Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools |
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Authors: | Shae Brennan Carla Haelermans John Ruggiero |
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Institution: | 1. University of Dayton, United States;2. TIER, Maastricht University, The Netherlands;3. Delft University of Technology, The Netherlands |
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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. |
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Keywords: | Data Envelopment Analysis Malmquist productivity Education |
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