Bootstrap-based testing for network DEA: Some Theory and Applications

Kelly Trinh and Valentin Zelenyuk

No WP052015, CEPA Working Papers Series from University of Queensland, School of Economics

Abstract: Traditional data envelopment analysis (DEA) views a production technology process as a ‘black box’, while network DEA allows a researcher to look into the ‘black box’, to evaluate the overall performance and the performance of each sub-process of the system. The technical efficiency scores calculated from these approaches can be slightly, or sometimes vastly different. Our aim is to develop two bootstrap-based algorithms to test whether any observed difference between the results from the two approaches is statistically significant, or whether it is due to sampling and estimation noise. We focus on testing the equality of the first moment (i.e., the mean) and of the entire distribution of the technical efficiency scores. The bootstrap-based procedures can also be used for pairwise comparison between two network DEA models to perform sensitivity analysis of the resulting estimates across various network structures. In our empirical illustration of non-life insurance companies in Taiwan, both algorithms provide fairly robust results. We find statistical evidence suggesting that the first moment and the entire distribution of the overall technical efficiencies are significantly different between the DEA and network DEA models. However, the differences are not statistically significant for the two sub-processes across these models.

Keywords: DEA; Network DEA; Subsampling Bootstrap (search for similar items in EconPapers)
Date: 2015-05
New Economics Papers: this item is included in nep-cse, nep-ecm and nep-eff
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:qld:uqcepa:103

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