本文關(guān)鍵詞：杭州市商品房市場調(diào)控政策的系統(tǒng)動力學仿真研究　出處：《浙江大學》2014年碩士論文　論文類型：學位論文

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【摘要】：自2003年國家將房地產(chǎn)業(yè)定位為支柱產(chǎn)業(yè)以來,我國的房地產(chǎn)業(yè)出現(xiàn)了飛速的發(fā)展,近十年來房價與銷售量同時大幅上漲,引起了社會各界的廣泛關(guān)注。國家也出臺了一系列的措施進行調(diào)控,但是結(jié)果卻并不理想。因此,全面分析我國房地產(chǎn)市場的發(fā)展與宏觀調(diào)控作用,構(gòu)建政策對房地產(chǎn)市場影響的仿真模型是十分必要的。本文以杭州市商品房市場為例,建立系統(tǒng)動力學仿真模型,對政策調(diào)控作用下的杭州市商品房市場進行模擬,并通過政策實驗,提出較有效的政策建議。本文的主要工作及結(jié)論有： 首先,在總結(jié)國內(nèi)外當前研究成果的基礎(chǔ)上,針對房地產(chǎn)市場復雜多變的特性,選擇對處理高階次、非線性、多重反饋的系統(tǒng)問題具有優(yōu)勢的系統(tǒng)動力學方法進行本研究的模型構(gòu)建與仿真。以杭州市商品房市場為例,將其劃分為價格子系統(tǒng)、供給子系統(tǒng)和需求子系統(tǒng)(其中,需求子系統(tǒng)又區(qū)分自主性需求與投資性需求),繪制因果反饋圖和系統(tǒng)流圖,尋找因素間的關(guān)系以及各因素對系統(tǒng)的影響力,建立杭州市商品房市場系統(tǒng)動力學仿真模型。 定義變量,運用多元回歸、打分賦值等方法對杭州市商品房市場系統(tǒng)動力學仿真模型進行參數(shù)估計和指標估算,列出DYNAMO方程,運用計算機軟件Vensim PLE6.2對模型運算,并進行真實性檢驗,通過對比仿真值與實際值,發(fā)現(xiàn)系統(tǒng)模型的整體仿真性能較好,平均誤差都能保證在10%以內(nèi),可以認為模型是有效的。根據(jù)模型的仿真結(jié)果,2013年杭州市區(qū)商品房均價的預測值為18734元/m2。 最后,調(diào)整模型參數(shù),進行政策實驗。結(jié)果表明：人口政策對商品房價格的影響較小,但對需求的刺激作用明顯。寬松的貨幣政策會帶動房價的上漲,而緊縮的貨幣政策并不會抑制房價的上升。按揭政策對商品房市場的影響最大,特別是寬松的按揭政策會推動房價和需求大量抬升,緊縮的按揭政策則會打壓房價,同時減少需求量,但是變化幅度遠不及寬松的政策作用,并且當政策的緊縮性到達一定的臨界值時,繼續(xù)加大調(diào)控力度對抑制價格的邊際作用是有限的。新房購置契稅稅率的調(diào)整幾乎對商品房市場沒有太大影響,無論是提高還是降低稅率對商品房市場的成交量和價格都改變不大。
[Abstract]:Since 2003, the country has positioned the real estate industry as the pillar industry, the real estate industry of our country has appeared the rapid development, the house price and the sales volume simultaneously rise sharply in the last ten years. The government has also issued a series of measures to control, but the results are not ideal. Therefore, the comprehensive analysis of the development of the real estate market in China and the role of macro-control. It is necessary to build a simulation model of the impact of policies on the real estate market. This paper takes the commercial housing market in Hangzhou as an example to establish the simulation model of system dynamics. This paper simulates the commercial housing market in Hangzhou under the action of policy regulation and puts forward some effective policy suggestions through policy experiments. The main work and conclusions of this paper are as follows: First of all, on the basis of summarizing the current research results at home and abroad, in view of the complex and changeable characteristics of the real estate market, choose to deal with the higher order, nonlinear. Multi-feedback system problem with the advantage of the system dynamics method to build and simulate the model of this study. Taking the commercial housing market in Hangzhou as an example, it is divided into price subsystem. The supply subsystem and the demand subsystem (among them, the demand subsystem distinguishes the independent demand from the investment demand, draws the causality feedback diagram and the system flow diagram, looks for the relationship between the factors and the influence of each factor on the system. The system dynamics simulation model of commercial housing market in Hangzhou was established. Define variables, use multivariate regression, score assignment and other methods to Hangzhou commercial housing market system dynamics simulation model parameter estimation and index estimation, and list the DYNAMO equation. The computer software Vensim PLE6.2 is used to calculate the model and verify the authenticity of the model. By comparing the simulation value with the actual value, it is found that the overall simulation performance of the system model is better. The average error can be guaranteed to be less than 10%, which can be regarded as valid. According to the simulation results of the model, the forecast value of the average price of commercial housing in Hangzhou urban area in 2013 is 18734 yuan / m2. Finally, adjust the parameters of the model, carry on the policy experiment. The result shows that the population policy has little influence on the commodity housing price, but the stimulative effect on the demand is obvious, and the loose monetary policy will lead to the rise of the house price. But tight monetary policy will not restrain the rise of house prices. Mortgage policy will have the greatest impact on the commodity housing market, especially the loose mortgage policy will promote a large increase in house prices and demand. Tight mortgage policy will suppress house prices and reduce demand, but the change is not as loose as the role of policy, and when the policy tightening reached a certain threshold. The marginal effect of increasing regulation and control on restraining prices is limited. The adjustment of contract tax rate on new house purchase has little effect on the commercial housing market. Whether raising or reducing the tax rate on the commercial housing market volume and prices do not change much.
【學位授予單位】：浙江大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F299.23;N941.3

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