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School cost functions: A meta-regression analysis

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  • Colegrave, Andrew D.
  • Giles, Margaret J.

Abstract

The education cost literature includes econometric studies attempting to determine economies of scale, or estimate an optimal school or district size. Not only do their results differ, but the studies use dissimilar data, techniques, and models. To derive value from these studies requires that the estimates be made comparable. One method to do this is meta-regression analysis (MRA) which was pioneered by Stanley and Jarrell [(1998). Gender wage discrimination bias? An MRA. Journal of Human Resources, 33, 947-973] as a result of similar frustrations with 'omnipresent biases' (p. 717). In this paper, the basic technique of MRA is described and then applied to 22 estimates of school costs, where an optimal school size (OSS) has or can be calculated. Results suggest an OSS of around 1543 students at the US secondary school level. Difficulties in interpreting the estimates are highlighted. The paper concludes with cautions in the use of MRA and opportunities for further research in this area.

Suggested Citation

  • Colegrave, Andrew D. & Giles, Margaret J., 2008. "School cost functions: A meta-regression analysis," Economics of Education Review, Elsevier, vol. 27(6), pages 688-696, December.
    • Handle: RePEc:eee:ecoedu:v:27:y:2008:i:6:p:688-696
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    1. Tirivayi, J.N. & Maasen van den Brink, H. & Groot, W.N.J., 2014. "Size and economies of scale in higher education and the implications for mergers," MERIT Working Papers 2014-066, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    2. Mora Rodríguez, Jhon James & Muro, Juan, 2015. "On the size of sheepskin effects: A meta-analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-18.
    3. Rhys Andrews, 2013. "Local government size and efficiency in labor-intensive public services: evidence from local educational authorities in England," Chapters, in: Santiago Lago-Peñas & Jorge Martinez-Vazquez (ed.), The Challenge of Local Government Size, chapter 7, pages 171-188, Edward Elgar Publishing.
    4. Liang-Cheng Zhang & Andrew C. Worthington, 2018. "Explaining Estimated Economies of Scale and Scope in Higher Education: A Meta-Regression Analysis," Research in Higher Education, Springer;Association for Institutional Research, vol. 59(2), pages 156-173, March.
    5. Jos L. T. Blank & Thomas K. Niaounakis, 2019. "Managing Size of Public Schools and School Boards: A Multi-Level Cost Approach Applied to Dutch Primary Education," Sustainability, MDPI, vol. 11(23), pages 1-11, November.
    6. Carlos Renato De Melo Castro & Geraldo Da Silva E Souza & Maria Eduarda Tannuri-Pianto, 2016. "Gastos Em Educação: Mais Recursos Sem Gestão?," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 072, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. H餩 Essid & Pierre Ouellette & St鰨ane 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.
    8. Stiefel, Leanna & Schwartz, Amy Ellen & Iatarola, Patrice & Chellman, Colin C., 2009. "Mission matters: The cost of small high schools revisited," Economics of Education Review, Elsevier, vol. 28(5), pages 585-599, October.
    9. Giambona, Francesca & Porcu, Mariano, 2018. "School size and students' achievement. Empirical evidences from PISA survey data," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 66-77.
    10. Rhys Andrews, 2012. "Local Government Size and Efficiency in Labour Intensive Public Services: Evidence from Local Educational Authorities in England," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1214, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
    11. Rebai, Sonia & Ben Yahia, Fatma & Essid, Hédi, 2020. "A graphically based machine learning approach to predict secondary schools performance in Tunisia," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    12. Zuzana Iršová & Tomáš Havránek, 2010. "Measuring Bank Efficiency: A Meta-Regression Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2010(4), pages 307-328.

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