Abstract
In a non-market environment, there is no pressure coming from competitors that leads firms toward efficiency. Public education system is the target of many critiques as being such an example of inefficiency. Some papers attempted to measure the level of inefficiency of schools or school districts using different methods. Unfortunately, those methods do not include an important aspect of the school management that is characterized by the incapacity to adjust some inputs like buildings and equipment to their optimal level. In this paper, we use a generalization of Malmquist indexes that introduces this lack of flexibility in the measurement of productivity and we apply this method in the case of school districts in the Province of Québec (Canada).
Similar content being viewed by others
References
Asmild, M., & Tam, F. (2007). Estimating global frontier shifts and global Malmquist indices. Journal of Productivity Analysis, 27(2), 137–148.
Banker, R. D., & Morey, R. C. (1986). The use of categorical variable in data envelopment analysis. Management Science, 32(12), 1613–1627.
Burgess, J.F. Jr, & Wilson, P.W. (1995). Decomposing hospital productivity changes, 1985–1988: a nonparametric Malmquist approach. Journal of Productivity Analysis, 6(4), 343–363.
Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output and productivity. Econometrica, 50(6), 1393–1414.
Chakraborty, K., Biswas, B., & Lewis, W. C. (2001). Measurement of Technical Efficiency in Public Education: A Stochastic and Nonstochastic Production Function Approach. Southern Economic Journal, 67(4), 889–905.
Coates, D. C., & Lamdin, D. J. (2002). School performance evaluation using data envelopment analysis. Public Finance and Management, 2(4), 566–591.
Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1994). Productivity developments in Swedish hospitals: a Malmquist output index approach. In A. Charnes, W. Cooper, A. Y. Lewin, & L. M. Seiford (Eds.), Data envelopment analysis: theory, methodology and applications. Boston: Kluwer Academic.
Farrell, M. J. (1957). The measurement of production efficiency. Journal of the Royal Statistics Society, Series A, 120, 253–261.
Flegg, A. T., et al. (2004). Measuring the efficiency of British universities: a multi-period data envelopment analysis. Education Economics, 12(3), 231–249.
Gannon, B. (2008). Total factor productivity growth of hospitals in Ireland: a nonparametric approach. Applied Economics Letters, 15(1–3), 131–135.
Grifell-Tatjé, E., & Lovell, C. A. K. (1995). A note on the Malmquist productivity index. Economics Letters, 47, 169–175.
Grosskopf, S., & Moutray, C. (2001). Evaluating performance in Chicago public schools in the wake of decentralization. Economics of Education Review, 20(1), 1–14.
Kirjavainen, T., & Loikkanen, H. A. (1998). Efficiency differences of Finnish senior secondary schools: an application of DEA and Tobit analysis. Economics of Education Review, 17(4), 377–394.
Lambert, D. K. (1999). Scale and the Malmquist productivity index. Applied Economics Letters, 6, 593–596.
Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estatistica, 4, 209–242.
Nemoto, J., & Goto, M. (1999). Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies. Economics Letters, 64, 51–56.
Nemoto, J., & Goto, M. (2003). Measurement of dynamic efficiency in production: an application of data envelopment analysis to Japanese electric utilities. Journal of Productivity Analysis, 19, 191–210.
Ouellette, P., & Vierstraete, V. (2004). Technological change and efficiency in the presence of quasi-fixed inputs: a DEA application to the hospital sector. European Journal of Operational Research, 154(3), 755–763.
Ouellette, P., & Yan, L. (2008). Investment and dynamic DEA. Journal of Productivity Analysis, 29(3), 235–247.
Puig-Junoy, J. (1998). Technical efficiency in the clinical management of critically ill patients. Health Economics, 7(3), 263–277.
Rassouli-Currier, S. (2007). Assessing the efficiency of Oklahoma public schools: a data envelopment analysis. Southwestern Economic Review, 34(1), 131–144.
Ruggiero, J. (2004). Performance evaluation in education: modeling educational production. In W. W. Cooper, L. M. Seiford, & J. Zhu (Eds.), Handbook on data envelopment analysis. International series in operations research and management science (pp. 323–348). Boston, Dordrecht, London: Kluwer Academic.
Silva, E., & Stefanou, S. (2003). Nonparametric dynamic production analysis and the theory of cost. Journal of Productivity Analysis, 19, 5–32.
Silva, E., & Stefanou, S. (2007). Dynamic efficiency measurement: theory and application. American Journal of Agricultural Economics, 89, 398–419.
Solow, R. M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39, 312–320.
Steinmann, L., Dittrich, G., Karmann, A., & Zweifel, P. (2004). Measuring and comparing the (in)efficiency of German and Swiss hospitals. The European Journal of Health Economics, 5(3), 216–226.
Worthington, A. C., & Lee, B. L. (2008). Efficiency, technology and productivity change in Australian universities, 1998–2003. Economics of Education Review, 27(3), 285–298.
Zofio, J. (2007). Malmquist productivity index decompositions: a unifying framework. Applied Economics, 39(18), 2371–2387.
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Ouellette, P., Vierstraete, V. Malmquist indexes with quasi-fixed inputs: an application to school districts in Québec. Ann Oper Res 173, 57–76 (2010). https://doi.org/10.1007/s10479-008-0477-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-008-0477-0