Abstract
The aim of this paper is to provide an alternative approach for estimating efficiency when a set of decision-making units uses non-discretionary inputs in the productive process. To test the influence of these variables, our proposal uses a multi-stage approach based on Tobit regressions. In order to avoid potential bias, a bootstrap procedure is used to estimate these regressions. This methodology allows enhancing other models previously proposed to introduce non-controllable inputs in data envelopment analysis (DEA) overcoming, thus, some of their main shortcomings. We illustrate our framework with an empirical application on Spanish high schools where non-controllable factors play a major role to explain educational achievements.
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Acknowledgements
We are grateful to participants at the IV North American Productivity Workshop and to an anonymous referee for helpful comments. This research was supported by the Spanish Government, Ministry of Education and Science, Project MEC/SEJ 2004-080J1/ECON.
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Cordero-Ferrera, J., Pedraja-Chaparro, F. & Santín-González, D. Enhancing the inclusion of non-discretionary inputs in DEA. J Oper Res Soc 61, 574–584 (2010). https://doi.org/10.1057/jors.2008.189
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DOI: https://doi.org/10.1057/jors.2008.189