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Open AccessArticle

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

1
Department of Economics, Jinan University, Guangzhou 510632, China
2
School of Economics and Trade, Hunan University, Changsha 410079, China
3
Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(6), 1622; https://doi.org/10.3390/su11061622
Received: 19 December 2018 / Revised: 3 March 2019 / Accepted: 5 March 2019 / Published: 18 March 2019
This paper develops a new network data envelopment analysis (DEA) model that simultaneously integrates the non-convex metafrontier and undesirable outputs and which is super efficient at performing dynamic network slacks-based measures. The model is employed to discuss the efficiency of 36 commercial banks in China during the years 2010–2014. The efficiency of these banks shows significant heterogeneity and the efficiency of most foreign banks has much room for improvement. Regarding both the non-convex metafrontier and the group frontier, state-owned banks perform the best, followed by joint-stock banks, with foreign banks performing the worst; the same is true for the technology gap ratios. The empirical results produced by the feasible generalized least squares estimation method indicate that liquidity and scale effects exert positive impacts on bank efficiency. An alternative estimation method confirmed that the conclusions were robust. View Full-Text
Keywords: dynamic network slacks-based measure; non-convex metafrontier; super efficiency; bank efficiency; feasible generalized least squares dynamic network slacks-based measure; non-convex metafrontier; super efficiency; bank efficiency; feasible generalized least squares
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Yu, Y.; Huang, J.; Shao, Y. The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression. Sustainability 2019, 11, 1622.

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