【作者】 李斌；

【导师】 张所地；

【作者基本信息】 山西财经大学 ， 统计学， 2013， 博士

【摘要】 预期直接影响着商品住宅市场的运行轨迹，能否揭示二者之间的本质联系关系到市场参与者投资、消费决策的成败，关系到政府住房宏观调控的效果，也关系到整个国民经济的正常运行与社会的和谐稳定。本文从预期与商品住宅价格的关系、预期与住房宏观调控效果的关系、商品住宅价格与预期回报的关系、商品住宅市场预期的形成与扩散四个方面入手，探析了预期对中国商品住宅市场的影响机理。主要的研究工作如下：1．基于预期异质性的商品住宅价格模型构建与实证研究根据市场特点和交易者行为差异，将金融市场的噪声交易模型进行了符合商品住宅市场的重新设定，首次采用世代交迭模型的跨期决策分析方法，构建了包含理性套利者、动量交易者、信息观察者、基本面分析者4类异质交易者预期的商品住宅价格模型；在考虑预期异质性情形下，采用系统仿真方法探析了异质交易者的重要行为参数对住宅价格的单独影响和叠加影响；在不考虑预期异质性情形下，将上述模型转化为一般的含有预期的住宅价格模型，并选取中国30个省（市、自治区）商品住宅市场的省际面板数据进行了实证检验，由于模型建立过程中引入了更符合经验事实的微观基础，而又不脱离传统的宏观基本面分析方法，从而可以更好地揭示预期与商品住宅价格这两种随机波动序列的本质联系。2．基于环境异质性的住房宏观调控模型构建与实证研究将预期模式与城市的差异性引入了商品住宅供给和需求调控的分析框架，在住宅存量—流量模型基础上分别建立了考虑异质预期和异质城市政策实施环境的住房供给调控动态模型和住房需求调控模型；对中国35个大中城市住房宏观调控的实施效应进行了量化研究、比较分析和系统仿真，识别出了有效的政策工具，模拟了异质环境下商品住宅市场的运行轨迹，为政府出台具有精准性、有效性的调控政策提供了有力依据。3．房价与理性（适应性）预期回报的非线性双重时序模型构建与实证研究在房地产回报的非线性双重时序评估模型基础上，首次将预期引入了房价与回报非线性关系的研究框架，将商品住宅价格与预期回报的随机序列视为一个随机系统，利用现代随机系统理论方法进行了系统辨识，构建了可以更好地描述商品住宅市场随机机制的房价与理性（适应性）预期回报的非线性双重时序模型；首次给出了量化不可观测的预期回报的方法，并在中国35个大中城市进行了预期回报评估的实证分析，识别出了具有投资价值的城市和地区，为市场参与者的投资消费决策提供了合理的评估方法和结论。4．商品住宅市场预期扩散模型构建与仿真研究首次将创新扩散理论与方法应用于住宅市场预期的研究，对传染病扩散模型与Bass模型进行了符合住宅市场现状的重新设定，对仅存在口头交流等内部影响和同时存在大众传媒等外部影响两种情形下的预期扩散过程进行了理论描述、建模刻画与系统仿真，识别出了两种条件下影响预期扩散的关键因素，探析了预期的扩散规律，为预期的培养、管理活动提供了决策参考。本文的研究工作有助于深入认识商品住宅市场的运行规律，为现实中的房价波动、调控低效、需求非理性增长等问题提供了更多的解释与解决手段，为政府、房地产企业和购房者的行为决策提供了科学依据，也为一般的带预期的非线性随机系统的理论与应用研究提供了一种崭新的思路。更多还原

【Abstract】 Expectations affect the trajectory of commercial housing market directly. Revealing theessential relationship between them is a crucial problem related to success or failure of marketparticipants’ decision making about investment or consumption, related to the effects of housingmacro control, and also related to operation of national economy and social harmony and stability.In order to reveal how do expectations affect commercial housing market, this dissertation studiesthe relationships between expectations and house prices, expectations and effects of housing macrocontrol, house prices and return expectations, and formation and diffusion of expectations. Themain work is as follows:1. Building the commercial housing prices model which contains heterogeneous expectationsand making an empirical studyAccording to market characteristics and differences of traders, the DSSW model in financialmarket is reset in accordance with commercial housing market for the first time, the equilibriummodel of commercial housing prices which contains4kinds of traders as Rational Arbitrageurs,Momentum Traders, Information Watchers and Fundamental Analyzers is built by the interperioddecision making method of stripped-down overlapping generations model. In the case ofconsidering heterogeneous expectations, the separate and superimposed effects of heterogeneoustraders’ important behavioral parameters on house equilibrium price are discussed throughsimulation method; in the opposite case, the model is transformed into a general house prices modelwhich contains expectations, and empirical research is made applying panel data model of30provinces in China. Due to introduction of micro-foundation in line with experience and facts, andwithout departing from the traditional macro-fundamental analysis method, the model can betterreveal the essential relationship between expectations and commercial housing prices.2. Building the housing macro control model which considers environmental heterogeneity andmaking an empirical studyDifferences in expectation patterns and cities are introduced into analysis framework ofcommercial housing supply and demand regulation. On the basis of the housing stock-flow model,housing supply regulation dynamic model and demand regulation model considering heterogeneousexpectations and heterogeneous urban environment of policies implementation are establishedrespectively; quantitative and comparative analyses of housing macro control effects on35cities inChina are made. Adopting method of system simulation, the optimal policy instruments areidentified and trajectory of commercial housing market is simulated, which provide a strong basis for government to make precise and effective policies.3. Building the nonlinear doubly time series models of real estate prices and rational (adaptive)return expectations and making an empirical studyExpectation is introduced into research framework of prices and returns for the first time onthe basis of the nonlinear doubly time series appraisal model of real estate return, commercialhousing prices and return expectations are treated as a random system which is identified adoptingthe modern theoretical methods of stochastic systems, and the nonlinear doubly time series modelsof real estate prices and rational (adaptive) return expectations are built which can describe marketstochastic mechanism better; the method that using observable prices sequence to quantify theunobservable return expectations sequence based on the relationship between them is given for thefirst time, and an empirical study on35cities in China is made. Cities or regions with goodinvestment return are identified by above research, and reasonable appraisal method andconclusions are provided for market participants to make investment and consumption decisions.4. Building the expectation diffusion model in commercial housing market and making asimulation studyThe innovation diffusion theory and methods are applied to the study of expectations inhousing market for the first time, the infectious diseases diffusion model and Bass model are resetto meet housing market status, the expectations diffusion in commercial housing market is analyzedon assumptions that there is only internal influence and there are both internal and externalinfluences; key factors affecting expectations diffusion on two types of conditions are identified,diffusion laws are analyzed, and decision-making reference is provided for expectations cultivationand management.The research work in this dissertation contributes to analyze the laws governing the operationof commercial housing market, provides more explanations and solutions to soaring prices,overheated investment and inefficient regulation in reality. The conclusions are helpful forgovernment, developers and house purchasers to make investment and consumption decisionsaccurately. In addition, the research work also provides a new train of thought for theoretical andapplied research on general nonlinear stochastic system with expectations.更多还原