本文選題：房地產(chǎn)市場 + 房價(jià)�。� 參考：《清華大學(xué)》2013年碩士論文

【摘要】：近年來，伴隨著住房制度和土地使用制度改革，我國的房地產(chǎn)業(yè)迅速發(fā)展，，不僅改善了城鎮(zhèn)居民的居住條件，也成為我國宏觀經(jīng)濟(jì)發(fā)展的支柱。但是，房價(jià)的持續(xù)、過快上漲所引起的房地產(chǎn)泡沫的跡象也給經(jīng)濟(jì)的穩(wěn)定發(fā)展蒙上了一層陰影。 住房問題關(guān)系國計(jì)民生，面對房地產(chǎn)價(jià)格過快上漲所造成的不良影響，政府給予了高度重視，各種形式的限售、限購和限價(jià)措施也相繼出臺(tái)。這些政策指向國民經(jīng)濟(jì)的方方面面，利用行政手段和市場調(diào)控平抑房價(jià)，同時(shí)打擊投機(jī)行為。近年來的實(shí)踐表明，這些措施部分取得了明顯的成果，但是也促成了“假結(jié)婚”、“假離婚”等一些社會(huì)熱點(diǎn)問題。 本文以北京市商品房銷售價(jià)格為例，探究房地產(chǎn)價(jià)格形成機(jī)制和影響因素。究竟是哪些因素影響了商品房價(jià)格，這些因素的影響程度如何，政府怎樣基于這些因素更加有效、穩(wěn)妥地進(jìn)行宏觀調(diào)控，是本文著重進(jìn)行分析，力求解決的問題。 本文首先介紹了行政指令形成機(jī)制、成本利潤形成機(jī)制和市場供需形成機(jī)制這三種房地產(chǎn)價(jià)格形成機(jī)制，列舉了人口、利率、經(jīng)濟(jì)發(fā)展水平、居民生活水平、各種價(jià)格指數(shù)、房屋施工建設(shè)和銷售情況等經(jīng)濟(jì)社會(huì)發(fā)展中各種可能影響房價(jià)的因素以及它們的作用形式，在收集數(shù)據(jù)的過程中對這些因素的內(nèi)涵作了進(jìn)一步的解釋。其次，通過對數(shù)據(jù)的探索性研究分析之后，使用線性回歸模型解釋數(shù)據(jù)之間的關(guān)系，同時(shí)采用多元線性回歸中的AIC準(zhǔn)則、方差膨脹因子等變量選擇方法使模型更加合理可靠。對于城鎮(zhèn)家庭人均可支配收入等具有明顯的季節(jié)性特征的數(shù)據(jù)，考慮到作為響應(yīng)變量的房屋價(jià)格指數(shù)沒有這樣的特點(diǎn)，采用季節(jié)效應(yīng)模型進(jìn)行分析，去除季節(jié)影響之后再進(jìn)行回歸分析，力求減少因季節(jié)波動(dòng)導(dǎo)致的反常影響。 從最終建立的模型及其殘差圖和預(yù)測曲線圖上可以看出，模型的合理性還是有一定保證的，但是與現(xiàn)實(shí)中的情況并不完全符合，這可能是在進(jìn)行變量選擇的時(shí)候遺漏了重要因素，也可能是數(shù)據(jù)中的一些隱藏的特性，比如異方差性沒有被考慮到，這些也是后續(xù)研究中需要考慮的問題。
[Abstract]:In recent years, with the reform of housing system and land use system, the real estate industry in China has developed rapidly, which not only improves the living conditions of urban residents, but also becomes the mainstay of our country's macroeconomic development. But the signs of a housing bubble caused by rising housing prices have also cast a shadow over the stability of the economy. The housing problem is related to the national economy and the people's livelihood. In the face of the adverse effects caused by the rapid rise in real estate prices, the government has attached great importance to it, and various forms of restrictions on sales, purchase restrictions and price restrictions have been introduced one after another. These policies point to all aspects of the national economy, using administrative measures and market regulation to stabilize house prices, while cracking down on speculation. The practice in recent years shows that these measures have achieved some obvious results, but also contributed to some hot social issues such as "fake marriage" and "fake divorce". This paper takes the selling price of commercial housing in Beijing as an example to explore the formation mechanism and influencing factors of real estate price. Exactly which factors affect the commodity housing prices, how these factors affect the degree, and how the government based on these factors more effective, stable macro-control, is the focus of this paper analysis, and strive to solve the problem. This paper first introduces three kinds of real estate price formation mechanisms, namely, administrative instruction formation mechanism, cost-profit formation mechanism and market supply-demand formation mechanism, and enumerates population, interest rate, economic development level, residents' living standard and various price indices. In the course of collecting data, the connotation of these factors is further explained in the course of building construction, sales and other economic and social development, which may affect the housing prices and their forms of action. Secondly, after the exploratory analysis of the data, the linear regression model is used to explain the relationship between the data, and the AIC criterion in the multivariate linear regression and the variable selection method such as variance expansion factor are used to make the model more reasonable and reliable. For the data with obvious seasonal characteristics such as per capita disposable income of urban households, taking into account that the housing price index as a response variable does not have such characteristics, the seasonal effect model is used to analyze the data. After removing seasonal effects, regression analysis was carried out to reduce the anomalous effects caused by seasonal fluctuations. It can be seen from the final model, its residuals and prediction curves that the rationality of the model is guaranteed, but it is not completely consistent with the actual situation. This may be due to the omission of important factors in the selection of variables, or some hidden features in the data, such as heteroscedasticity being not taken into account, which are also issues to be considered in subsequent studies.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F299.27;F224

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相關(guān)期刊論文 前2條

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本文編號：1826135