發(fā)布時(shí)間：2018-06-21 06:27

  本文選題：房地產(chǎn)價(jià)格 + 銀行信貸��； 參考：《長(zhǎng)沙理工大學(xué)》2016年碩士論文

【摘要】：目前,我國(guó)經(jīng)濟(jì)形勢(shì)面臨著下行的壓力,由過(guò)去的資本與商品存在雙短缺過(guò)渡到商品與資本的雙過(guò)剩。如何化解過(guò)剩產(chǎn)能已經(jīng)成為我國(guó)房地產(chǎn)業(yè)的熱門(mén)議題,“去庫(kù)存”也被列上了日事議程。2015年,我國(guó)政府放松對(duì)房地產(chǎn)的信貸政策,首套房公積金貸款最低首付降到20%,首套房已結(jié)清房貸的,再次購(gòu)買(mǎi)申請(qǐng)公積金貸款降低至30%等,以此來(lái)緩解經(jīng)濟(jì)發(fā)展下行的壓力并促進(jìn)中國(guó)房地產(chǎn)市場(chǎng)健康、持續(xù)、穩(wěn)定、有序的發(fā)展。在此背景下,本文研究我國(guó)銀行信貸對(duì)房地產(chǎn)價(jià)格波動(dòng)的影響,從我國(guó)一二線(xiàn)城市的視角進(jìn)行分析就很具備學(xué)術(shù)價(jià)值和現(xiàn)實(shí)社會(huì)價(jià)值。文章將銀行信貸與房地產(chǎn)價(jià)格為研究對(duì)象,分別探討一線(xiàn)城市與二線(xiàn)城市的銀行信貸與房地產(chǎn)價(jià)格波動(dòng)的影響及其影響程度。首先,從理論知識(shí)和建模中分析銀行信貸與房地產(chǎn)價(jià)格的傳導(dǎo)效應(yīng)。然后,在實(shí)證分析部分,選取我國(guó)商品房平均銷(xiāo)售價(jià)格作為被解釋變量來(lái)衡量房地產(chǎn)價(jià)格,選取金融機(jī)構(gòu)人民幣各項(xiàng)貸款作為解釋變量來(lái)表示銀行信貸。在進(jìn)行分析處理過(guò)程中,還曾選取國(guó)內(nèi)生產(chǎn)總值GDP、物價(jià)消費(fèi)指數(shù)CPI以及貸款利率LI作為解釋變量,最終得出以上三個(gè)解釋變量對(duì)被解釋變量的實(shí)證結(jié)果不顯著,故將其剔除出模型中。本文是在剔除通貨膨脹因素的情況下,使用我國(guó)35個(gè)一二線(xiàn)城市1999-2013年的銀行信貸與房地產(chǎn)價(jià)格的年度數(shù)據(jù),建立不變系數(shù)模型,并利用Granger因果檢驗(yàn)方法對(duì)二者之間關(guān)系進(jìn)行實(shí)證檢驗(yàn)。得出結(jié)論,銀行信貸與房地產(chǎn)價(jià)格存在單向因果關(guān)系。一線(xiàn)城市的房地產(chǎn)價(jià)格對(duì)銀行信貸存在單向引導(dǎo);二線(xiàn)城市的銀行信貸對(duì)房地產(chǎn)價(jià)格的單向引導(dǎo)。后者的房地產(chǎn)價(jià)格波動(dòng)受到銀行信貸影響程度比前者所受影響更大�；诖�,為了更好地控制中國(guó)房地產(chǎn)市場(chǎng)的價(jià)格,政府相關(guān)部門(mén)可以對(duì)我國(guó)不同城市采取差別化信貸政策。對(duì)一線(xiàn)城市采取信貸政策與其他宏觀經(jīng)濟(jì)政策配套使用,根據(jù)經(jīng)濟(jì)增長(zhǎng)水平合理確定本地區(qū)的新建住房數(shù)量目標(biāo),嚴(yán)格住房用地供應(yīng)管理以及有效引導(dǎo)消費(fèi)者的住房需求。對(duì)二線(xiàn)城市重點(diǎn)實(shí)施合理有效的信貸政策,輔之相應(yīng)的金融政策共同控制房地產(chǎn)價(jià)格在合理區(qū)間內(nèi)變動(dòng)。
[Abstract]:At present, the economic situation of our country is facing downward pressure, from double shortage of capital and commodity in the past to double surplus of commodity and capital. How to resolve excess production capacity has become a hot topic in China's real estate industry, and "going to inventory" has also been put on the agenda of Japan. In 2015, our government relaxed its credit policy on real estate. The minimum down payment for the first housing provident fund loan has dropped to 20. If the first house has settled its housing loan, the purchase and application for a provident fund loan will be reduced to 30%, so as to ease the downward pressure on economic development and promote the health, sustainability and stability of China's real estate market. An orderly development. Under this background, this paper studies the influence of bank credit on the real estate price fluctuation in China. It has academic value and realistic social value from the perspective of the first and second tier cities in China. Taking bank credit and real estate price as the research object, this paper discusses the influence of bank credit and real estate price fluctuation in first-tier city and second-tier city respectively and their influence degree. Firstly, the paper analyzes the conduction effect of bank credit and real estate price from theoretical knowledge and modeling. Then, in the empirical analysis part, the average selling price of commercial housing in China is chosen as the explained variable to measure the real estate price, and the RMB loans of financial institutions are selected as the explanatory variables to represent bank credit. In the process of analysis and processing, we also selected GDP, CPI and Li as explanatory variables. Finally, the empirical results of the above three explanatory variables on the explained variables are not significant. Therefore, it is removed from the model. Based on the annual data of bank credit and real estate prices from 1999 to 2013 in 35 first and second tier cities in China, this paper establishes a constant coefficient model. And Granger causality test method is used to test the relationship between the two. The conclusion is that bank credit and real estate prices have a one-way causal relationship. Real estate prices in first-tier cities have one-way guidance to bank credit, while bank credit in second-tier cities has one-way guidance on real estate prices. The latter's real estate price volatility is more affected by bank credit than the former. Based on this, in order to better control the prices of China's real estate market, the relevant government departments can adopt differential credit policy for different cities in China. Credit policy and other macroeconomic policies should be adopted in first-tier cities. According to the level of economic growth, the target of new housing quantity in this area should be reasonably determined, the supply of housing land should be strictly managed and the housing demand of consumers should be effectively guided. Second-tier cities focus on the implementation of reasonable and effective credit policy, supplemented by the corresponding financial policies to control the real estate prices in a reasonable range of changes.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：F299.23;F832.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 沈悅;戴士偉;陳錕;;房?jī)r(jià)過(guò)度波動(dòng)的系統(tǒng)性風(fēng)險(xiǎn)溢出效應(yīng)測(cè)度——基于GARCH-Copula-CoVaR模型[J];中央財(cái)經(jīng)大學(xué)學(xué)報(bào);2016年03期

