloff & Edward Shen, 2012. "Collinearity in Linear Structural Models of Market Power," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 40(2), pages 131-138, March.
    3. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    4. Paolo Coccorese, 2014. "Estimating the Lerner index for the banking industry: a stochastic frontier approach," Applied Financial Economics, Taylor & Francis Journals, vol. 24(2), pages 73-88, January.
    5. Heinesen, Eskil, 2018. "Admission to higher education programmes and student educational outcomes and earnings–Evidence from Denmark," Economics of Education Review, Elsevier, vol. 63(C), pages 1-19.
    6. Oppedisano, Veruska, 2014. "Higher education expansion and unskilled labour market outcomes," Economics of Education Review, Elsevier, vol. 40(C), pages 205-220.
    7. Rothschild, Michael & White, Lawrence J, 1995. "The Analytics of the Pricing of Higher Education and Other Services in Which the Customers Are Inputs," Journal of Political Economy, University of Chicago Press, vol. 103(3), pages 573-586, June.
    8. Oppedisano, Veruska, 2011. "The (adverse) effects of expanding higher education: Evidence from Italy," Economics of Education Review, Elsevier, vol. 30(5), pages 997-1008, October.
    9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    10. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    11. Zoghbi, Ana Carolina & Rocha, Fabiana & Mattos, Enlinson, 2013. "Education production efficiency: Evidence from Brazilian universities," Economic Modelling, Elsevier, vol. 31(C), pages 94-103.
    12. Façanha, Luís Otávio & Resende, Marcelo & Marinho, Alexandre, 1997. "Brazilian Federal Universities: Relative Efficiency Evaluation and Data Envelopment Analysis," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 51(4), October.
    13. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    14. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    15. Allen, Robert F. & Shen, Jianshou, 1999. "Some new evidence of the character of competition among higher education institutions," Economics of Education Review, Elsevier, vol. 18(4), pages 465-470, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    2. repec:use:tkiwps:3232 is not listed on IDEAS
    3. David Mayston, 2015. "Analysing the effectiveness of public service producers with endogenous resourcing," Journal of Productivity Analysis, Springer, vol. 44(1), pages 115-126, August.
    4. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    5. Luis R. Murillo-Zamorano & Juan Vega-Cervera, "undated". "The Use of Parametric and Non Parametric Frontier Methods to Measure the Productive Efficiency in the Industrial Sector. A Comparative Study," Discussion Papers 00/17, Department of Economics, University of York.
    6. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    7. Vangelis Tzouvelekas & Konstantinos Giannakas & Peter Midmore & Konstantinos Mattas, 1997. "Technical efficiency measures for olive-growing farms in Crete, Greece," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 3(2), pages 154-169, May.
    8. Pavlos Almanidis & Robin C. Sickles, 2016. "Banking Crises, Early Warning Models, and Efficiency," International Series in Operations Research & Management Science, in: Juan Aparicio & C. A. Knox Lovell & Jesus T. Pastor (ed.), Advances in Efficiency and Productivity, chapter 0, pages 331-364, Springer.
    9. Amer Ait Sidhoum & K Hervé Dakpo & Laure Latruffe, 2022. "Trade-offs between economic, environmental and social sustainability on farms using a latent class frontier efficiency model: Evidence for Spanish crop farms," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-17, January.
    10. Manlagnit, Maria Chelo V., 2015. "Basel regulations and banks’ efficiency: The case of the Philippines," Journal of Asian Economics, Elsevier, vol. 39(C), pages 72-85.
    11. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
    12. Williams, Jonathan & Nguyen, Nghia, 2005. "Financial liberalisation, crisis, and restructuring: A comparative study of bank performance and bank governance in South East Asia," Journal of Banking & Finance, Elsevier, vol. 29(8-9), pages 2119-2154, August.
    13. Méon, Pierre-Guillaume & Weill, Laurent, 2010. "Does financial intermediation matter for macroeconomic performance?," Economic Modelling, Elsevier, vol. 27(1), pages 296-303, January.
    14. Canay, Iván, 2002. "Eficiencia y Productividad en Distribuidoras Eléctricas: Repaso de la Metodología y Aplicación," UADE Textos de Discusión 35_2002, Instituto de Economía, Universidad Argentina de la Empresa.
    15. Carlos Pestana Barros & Julio del Corral & Pedro Garcia-del-Barrio, 2008. "Identification of Segments of Soccer Clubs in the Spanish League First Division With a Latent Class Model," Journal of Sports Economics, , vol. 9(5), pages 451-469, October.
    16. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    17. William Greene, 2003. "Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function," Journal of Productivity Analysis, Springer, vol. 19(2), pages 179-190, April.
    18. Léopold Simar & Paul W. Wilson, 2023. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1391-1403, October.
    19. García-Suárez, Federico & Pérez-Quesada, Gabriela & Molina, Carlos, 2022. "Rangeland cattle production in Uruguay: Single-output versus multi-output efficiency measures," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 22(01), June.
    20. Murillo-Zamorano, Luis R. & Vega-Cervera, Juan A., 2001. "The use of parametric and non-parametric frontier methods to measure the productive efficiency in the industrial sector: A comparative study," International Journal of Production Economics, Elsevier, vol. 69(3), pages 265-275, February.
    21. Althaler, Karl S. & Slavova, Tatjana, 2000. "DEA Problems under Geometrical or Probability Uncertainties of Sample Data," Economics Series 89, Institute for Advanced Studies.

    More about this item

    Keywords

    higher education market; market power; stochastic frontier;
    All these keywords.

    JEL classification:

    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_11370. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.