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The Total Factor Productivity Growth And Its Convergence Of China Banking

Posted on:2016-03-07Degree:MasterType:Thesis
Country:ChinaCandidate:X M GuanFull Text:PDF
GTID:2309330461452273Subject:Finance
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To fulfill the commitment towards WTO, the banking industry of China has brought the all-round opening into practice since 2006. From then on, the banking industry of China has stepped into the stage in which they competed with those of foreign countries completely. Nowadays, world economy is gradually getting out of the shadow caused by the financial crisis in 2008 and the banking industry of China starts emerging on the international economic performing stage. Therefore, taking a new look at its operating efficiency is becoming crucial. The following article makes 25 commercial banks to be the sample, which include 5 state-owned banks,10 joint-stock banks and 10 city commercial banks. By constructing the global Malmquis-luenberger Index, this paper tries to measure the growth of TFP which was under the constraint of the non-performing loans from 2008 to 2013 and to decompose the index.During the period from 2008 to 2013, the total factor productivity(TFP) of state-owned banks and joint-stock banks showed a upward trend while that of commercial banks of city showed a total opposite trend. Among it, the TFP of state-owned banks has increased by 0.06%, which is less than the joint-stock banks by 0.62%. In the meanwhile, that of city commercial banks decreased by 0.73%. Moreover, in terms of the decomposition factor of TFP, Efficiency Change posed a great influence to the rise of TFP. However, the change in technology or innovation made a slow advance at the same time. Though Efficiency Change in city commercial banks is obvious, their technology suffered a hold-back during the sample period due to limited capital and area, which led to the recession of TFP of city commercial banks. As a result, in order to increase TFP, not only should the production frontier be focused on, but also the importance of inside efficiency is supposed to be emphasized.In order to compare the GML Index to the traditional ML Index, this paper working out their differences with Wilconxon inspection found that the growth rate of TFP didn’t illustrate any significant differences through those two methods. In addition, this article also examined the GML Index, traditional ML Index and their decomposition factors---the transitivity of efficiency improvement and technological progress respectively. The result of showed that GML Index and its decomposition factor, GMLEC and GMLTC, satisfied the transitivity while only MLEC which lies in ML Index satisfied transitivity. Both ML Index itself and MLTC didn’t satisfy the transitivity. Therefore, although the GML index and ML index does not exist significant difference in efficiency measure, the transitivity of GML index makes it more attractive than ML index.Finally, the article also verifies the σ-convergence, the absolute β-convergence and relative β-convergence of the Chinese Commercial Banks’ TFP. Findings:(1) During the sample period, the TFP of Chinese Commercial Banks don’t indicate any σ-convergence phenomenon and the standard deviation of city commercial Banks’ TFP index is far greater than that of state-owned banks’ and joint-stock banks’, which means that the business differentiation of city commercial banks are much larger than state-owned banks and joint-stock banks. (2)There are an obvious β-convergence phenomenon and relative β-convergence phenomenon existing in the TFP of Chinese Commercial Banks. The non-performing loans have a negative impact on the growth of the banks’ TFP and the proportion which the non-interest income accounted for of the operation revenue leaves a positive influence on the growth of the banks’ TFP. Therefore, increasing the proportion which non-interest accounts for of the operation revenue and decreasing the rate of non-performing loans are of great significance to the growth of Chinese Commercial Banks’ TFP.
Keywords/Search Tags:Data envelopment analysis, Undesirable Output, Global Malmquist-L uenberger index, Total Factor Productivity
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