Unveiling endogeneity between competition and efficiency in Chinese banks: a two-stage network DEA and regression analysis

Aaron Tan, Peter Wanke, Jorge Antunes, Ali Emrouznejad

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

Although there is a growing number of research articles investigating the performance in the banking industry, research on Chinese banking efficiency is rather focused on discussing rankings to the detriment of unveiling its productive structure in light of banking competition. This issue is of utmost importance considering the relevant transformations in the Chinese economy over the last decades. This is a development of a two-stage network production process (production and intermediation approaches in banking, respectively) to evaluate the efficiency level of Chinese commercial banks. In the second stage regression analysis, an integrated Multi-Layer Perceptron/Hidden Markov model is used for the first time to unveil endogeneity among banking competition, contextual variables, and efficiency levels of the production and intermediation approaches in banking. The competitive condition in the Chinese banking industry is measured by Panar-Rosse H-statistic and Lerner index under the Ordinary Least Square regression. Findings reveal that productive efficiency appears to be positively impacted by competition and market power. Second, credit risk analysis in older local banks, which focus the province level, would possibly be the fact that jeopardizes the productive efficiency levels of the entire banking industry in China. Thirdly, it is found that a perfect banking competition structure at the province level and a reduced market power of local banks are drivers of a sound banking system. Finally, our findings suggest that concentration of credit in a few banks leads to an increase in bank productivity.
Original languageEnglish
Pages (from-to)131-171
Number of pages41
JournalAnnals of Operations Research
Volume306
Issue number1-2
Early online date29 May 2021
DOIs
Publication statusPublished - 1 Nov 2021

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