Determinants of school efficiency

Determinants of school efficiency Purpose – The purpose of this paper is: to measure school technical efficiency and to identify the determinants of primary school performance. Design/methodology/approach – A two-stage data envelopment analysis (DEA) of school efficiency is conducted. At the first stage, DEA is employed to calculate an individual efficiency score for each school. At the second stage, efficiency is regressed on school characteristics and environmental variables. Findings – The mean technical efficiency of schools in the State of Geneva is equal to 93 per cent. By improving the operation of schools, 7 per cent (100−93) of inputs could be saved, representing 17,744,656 Swiss francs in 2010. School efficiency is negatively influenced by: operations being held on multiple sites, the proportion of disadvantaged pupils enroled at the school and the provision of special education, but positively influenced by school size (captured by the number of pupils). Practical implications – Technically, the determinants of school efficiency are outside of the control of headteachers. However, it is still possible to either boost the positive impact or curb the negative impact. In the context of the State of Geneva, the policy-related implications of the current study could be summarized as follows. New schools or existing multi-site schools should be concentrated on common sites; if this is not possible, the use of information and communication technology in school management and teaching should be developed and encouraged. In order to correct the negative influence of disadvantaged pupils on school performance, policymakers should focus on related social policies, such as pre-school, health, housing and benefits policies, rather than on allocating additional resources to schools. Finally, with an average of 381 pupils per school, school size could be increased to maximize school efficiency. Originality/value – Unlike most similar studies, the model in this study is tested for multicollinearity, heteroskedasticity and endogeneity. It is therefore robust. Moreover, one explanatory variable of school efficiency (operations being held on multiple sites) is a truly original variable as it has never been tested so far. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Educational Management Emerald Publishing

Determinants of school efficiency

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0951-354X
DOI
10.1108/IJEM-12-2013-0183
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is: to measure school technical efficiency and to identify the determinants of primary school performance. Design/methodology/approach – A two-stage data envelopment analysis (DEA) of school efficiency is conducted. At the first stage, DEA is employed to calculate an individual efficiency score for each school. At the second stage, efficiency is regressed on school characteristics and environmental variables. Findings – The mean technical efficiency of schools in the State of Geneva is equal to 93 per cent. By improving the operation of schools, 7 per cent (100−93) of inputs could be saved, representing 17,744,656 Swiss francs in 2010. School efficiency is negatively influenced by: operations being held on multiple sites, the proportion of disadvantaged pupils enroled at the school and the provision of special education, but positively influenced by school size (captured by the number of pupils). Practical implications – Technically, the determinants of school efficiency are outside of the control of headteachers. However, it is still possible to either boost the positive impact or curb the negative impact. In the context of the State of Geneva, the policy-related implications of the current study could be summarized as follows. New schools or existing multi-site schools should be concentrated on common sites; if this is not possible, the use of information and communication technology in school management and teaching should be developed and encouraged. In order to correct the negative influence of disadvantaged pupils on school performance, policymakers should focus on related social policies, such as pre-school, health, housing and benefits policies, rather than on allocating additional resources to schools. Finally, with an average of 381 pupils per school, school size could be increased to maximize school efficiency. Originality/value – Unlike most similar studies, the model in this study is tested for multicollinearity, heteroskedasticity and endogeneity. It is therefore robust. Moreover, one explanatory variable of school efficiency (operations being held on multiple sites) is a truly original variable as it has never been tested so far.

Journal

International Journal of Educational ManagementEmerald Publishing

Published: Jun 8, 2015

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