發(fā)布時間：2018-04-24 07:01

  本文選題：房價波動 + 空間效應(yīng)��； 參考：《暨南大學(xué)》2013年碩士論文

【摘要】：為探討我國房地產(chǎn)市場波動的規(guī)律性，本文在國內(nèi)首次利用截面相關(guān)的CCE估計法，分析房價與人均可支配收入、貸款余額間是否存在長期協(xié)整關(guān)系；若存在，則對殘差序列建立空間滯后模型，并通過最大似然估計法得出空間相關(guān)系數(shù)，以此判斷房價波動空間效應(yīng)的存在及其大小。結(jié)果表明：我國房價波動存在顯著的空間溢出效應(yīng)，不同城市間的房價波動具有較強的趨同性，但同時房價的波動又存在一定的差異性。經(jīng)濟越發(fā)達(dá)的城市，不僅房價高、增長快，而且房價運行的獨立性越強；而經(jīng)濟落后的城市，其房價容易受到外部地區(qū)房價的影響。 同時，，文中運用GARCH模型研究房價等基本面因素對銀行不良貸款率的影響，以此間接分析房價波動與金融穩(wěn)定間的關(guān)系。估計結(jié)果表明：當(dāng)模型中包含國內(nèi)生產(chǎn)總值時，國內(nèi)生產(chǎn)總值的估計系數(shù)最大，其次為廣義貨幣供應(yīng)量，最后是房地產(chǎn)價格；而當(dāng)模型中不包含國內(nèi)生產(chǎn)總值時，房地產(chǎn)價格指數(shù)與廣義貨幣供給量系數(shù)均顯著增大，且系數(shù)符號與實際經(jīng)濟情況相符。此外，將房價引入方差方程中，估計系數(shù)顯著不為零，說明房價的波動確實會顯著導(dǎo)致不良貸款率的變動，影響銀行穩(wěn)定，進而是金融穩(wěn)定。
[Abstract]:In order to study the regularity of the fluctuation of the real estate market in China, this paper, for the first time, uses cross-sectional CCE estimation method to analyze whether there is a long-term cointegration relationship between house price and per capita disposable income and loan balance. Then the spatial lag model is established for the residual sequence, and the spatial correlation coefficient is obtained by the maximum likelihood estimation method, so as to judge the existence and magnitude of the spatial effect of house price fluctuation. The results show that there is a significant spatial spillover effect in the fluctuation of house price in China. The fluctuation of house price in different cities has strong convergence, but there are some differences in the fluctuation of house price at the same time. The more developed city, not only high house price, fast growth, but also the more independent housing price, while the backward city, its house price is easy to be affected by the outside region housing price. At the same time, GARCH model is used to study the influence of fundamental factors such as house price on the non-performing loan rate of banks, so as to indirectly analyze the relationship between the fluctuation of house price and financial stability. The results show that when the GDP is included in the model, the estimated coefficient of GDP is the largest, followed by the broad money supply and the real estate price, and when the GDP is not included in the model, Both the real estate price index and the generalized money supply coefficient increase significantly, and the symbol of the coefficient is consistent with the actual economic situation. In addition, when the house price is introduced into the variance equation, the estimated coefficient is significantly not zero, which indicates that the fluctuation of the house price will cause the change of the non-performing loan ratio, which will affect the stability of the bank and then the financial stability.
【學(xué)位授予單位】：暨南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.5;F299.23

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