2 袁東;何秋谷;趙波;;房?jī)r(jià)變動(dòng)的影響因素研究:一個(gè)文獻(xiàn)綜述[J];經(jīng)濟(jì)與管理研究;2016年03期

3 黃燕芬;張磊;;2016年中國(guó)房地產(chǎn)業(yè)主基調(diào):去庫(kù)存、穩(wěn)市場(chǎng)[J];價(jià)格理論與實(shí)踐;2015年12期

4 何青;錢(qián)宗鑫;郭俊杰;;房地產(chǎn)驅(qū)動(dòng)了中國(guó)經(jīng)濟(jì)周期嗎?[J];經(jīng)濟(jì)研究;2015年12期

5 辛兵海;張曉云;陶江;;異質(zhì)性條件、資產(chǎn)價(jià)格和銀行信貸[J];國(guó)際金融研究;2015年09期

6 鄭忠華;張瑜;;房地產(chǎn)市場(chǎng)、銀行體系與中國(guó)宏觀經(jīng)濟(jì)波動(dòng)——基于多部門(mén)動(dòng)態(tài)隨機(jī)一般均衡模型的分析[J];南方經(jīng)濟(jì);2015年02期

7 王拉娣;安勇;王佳;;房?jī)r(jià)波動(dòng)與銀行信貸風(fēng)險(xiǎn)的動(dòng)態(tài)相關(guān)關(guān)系研究[J];經(jīng)濟(jì)問(wèn)題;2014年12期

8 黃梓蔚;潘海英;;銀行信貸規(guī)模與房地產(chǎn)價(jià)格波動(dòng)關(guān)系研究[J];價(jià)格理論與實(shí)踐;2014年11期

9 沈悅;徐妍;鄭冠群;;基于銀行風(fēng)險(xiǎn)承擔(dān)視角的房地產(chǎn)信貸政策調(diào)控效果研究[J];金融經(jīng)濟(jì)學(xué)研究;2014年04期

10 沈悅;郭培利;;經(jīng)濟(jì)增長(zhǎng)、銀行信貸與住宅價(jià)格波動(dòng)——基于35個(gè)大中城市異質(zhì)面板的實(shí)證分析[J];軟科學(xué);2014年07期

相關(guān)博士學(xué)位論文 前3條

1 孟彩云;中國(guó)房地產(chǎn)價(jià)格對(duì)產(chǎn)出和消費(fèi)物價(jià)的影響[D];暨南大學(xué);2012年

2 薩秋榮;房地產(chǎn)價(jià)格波動(dòng)與銀行信貸關(guān)系研究[D];南開(kāi)大學(xué);2011年

3 周京奎;金融支持過(guò)度與房地產(chǎn)泡沫研究[D];南開(kāi)大學(xué);2004年

，

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