A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China

Abstract

There are two typical subprocesses in bank production—deposit generation and loan generation. Aiming to open the black box of input-output production of banks and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM). Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples. Applying it to measure the efficiency of Chinese commercial banks from 2008 to 2012, this paper explores the characteristics of overall and divisional efficiency, as well as the determinants of them. Some interesting results are discovered. The polarization of efficiency occurs in the bank level and deposit generation, yet does not in the loan generation. Five hypotheses work as expected in the bank level, but not all of them are supported in the stage level. Our results extend and complement some earlier empirical publications in the bank level.

Integration of network data envelopment analysis and decision‐making trial and evaluation laboratory for the performance evaluation of the financial holding companies in Taiwan

“…They considered labor, fixed asset, and operating expense as inputs; deposit as intermediate input/output; and loan and securities investment as outputs. In addition, Huang, Chen, and Yin () used fixed assets, equity, and personnel expenses as inputs; deposits and short‐term funding and other raised funds as intermediates; and gross loan, other earning assets, and NPLs as outputs in evaluating banks in China. Ghroubi and Abaoub () measured cost and revenue efficiency of the Islamic and conventional Malaysian banks by using the stochastic frontier method and the meta‐frontier analysis over the period 2006–2012.…”

Incorporating Credit Quality in Bank Efficiency Measurements: A Directional Distance Function Approach

“…The study divided the overall efficiency into two sub-processes, i.e., deposit producing and profit earning. Huang et al (2014) examined the super efficiency of Chinese banks using a two-stage network model with bad outputs by extending the network slack-based measure model (NSBM) of Tone and Tsutsui (2009). The non-performing loans were modeled as a second-stage undesirable output.…”

Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model

“…Avkiran [16] illustrated dynamic network data envelopment analysis (DN-DEA) in commercial banking with emphasis on testing robustness. Huang et al [17] proposed a two-stage network model with bad outputs and supper efficiency (US-NSBM). Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples.…”