本文關(guān)鍵詞：信貸擴(kuò)張對(duì)我國(guó)商業(yè)銀行不良貸款率的影響分析　出處：《南京財(cái)經(jīng)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 信貸擴(kuò)張 不良貸款率 商業(yè)銀行 動(dòng)態(tài)面板模型

【摘要】：國(guó)際金融危機(jī)的爆發(fā)使我國(guó)經(jīng)濟(jì)開(kāi)始下滑,為了應(yīng)對(duì)金融危機(jī)、促使經(jīng)濟(jì)復(fù)蘇,我國(guó)采取了四萬(wàn)億投資計(jì)劃和寬松貨幣政策,同時(shí)也出現(xiàn)了新一輪信貸擴(kuò)張。大量信貸的投放固然有助于克服國(guó)際金融危機(jī)所帶來(lái)的沖擊,但是也必須看到信貸擴(kuò)張帶來(lái)的一些隱患,不良貸款的增加就是其中的一個(gè)表現(xiàn)。大量信貸和貨幣的投放使得國(guó)內(nèi)開(kāi)始出現(xiàn)通貨膨脹和資產(chǎn)價(jià)格泡沫,于是2011年政府又開(kāi)始進(jìn)行宏觀調(diào)控,銀行貸款增速也逐漸放緩。信貸增速的放緩將使得擴(kuò)張時(shí)期被掩蓋的不良貸款開(kāi)始暴露,銀行不良貸款開(kāi)始出現(xiàn)反彈。信貸擴(kuò)張與不良貸款的顯現(xiàn)之間存在一定的時(shí)滯,即兩者之間存在著滯后的正相關(guān)關(guān)系。本文的理論分析遵循由一般到特殊的原則。一方面從一般理論出發(fā),對(duì)信貸擴(kuò)張會(huì)導(dǎo)致未來(lái)不良貸款增加的原因進(jìn)行闡述,其原因主要有信貸標(biāo)準(zhǔn)下降、貸款管理不力、資產(chǎn)價(jià)格泡沫的破裂、制度記憶等等。另一方面聯(lián)系我國(guó)國(guó)情,結(jié)合我國(guó)近期信貸大幅增加的事實(shí),闡述了新一輪信貸擴(kuò)張影響我國(guó)商業(yè)銀行不良貸款的機(jī)理。新一輪信貸投放的主要方向在于地方政府融資平臺(tái)貸款、產(chǎn)能過(guò)剩行業(yè)貸款以及房地產(chǎn)貸款這三類貸款,分別對(duì)這三類貸款將會(huì)給銀行帶來(lái)的信貸風(fēng)險(xiǎn)進(jìn)行分析。根據(jù)前文的理論分析,在第四章的實(shí)證部分,本文以2003-2012年為研究區(qū)間,選取我國(guó)30家商業(yè)銀行作為樣本,采用GMM方法構(gòu)建動(dòng)態(tài)面板模型對(duì)信貸擴(kuò)張與不良貸款率之間的動(dòng)態(tài)關(guān)系進(jìn)行分析。在變量的選取方面,本文加入滯后二期至四期的貸款增長(zhǎng)率作為解釋變量,并選取了GDP實(shí)際增長(zhǎng)率、實(shí)際利率、通貨膨脹率、資產(chǎn)相對(duì)規(guī)模、凈資產(chǎn)收益率和股東權(quán)益比率作為控制變量。得出的結(jié)論為滯后二期的貸款增長(zhǎng)率系數(shù)為負(fù),滯后三、四期的貸款增長(zhǎng)率系數(shù)為正,且滯后四期的貸款增長(zhǎng)率系數(shù)較大,這表明信貸增長(zhǎng)的初始影響會(huì)降低不良貸款率,但是從長(zhǎng)期看,三至四年后不良貸款率將提高,并且在四年后上升的幅度會(huì)更大,從而會(huì)對(duì)整個(gè)銀行系統(tǒng)的穩(wěn)定性造成不利影響。在對(duì)“信貸擴(kuò)張對(duì)我國(guó)商業(yè)銀行不良貸款率的影響”這一問(wèn)題的理論分析和實(shí)證分析的基礎(chǔ)上,本文為銀行運(yùn)營(yíng)管理部門和監(jiān)管當(dāng)局提出了應(yīng)該如何降低信貸風(fēng)險(xiǎn)、減少不良貸款的參考性建議。商業(yè)銀行應(yīng)該嚴(yán)防重點(diǎn)領(lǐng)域風(fēng)險(xiǎn),妥善化解存量風(fēng)險(xiǎn)；調(diào)整信貸結(jié)構(gòu),著力促進(jìn)經(jīng)濟(jì)結(jié)構(gòu)調(diào)整；加強(qiáng)信貸管理,盡早發(fā)現(xiàn)問(wèn)題；同時(shí),監(jiān)管部門加強(qiáng)監(jiān)管,實(shí)現(xiàn)貸款平穩(wěn)增長(zhǎng)。這樣,我國(guó)銀行業(yè)的不良貸款水平能夠得以降低,信貸風(fēng)險(xiǎn)能得以有效控制。
[Abstract]:The outbreak of the international financial crisis has made our economy begin to decline. In order to deal with the financial crisis and promote economic recovery, China has adopted 4 tillion investment plan and loose monetary policy. At the same time, there is also a new round of credit expansion. A large number of credit lending will help to overcome the impact of the international financial crisis, but we must also see some hidden dangers brought by credit expansion. The increase in non-performing loans is one of the signs. A large amount of credit and money has caused inflation and asset price bubbles in the country, so in 2011 the government began to macro-control. Bank lending growth is also slowing. A slowdown in credit growth will expose non-performing loans that were masked during the expansion period. Bank non-performing loans began to rebound. There is a certain lag between the credit expansion and the appearance of non-performing loans. That is, there is a lag positive correlation between the two. The theoretical