【摘要】：隨著經(jīng)濟(jì)高速發(fā)展時(shí)代的結(jié)束,中高速發(fā)展的“新常態(tài)”將成為今后很長時(shí)期內(nèi)中國經(jīng)濟(jì)發(fā)展的主基調(diào)。除此之外,全球經(jīng)濟(jì)持續(xù)低迷,復(fù)蘇之路異常崎嶇曲折。在國內(nèi)外這種大背景下,很多行業(yè)面臨著經(jīng)營困難、資金短缺的發(fā)展窘境。另外受銀行業(yè)全面對(duì)外放開,利率市場(chǎng)化快速推進(jìn),互聯(lián)網(wǎng)金融快速發(fā)展等因素的影響,中國銀行業(yè)受到了前所未有的沖擊。而銀行作為資金融通的中介,為經(jīng)濟(jì)發(fā)展提供充足的活力供應(yīng),其作用可以說是其他任何部門無法取代。因此,研究分析銀行效率情況不僅可以了解銀行運(yùn)營發(fā)展情況,還可以為未來發(fā)展指明方向。無論是盈利能力還是競(jìng)爭(zhēng)力,上市商業(yè)銀行在我國銀行業(yè)都很具有代表性,再加上其各項(xiàng)數(shù)據(jù)都易獲得,為此成為本文的研究對(duì)象。本文使用SBM方法及Malmquist生產(chǎn)指數(shù)法分別對(duì)不考慮、考慮不良貸款兩種情況下的16家上市商業(yè)銀行的效率進(jìn)行了對(duì)比研究分析,并使用Stata軟件在固定、隨機(jī)效應(yīng)的兩種假設(shè)下對(duì)影響因素進(jìn)行了Tobit面板數(shù)據(jù)回歸分析。在測(cè)度銀行效率及全要素生產(chǎn)率時(shí),本文采用固定資產(chǎn)投資價(jià)格指數(shù)(以2010年為基期)對(duì)投入指標(biāo)固定資產(chǎn)凈值進(jìn)行平減處理,利用GDP平減指數(shù)對(duì)其余投入產(chǎn)出指標(biāo)進(jìn)行了類似處理。在進(jìn)行Tobit回歸分析時(shí),選擇GDP增速、資產(chǎn)市場(chǎng)份額、資源配置能力、穩(wěn)定性、盈利能力、創(chuàng)新能力作為影響因子。經(jīng)過研究發(fā)現(xiàn),在不考慮與考慮不良貸款兩種情況下,均呈現(xiàn)出城市商業(yè)銀行效率最高,國有大型商業(yè)銀行效率次之,股份制商業(yè)銀行效率最低;股份制商業(yè)銀行全要素生產(chǎn)率最高,國有大型商業(yè)銀行全要素生產(chǎn)率次之,城市商業(yè)銀行全要素生產(chǎn)率在最低,且均呈放緩趨勢(shì);忽略不良貸款會(huì)使銀行效率值及全要素生產(chǎn)率值被低估;盈利能力、創(chuàng)新能力均會(huì)對(duì)銀行效率起到顯著的正向促進(jìn)作用,GDP增速均與銀行全要素生產(chǎn)率呈現(xiàn)顯著的正相關(guān)關(guān)系,穩(wěn)定性在不考慮不良貸款時(shí)與銀行全要素生產(chǎn)率呈正相關(guān)關(guān)系,創(chuàng)新能力在考慮不良貸款時(shí)與銀行全要素生產(chǎn)率呈正相關(guān)關(guān)系。根據(jù)研究成果,本文提出了對(duì)中國銀行業(yè)未來健康長遠(yuǎn)發(fā)展有益的建議。
[Abstract]:With the end of the era of rapid economic development, the "new normal" of China's rapid economic development will become the main tone of China's economic development for a long time to come. China's banking industry has been impacted unprecedentedly by factors such as the opening of banking industry to the outside world, the rapid advance of interest rate marketization and the rapid development of Internet finance. The analysis of bank efficiency can not only understand the development of bank operation, but also point out the direction for future development. Regardless of profitability or competitiveness, listed commercial banks are representative in China's banking industry, and their data are easy to obtain. Therefore, this paper uses the SBM method and Malmq. The efficiency of 16 listed commercial banks with non-performing loans and non-performing loans is compared and analyzed by the UIST production index method, and the influencing factors are analyzed by the Tobit panel data regression analysis using Stata software under two assumptions of fixed and random effects. In this paper, the fixed assets investment price index (based on 2010) is used to reduce the input index of the net fixed assets, and the GDP reduction index is used to deal with the other input-output indicators. It is found that the efficiency of city commercial banks is the highest, that of state-owned large commercial banks is the second, that of joint-stock commercial banks is the lowest, that of joint-stock commercial banks is the highest, and that of state-owned large commercial banks is the second. The total factor productivity of urban commercial banks is the lowest, and all show a slowing trend; neglecting non-performing loans will make the bank efficiency and total factor productivity value underestimated; profitability, innovation ability will play a significant positive role in promoting bank efficiency, GDP growth and total factor productivity of banks show a significant positive correlation, stable. There is a positive correlation between innovation capability and bank total factor productivity when non-performing loans are not taken into account, and there is a positive correlation between innovation capability and bank total factor productivity when non-performing loans are taken into account.
【學(xué)位授予單位】：聊城大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F832.33

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