Dealing with endogeneity in data envelopment analysis applications
作者：
Highlights：
• DEA has been widely applied to benchmark DMUs’ performance.
• We provide a simple heuristic procedure to identify the presence of endogeneity.
• We propose a potential tool for dealing with this issue and improving DEA estimates.
• The proposed II-DEA approach outperforms standard DEA in finite samples.
• An empirical application on the education sector illustrates theoretical findings.
摘要
•DEA has been widely applied to benchmark DMUs’ performance.•We provide a simple heuristic procedure to identify the presence of endogeneity.•We propose a potential tool for dealing with this issue and improving DEA estimates.•The proposed II-DEA approach outperforms standard DEA in finite samples.•An empirical application on the education sector illustrates theoretical findings.
论文关键词：Data envelopment analysis (DEA),Endogeneity,Simulation,Education
论文评审过程：Received 14 July 2016, Revised 12 September 2016, Accepted 1 October 2016, Available online 8 October 2016, Version of Record 24 October 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.002