analysis of this paper follows the principle from general to special. On the one hand, it starts from general theory. The reasons why the expansion of credit will lead to the increase of non-performing loans in the future are explained. The main reasons are the decline of credit standards, the poor management of loans and the bursting of asset price bubbles. Institutional memory and so on. On the other hand, in connection with China's national conditions, combined with the recent increase in credit in China's facts. This paper expounds the mechanism that the new round of credit expansion affects the non-performing loans of commercial banks in our country. The main direction of the new round of credit investment lies in the local government financing platform loans. Overcapacity industry loans and real estate loans these three types of loans, the three types of loans will bring bank credit risk analysis. According to the previous theoretical analysis, in the 4th chapter of the empirical part. This article takes 2003-2012 as the research interval, selects 30 commercial banks in our country as the sample. Using GMM method to construct dynamic panel model to analyze the dynamic relationship between credit expansion and non-performing loan ratio. In this paper, the loan growth rate of the second to fourth period is added as the explanatory variable, and the real growth rate of GDP, the real interest rate, the inflation rate and the relative size of assets are selected. The return on net assets and the ratio of shareholders' equity are the controlling variables. The conclusion is that the coefficient of loan growth rate is negative in the second phase, and is positive in the third and fourth periods. The coefficient of loan growth rate is larger than that of four periods, which indicates that the initial impact of credit growth will reduce the ratio of non-performing loans, but in the long run, the ratio of non-performing loans will increase after three to four years. And in four years, the increase will be even greater. This will have a negative impact on the stability of the entire banking system. On the basis of the theoretical and empirical analysis of the problem of "the impact of credit expansion on the non-performing loan rate of commercial banks in China". This paper puts forward some suggestions on how to reduce the credit risk and reduce the non-performing loan for the bank operation management department and the supervisory authority. The commercial bank should strictly guard against the risk in the key area and resolve the stock risk properly. To adjust the credit structure and promote the adjustment of economic structure; Strengthen credit management and find out problems as soon as possible; At the same time, the supervision department strengthens the supervision, realizes the loan steady growth, thus our country's banking industry's bad loan level can reduce, the credit risk can be effectively controlled.
【學(xué)位授予單位】：南京財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F832.4

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