中国房价波动特征及政策调控效应研究

发布时间：2018-01-02 06:21

本文关键词：中国房价波动特征及政策调控效应研究　出处：《中国地质大学》2017年博士论文　论文类型：学位论文

【摘要】：我国房地产市场化改革以来,截至2015年底,全国平均房价增长了2.57倍,除了次贷危机期间出现短暂下跌外,房价的上涨从未停止。2008年之后经济增长趋缓,但房价反而急剧上涨,引起了各界人士对房价波动的关注和对房价泡沫的担忧。同期,我国政府出台了大量的政策对房地产市场进行调控,尤其是2008年之后,但房价却陷入“越调越涨”的窘境之中,调控政策的有效性受到质疑。房价波动和房价泡沫的正确判断是制定、实施和评价调控政策的基础和依据,其中方法和数据是关键。指标法的前提是房价决定于经济基本面,否则指标法的应用就失去了意义。在数据方面,目前大都使用官方数据,但其质量备受争议,相对和平均意义的数据形式忽略了房地产的异质性。大数据的兴起为房价泡沫研究提供了包含异质性特征的数据,在提高对其判断的正确性的同时,也能够为政策调控提供更为合理的依据。本文围绕“房价波动”和“政策调控”两条主线,以房价决定理论与模型、大数据理论、特征价格理论和政府干预理论为基础,利用房天下和链接网站,抓取了30个省会城市和直辖市的房价发布信息,形成我国房价的网络大数据。以此为基础,构建房地产的特征价格模型,对房价进行特征调整;然后通过文献研究法梳理房价的影响因素,利用BMA方法和MC3抽样技术筛选出对房价最具解释力的影响因素集,回归得到基础房价;结合两个数据最终得到房价泡沫的结果,从GDP、收入、区域、人口、土地等角度对房价波动特征进行分析。将房价波动定义为市场和政府干预两种机制作用的结果,利用30个省市1999-2015年的面板数据展开实证分析。首先利用HP滤波法分离出长期趋势下的均衡房价,得到房价波动的总效应;其次使用变量减少法筛选出影响房价的市场因素集,回归得到市场机制下的房价,并计算得到房价波动的市场效应;通过相减得到政府干预机制下的政策效应。结合两种方法下获得的房价影响因素集,在对四象限模型扩展的基础上,建立使用市场和资产市场、长期与短期的分析框架,对房价波动的形成机制进行解释。调控政策对房价波动的作用,首先考虑政策是否将房价波动作为反应变量,在前人研究的基础上,构建了货币、财政和土地政策变量对房价的反应函数,利用1998-2014年的时间序列数据,并以2008年为界,使用GMM模型实证分析不同阶段的调控政策对房价的立场和反应。其次,在分析政策对房价的影响机理的基础上,建立房价与政策变量的回归模型,利用上述数据实证分析各项政策对房价波动的影响。最后,使用脉冲响应函数分析政策变量对房价的动态影响,并运用方差分解方法确定各项政策变量对房价波动的贡献大小。本文的研究结论如下:(1)政策调控失效的原因之一是对房价泡沫的判断出现了偏差,测度方法和数据选择由于不能完全反映房地产的异质性,因此很难反映出房价波动和房价泡沫的真实情况,随着时间推移,政策调控可能会加剧房价波动。(2)影响房价的特征变量中,建筑面积对房价的弹性大于1;多数城市房价对房间数的弹性为负,且绝对值小于0.5;建筑年代越早,反而总价越高;大多数城市的楼层越高,房价越低。(3)土地因素和收入因素是基础房价,即长期均衡房价的决定因素,尤其是土地因素,包括土地总成本、土地供应量和土地价格,土地市场对长期房价的影响最为突出。短期市场房价决定于收入、投资、成本、技术和劳动力等因素。(4)我国不存在全面性的房价泡沫,只存在局部泡沫,80%的城市房价均处于合理波动范围内。30个省会城市和直辖市中,一半城市的房价被高估,另外一半城市被低估,即实际房价没有反映出真实价值。GDP、土地对房价波动存在阈值效应,房价波动具有异质变异特征和收入效应,人口因素不能解释区域间的差异。(5)2009年之后大多数省市的房价波动为正,但幅度不大,具有明显的趋同性和空间递进特征。1999-2015年市场机制下的房价波动构成了一个完整的周期,并且大部分时间内房价被低估,市场机制对房价的决定作用并未因区域间市场成熟度的不同而不同。2008-2010年的扩张性政策是房价上涨的重要原因,尤其对于东部省市,真正意义上的负效应政策调控在2012年之后,但调控政策在不同区域间并未实现同步影响,而是由东向西转移。(6)引入房价变量,政策的最优反应规则需要对产出、通货膨胀及其滞后项和房价做出反应。货币供应量对房价做出了相反的反应,是房价高涨的重要原因;整体上,货币政策并未对房价做出显著反应,反而加剧了房价的上涨,土地政策的反应逐步走强,固定资产投资的反应趋于减弱;利率和货币供应量对经济增长和通货膨胀的反应的显著性呈现交错变化特征。(7)货币供应量对房价波动的影响最大,但有一定幅度的降低,是房价持续上涨的重要原因,同时利率政策推高了房价。土地供应对房价的影响有限,并不断下滑,固定资产投资对房价的影响在2008年之后变得显著。利率在短期内对房价负向影响,而货币供应量的影响在长期,固定资产投资和土地供应量对房价的短期影响明显。4个政策变量中,货币供应量对房价的影响最大,其次是固定资产投资、利率和土地供应量。(8)实现房地产市场的健康有序发展以及房价稳定,应发挥市场机制对房价的决定作用,实施分城施策,加强调控政策对房价的反应和政策的规则化和制度化建设,完善土地供应体系,发挥土地供应对房价的作用。本文的创新点在于:(1)基于大数据理念,建立了30个省会城市和直辖市的房价大数据,通过构建HPM模型对市场房价进行调整,得到反映异质性特征的房价数据,利用基础价值法拟合并导出长期均衡房价,从而得到房价泡沫结果,形成了房价泡沫测度与判断的方法和框架。(2)在市场机制和政府干预机制对房价决定的模型框架下,利用回归方法对两种机制产生的房价波动进行分解,从而能够判断和评价两种机制分别对房价波动的影响程度和效应。(3)分析各项政策对房价波动的影响之前,构建了引入房价变量的政策反应函数,并推导了最优政策反应规则,分别实证分析了货币、财政和土地政策对房价波动的立场和反应。将三项政策置于同一框架下,实证分析它们各自对房价波动的影响,包括静态和动态影响。
[Abstract]:Since the reform of China's real estate market, by the end of 2015, the national average price increase of 2.57 times, but fell short appears during the subprime crisis, housing prices have never stopped.2008 years after economic growth slowed, but prices rose sharply, attracted people from all walks of life on the price fluctuations and to the attention of the housing bubble worries the same period, the Chinese government issued a number of policies to regulate the real estate market, especially after 2008, but the price is in the more stressed the more up predicament, effective control policy has been questioned. Correct judgment of price volatility and price bubble is making, implementation and evaluation and the basis of regulatory policy among them, methods and data is the key precondition. Index method is the price depends on the economic fundamentals, or the application of index method is meaningless. In terms of data, most of the current use of the official number According to its quality, but controversial, and the average relative significance of data form ignores the heterogeneity of real estate. The rise of big data provides a heterogeneity of data for the study of the housing bubble in the right to improve the judgment at the same time, can also provide a more reasonable basis for policy regulation. This paper focuses on the "price