IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v234y2014i3p809-818.html
   My bibliography  Save this article

Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools

Author

Listed:
  • Brennan, Shae
  • Haelermans, Carla
  • Ruggiero, John

Abstract

In this paper we develop a Malmquist productivity index for public sector production characterized by the influence of environmental variables. We extend Johnson and Ruggiero (2011) to the more general case of variable returns to scale to further decompose the Malmquist productivity index into technical, efficiency, scale and environmental change. We apply our model to analyze productivity of Dutch schools using 2002–2007 data. The results indicate that the environment influences the productivity index as well as the technical, efficiency, scale and environmental change components. We see that schools with a moderate classification of environment have the highest productivity numbers. In line with expectations, schools with the worst environment also perform worse and would perform better with an improved environment.

Suggested Citation

  • Brennan, Shae & Haelermans, Carla & Ruggiero, John, 2014. "Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools," European Journal of Operational Research, Elsevier, vol. 234(3), pages 809-818.
    • Handle: RePEc:eee:ejores:v:234:y:2014:i:3:p:809-818
    DOI: 10.1016/j.ejor.2013.10.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221713008539
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    2. John Ruggiero, 2007. "Measuring the Cost of Meeting Minimum Educational Standards: An Application of Data Envelopment Analysis," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 1-13.
    3. Fare, Rolf & Grosskopf, Shawna, 1985. " Nonparametric Cost Approach to Scale Efficiency," Scandinavian Journal of Economics, Wiley Blackwell, vol. 87(4), pages 594-604.
    4. Kirjavainen, Tanja & Loikkanent, Heikki A., 1998. "Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis," Economics of Education Review, Elsevier, vol. 17(4), pages 377-394, October.
    5. De Witte, Kristof & Rogge, Nicky & Cherchye, Laurens & Van Puyenbroeck, Tom, 2013. "Economies of scope in research and teaching: A non-parametric investigation," Omega, Elsevier, vol. 41(2), pages 305-314.
    6. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    7. Shawna Grosskopf & Kathy J. Hayes & Lori L. Taylor, 2009. "The Relative Efficiency Of Charter Schools," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 80(1), pages 67-87, March.
    8. Mike Smet & Walter Nonneman, 1998. "Economies of scale and scope in Flemish secondary schools," Applied Economics, Taylor & Francis Journals, vol. 30(9), pages 1251-1258.
    9. 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.
    10. Maria Alberta Oliveira & Carlos Santos, 2005. "Assessing school efficiency in Portugal using FDH and bootstrapping," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 957-968.
    11. Afonso, Antonio & St. Aubyn, Miguel, 2006. "Cross-country efficiency of secondary education provision: A semi-parametric analysis with non-discretionary inputs," Economic Modelling, Elsevier, vol. 23(3), pages 476-491, May.
    12. Eric A. Hanushek, 1979. "Conceptual and Empirical Issues in the Estimation of Educational Production Functions," Journal of Human Resources, University of Wisconsin Press, vol. 14(3), pages 351-388.
    13. Pierre Ouellette & Valérie Vierstraete, 2010. "Malmquist indexes with quasi-fixed inputs: an application to school districts in Québec," Annals of Operations Research, Springer, vol. 173(1), pages 57-76, January.
    14. Christopher J. O'Donnell, 2012. "Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 873-890.
    15. Ruggiero, John, 1996. "Efficiency of Educational Production: An Analysis of New York School Districts," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 499-509, August.
    16. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    17. Pierre Ouellette & Valerie Vierstraete, 2005. "An evaluation of the efficiency of Quebec's school boards using the Data Envelopment Analysis method," Applied Economics, Taylor & Francis Journals, vol. 37(14), pages 1643-1653.
    18. Hédi Essid & Pierre Ouellette & Stéphane Vigeant, 2013. "Small is not that beautiful after all: measuring the scale efficiency of Tunisian high schools using a DEA-bootstrap method," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1109-1120, March.
    19. Haelermans, Carla & De Witte, Kristof & Blank, Jos L.T., 2012. "On the allocation of resources for secondary schools," Economics of Education Review, Elsevier, vol. 31(5), pages 575-586.
    20. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    21. Caroline M. Hoxby, 2004. "Productivity in Education: The Quintessential Upstream Industry," Southern Economic Journal, Southern Economic Association, vol. 71(2), pages 209-231, October.
    22. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    23. M-J Mancebón & J Calero & Á Choi & D P Ximénez-de-Embún, 2012. "The efficiency of public and publicly subsidized high schools in Spain: Evidence from PISA-2006," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(11), pages 1516-1533, November.
