Abstract
The performances of different types of banks may vary due to heterogeneous technology, which can be examined by metafrontier analysis. However, the metafrontier constructed in most existing literature is concave, resulting in a biased estimation of efficiency. Based on 93 Chinese commercial banks over the period of 2005–2016, we first evaluate the banking efficiency by using the proposed data envelopment analysis (DEA) model, NCMeta-US-NSBM, which simultaneously incorporates a non-concave metafrontier technique, undesirable outputs, and super efficiency into a network slacks-based measure (NSBM) model. Subsequently, the evolution of banking efficiency during the study period is investigated on the basis of the Dagum Gini index and kernel density estimation methods. The main empirical results show the following. 1) There exists significant disparity/heterogeneity in banking efficiency for overall efficiency, productivity efficiency, and profitability efficiency. 2) The results of the technology gap ratio (TGR) and the evaluation of stated-owned banks (SOB), joint-stock banks (JSB), and city commercial banks (CCB) in the productivity stage are higher than those in the profitability stage, indicating that most of the banks have a large space for improvement, especially for SOB and JSB in the profitability stage. 3) The major contribution of the overall difference of banking efficiency in China is the intensity of the transvariation. 4) Although the kernel density estimations for different efficiency scores have similar distributions in corresponding years, the multilevel differentiation phenomenon of banking efficiency may appear after 2008.
Highlights
The improvement of the performance of commercial banks is of great significance for the rational use of financial resources and the enhancement of the comprehensive competitiveness of China’s banking industry
Based on the need to include the abovementioned issues in the data envelopment analysis (DEA) analytical framework, we propose an innovative measurement approach that incorporates a non-concave metafrontier and undesirable outputs into a slack-based network DEA model (NCMeta-US-NSBM), providing more accurate results and evidence when banking efficiency is estimated
We mainly focus on the proposed model NCMeta-US-NSBM, which simultaneously incorporates the non-concave metafrontier technique, super efficiency, and undesirable outputs into the network slack-based measure model
Summary
The improvement of the performance of commercial banks is of great significance for the rational use of financial resources and the enhancement of the comprehensive competitiveness of China’s banking industry. The metafrontier is estimated by enveloping the group-specific frontiers [29, 56, 57] In their latest work, Chiu et al [57] developed a new model to decompose the source of metafrontier inefficiency for various banks based on a two-stage network system with undesirable outputs. Chiu et al [57] developed a new model to decompose the source of metafrontier inefficiency for various banks based on a two-stage network system with undesirable outputs Their empirical results suggest that foreign banks are less efficient in developed countries, indicating that there are technology gaps among different types of commercial banks. Based on the need to include the abovementioned issues in the DEA analytical framework, we propose an innovative measurement approach that incorporates a non-concave metafrontier and undesirable outputs into a slack-based network DEA model (NCMeta-US-NSBM), providing more accurate results and evidence when banking efficiency is estimated. The strength of the NCMeta-US-NSBM (compared to traditional DEA models) is its comparability treatment of efficiency of the same DMUs in different years due to possible unobserved exogenous technical changes and the ranks of the efficient DMUs on the efficient frontier
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