fluctuations" and "policy" the two main line, with prices in decision theory and model, big data theory, the hedonic price theory and government intervention theory as the foundation, the use of real world and linked sites, grabbed 30 of the capital city and the municipality prices to release information, the formation of large data network of China's housing prices. On this basis, the hedonic price model of real estate construction, characteristic adjustment of prices; then through literature research method combing the factors affecting prices, using the BMA method and the MC3 sampling technique to screen the prices Influential explanatory factors, regression based prices; combined with the two data obtained from the GDP results of the housing bubble, area, population, income, and to analyze the characteristics of land price fluctuations and other aspects. The price fluctuations in the market and the government intervention is defined as two kinds of machine made the results of empirical analysis, using the panel data of 30 provinces during 1999-2015. The first isolated long-term equilibrium prices under the trend of the use of the HP filter, to obtain the total effect of price fluctuations; secondly use variable reduction method to find out influencing factors of market prices, to get under the market mechanism of prices, and to calculate the market effect of price fluctuations; policy the effects of government intervention mechanism under the influence of factors. By subtracting prices obtained from the two methods combined with the set, based on the expansion of the four quadrant model, the establishment of long-term market and asset market. With the analysis framework of short-term, the formation mechanism of housing price fluctuation was explained. Effects of regulatory policies on price fluctuations, first consider whether the policy will be price fluctuations as a response variable, on the basis of previous research, build the monetary reaction function, finance and land policy variables on the price, using the time series data 1998-2014 in 2008, the use of GMM model to analyze the different stages of the regulatory policy positions and responses of prices. Secondly, in the analysis of the policy impact on the price mechanism on the basis of establishing the regression model of prices and policy variables, analysis of the impact of policies on price fluctuations by the empirical data. Finally, using the impulse response function analysis of dynamic effects of policy variables on prices, and use the variance decomposition method to determine the contribution of the policy variables on the price fluctuations. The conclusion of this paper One of the reasons are as follows: (1) policy failure is the housing bubble judgment, measurement methods and data selection because of heterogeneity can not fully reflect the real estate, so it is difficult to reflect the real situation of price fluctuations and the housing bubble, with the passage of time, policy may exacerbate price fluctuations (2. The impact of price variables), the construction area of housing price elasticity is greater than 1; most of the city of elastic room number is negative, and the absolute value is less than 0.5; the building earlier, but the higher price; most of the city's higher floors, prices lower. (3) land factor and income factor is based on prices, determinants of long-term equilibrium prices, especially land factors, including the total cost of land, land supply and land prices, land prices on the market long-term effect is most prominent. The short-term market price depends on the income of investment The cost of capital, labor, technology and other factors. (4) does not exist in our country comprehensive housing bubble, there is only local bubble, 80% city house prices are at a reasonable range of.30 in the capital city and municipality directly under the central government, half of the city's housing prices are overvalued, the