    24. Shawna Grosskopf & Kathy J. Hayes & Lori L. Taylor & William L. Weber, 1997. "Budget-Constrained Frontier Measures Of Fiscal Equality And Efficiency In Schooling," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 116-124, February.
    25. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    26. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-1177, September.
    27. Haelermans, Carla & Ruggiero, John, 2013. "Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools," European Journal of Operational Research, Elsevier, vol. 227(1), pages 174-181.
    28. Othman Joumady & Catherine Ris, 2005. "Performance in European higher education: A non-parametric production frontier approach," Education Economics, Taylor & Francis Journals, vol. 13(2), pages 189-205.
    29. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    30. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2013. "Dynamics of productivity in higher education: cross-european evidence based on bootstrapped Malmquist indices," Journal of Productivity Analysis, Springer, vol. 40(1), pages 67-82, August.
    31. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    32. Gerhard Kempkes, 2008. "Do Institutions Matter for University Cost Efficiency? Evidence from Germany," CESifo Economic Studies, CESifo, vol. 54(2), pages 177-203, June.
    33. Millimet, Daniel L. & Collier, Trevor, 2008. "Efficiency in public schools: Does competition matter?," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 134-157, July.
    34. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    35. K. Chakraborty & B. Biswas & WC. Lewis, 2000. "Economies of scale in public education: an econometric analysis," Contemporary Economic Policy, Western Economic Association International, vol. 18(2), pages 238-247, April.
    36. Rajiv D. Banker & Richard C. Morey, 1986. "The Use of Categorical Variables in Data Envelopment Analysis," Management Science, INFORMS, vol. 32(12), pages 1613-1627, December.
    37. Conroy, Stephen J. & Arguea, Nestor M., 2008. "An estimation of technical efficiency for Florida public elementary schools," Economics of Education Review, Elsevier, vol. 27(6), pages 655-663, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Barra, Cristian & Lagravinese, Raffaele & Zotti, Roberto, 2015. "Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities," MPRA Paper 67119, University Library of Munich, Germany.
    2. 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.
    3. Victor V. Podinovski & Wan Rohaida Wan Husain, 2017. "The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia," Annals of Operations Research, Springer, vol. 250(1), pages 65-84, March.
    4. Feyyaz Cengiz Dikmen, 2016. "Productivity Change: An Empirical Study on Turkish State Universities," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(1), pages 27-34, June.
    5. José Manuel Cordero & Daniel Santín & Rosa Simancas, 2017. "Assessing European primary school performance through a conditional nonparametric model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 364-376, April.
    6. Aparicio, Juan & Crespo-Cebada, Eva & Pedraja-Chaparro, Francisco & Santín, Daniel, 2017. "Comparing school ownership performance using a pseudo-panel database: A Malmquist-type index approach," European Journal of Operational Research, Elsevier, vol. 256(2), pages 533-542.
    7. Kao, Chiang & Liu, Shiang-Tai, 2016. "A parallel production frontiers approach for intertemporal efficiency analysis: The case of Taiwanese commercial banks," European Journal of Operational Research, Elsevier, vol. 255(2), pages 411-421.
    8. López-Torres, Laura & Nicolini, Rosella & Prior, Diego, 2017. "Does strategic interaction affect demand for school places? A conditional efficiency approach," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 89-103.
    9. Kristof de Witte & Laura López-Torres, 2015. "Efficiency in Education. A Review of Literature and a Way Forward," Working Papers 1501, Departament Empresa, Universitat Autònoma de Barcelona, revised Apr 2015.
    10. Aparicio, Juan & López-Torres, Laura & Santín, Daniel, 2018. "Economic crisis and public education. A productivity analysis using a Hicks-Moorsteen index," Economic Modelling, Elsevier, vol. 71(C), pages 34-44.
    11. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2018. "Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model," Journal of Informetrics, Elsevier, vol. 12(1), pages 10-30.
    12. Manh D. Pham & Léopold Simar & Valentin Zelenyuk, 2019. "Statistical Inference for Aggregation of Malmquist Productivity Indices," CEPA Working Papers Series WP082019, School of Economics, University of Queensland, Australia.
    13. Thanassoulis, Emmanuel & Shiraz, Rashed Khanjani & Maniadakis, Nikolaos, 2015. "A cost Malmquist productivity index capturing group performance," European Journal of Operational Research, Elsevier, vol. 241(3), pages 796-805.
    14. Carla Haelermans & John Ruggiero, 2017. "Non-parametric estimation of the cost of adequacy in education: the case of Dutch schools," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 390-398, April.

    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:eee:ejores:v:234:y:2014:i:3:p:809-818. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eor .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.