Productivity Measurement Of Commercial Banks In China And The Determinants Reasearch

With the full liberalization of the banking industry, the degree of financialliberalization accelerating, the relaxation of banking supervision and the entry offoreign banks, the financial environment of the domestic banking sector hasundergone tremendous changes and now the banking sector is facing more and morecompetitive pressures and financial risks. Therefore, the study of China’s bankingindustry since the full liberalization of the banking industry, to measure the efficiencyof the changes and to analyze the factors of affecting the efficiency is of great guidingsignificance to the reform and development of China’s banking industry in the nearfuture.This paper is based on the data of China’s commercial banks in2006-2011andthe use of model is based on the non-parametric DEA Malmquist productivity index.Commercial banks here have included four state-owned commercial banks, joint-stock commercial banks, city commercial banks. Fist of all, the author calculated thetotal factor productivity index. Then, the productivity index has been broken downinto technical efficiency index, the index of technological progress, pure technologicaladvances Index and scale efficiency index. Furthermore, the paper has analysed theefficiency change in the view of population，type of organization and the size ofscale. This part made a preliminary judgment on the impact of total factor.In the Chapter4, the author established a Panel Data model. The motive of thePanel Data model is testing the inherent impact facto of the productivity in China’scommercial banks.In this part, the total factor productivity is esteemed dependent variable and theconfiguration of the market share of the assets, the bank’s asset expense ratio and loanquality is esteemed independent variables. And then, the author established a panelmodel and made quantitative analysis of the factors that affect China’s commercialbanks total factor productivity. In the end, the author make conclusion and proposehow to enhance total factor productivity of China’s commercial banks. The maininnovation of this paper can be summarized as follows: Firstly, the paper measuredtotal factor productivity in China on the basis of the model of DEA Malmquistproductivity index, and then analyse the influencing factors of the total factorproductivity of China’s commercial banks. Secondly, the choice of sample data, the sample size in the time has been extended to2011and has enriched the size of thesample, expand the sample data, All of these make this paper a more comprehensivereflection of the total factor productivity of China’s commercial banks.