other half city is undervalued, the actual price was not reflect the true value of.GDP, there is a threshold effect on land price fluctuations, the price fluctuations have heterogeneous variability and the income effect, population factors cannot explain the differences between regions. (5) after the 2009 price fluctuations in most provinces is positive, but modest, has the obvious trend of price fluctuations and spatial characteristics of same-sex.1999-2015 progressive market the mechanism consists of a complete cycle, and most of the time in the price is undervalued, determine the role of the market mechanism of prices is not due to the regional market maturity varies.2008-2 010 years of expansionary policy is an important reason for rising prices, especially in the eastern provinces, the true sense of the negative effect of policy regulation in 2012, but the regulation policy in different regions did not achieve the synchronization effect, but the transfer from east to west. (6) the introduction of price variables, the optimal reaction rules and policies need to output. Inflation and its lag and prices respond. Money supply in response to housing prices is an important reason for rising prices; on the whole, the monetary policy did not make a significant response to prices, but increased prices, land policy reaction gradually strengthened, fixed asset investment response tends to weaken significantly; the money supply and interest rates in response to economic growth and inflation has staggered changes. (7) the impact of money supply on price fluctuations, but to a certain extent reduced An important reason is low, housing prices continued to rise, while the interest rate policy to push up prices. Land supply limited impact on prices, and declining prices, the impact of investment in fixed assets to become significant after 2008. The interest rate in the short term negative impact on prices, and the money supply influence in the long term, short term the impact of investment in fixed assets and land supply for housing was.4 a policy variable, the impact of money supply on the price of the largest, followed by investment in fixed assets, interest rates and the supply of land. (8), price stability and orderly development of the realization of the real estate market health, should play a decisive role in the market mechanism of prices and the implementation of the city facilities strategy, strengthen the construction of the policy of price regulation and policy rules and reaction system, improve the land supply system, play the role of land supply on house prices. The creative points of this paper are as follows: (1) base On the idea of big data, big data set up 30 provincial city and municipality directly under the central government house, by constructing a HPM model to adjust the market prices, housing prices get data to reflect the heterogeneity of the long-term equilibrium price derived by fitting value based method, so as to get the price bubble, forming method and framework of the housing bubble measure and judgment. (2) in the framework of market mechanism and government intervention mechanism of price decision, price fluctuations were produced in two different mechanisms by using regression method of decomposition, which can judge and evaluate the two mechanisms respectively on the fluctuation of the price impact and effect. (3) before analyzing the influence of policy on housing prices the volatility of the established policy reaction function into price variables, and the optimal policy rule is derived, respectively, the empirical analysis of monetary, financial and land policies on price fluctuations and position The three policies were placed in the same framework to demonstrate their impact on the volatility of house prices, including static and dynamic effects.

【学位授予单位】：中国地质大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：F299.23

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