Housing Market Equilibrium And Price Volatility Risk

With the social and economic development，the real estate industry contribution to theeconomic growth is increasing. Furthermore，it relates highly with other industries and playsan important role in industry structure adjustment， economic prosperity promotion，consumption structure optimization and employment improvement. Under the economic andother factors such as demographic，political，culture，institution etc. real estate industrypresents cyclical fluctuation. The housing market is an important component of real estatemarket. According to incomplete statistics，there is about2/3real estate investment occupiedwith housing market in35cities. Since the housing reform，the housing has reflected the dualattributes of social security and goods. The housing market operation and housing pricemovement affect both on citizens’ welfare and national economy.The scale of investment in the real estate market is increasing quickly. As an importantcomponent of the third industry，the real estate industry structure，organization，developmentand policy study need scientific theories and methods urgently. SCP framework is a typicalparadiam of industrial organization theory. It is generally used to explore the short-and-longterm mutual relations between market structure，conduct and performance. Currently，thehousing market policy and investment philosophy are imperfect，so the market structure，behavior and performance as well as corporate and investor irrationality are housing marketrisk incentives. Validity or not of the housing market and the quantity and structureequilibrium of housing demand and supply in regional research conclusion are moredifferences，which are attributed by the scholars to the oligopoly or insufficient degree ofmonopoly market structure. Facing to the housing price continued rapidly rising，whetherthere certainly exists a bubble with high price and the time-varying and persistent volatilitytogether with the consequently risk are hot momentsBased on the status of housing market，differences and hotspots，the author studiedhousing market structure and equilibrium characteristics，price volatility resources and houseprice volatility risk by integrated using finance，econometrics and other disciplinary theoriesand methods under the real estate economics and industrial economics theoretical background.The research and conclusion can rich the housing market competition and equilibrium theory，reflect the current price fluctuation regulation and provide forward information for investmentand policy and enhance the ability of identification and crisis prevention. The main contents and conclusions are as follows：(1) The monopolistic competition and the relative equibirium of supply and demandresearch under the SCP framework. In the industrial economics SCP framework，the authorstudied the relative monopolistic of housing market structure through modify the HHI index，analyzed the regional difference of market efficiency and price serial correlation throughvariance ratio calculation， measured the deviation of market price relative to the industryaverage cost by Lerner Index which to a certain extent reflects the monopoly factors andexcess demand during the market operation. In this paper，the author divided the housingdemand into short term supply change and long term equilibrium deviation. The half-life is8.7months calculated by the error correction model. These modified indicators and modeloutline a clear understanding of the real estate market，price movement regulation.(2) Individual fixed effects dynamic variable intercept model highlights the consumerinertia in the role of housing price fluctuation. Based on the supply and demand equilibriumanalysis，the author using panel data constructed individual fixed effects variable interceptmodel. The empirical results show that the housing price is proportional to the sales area andinversely to the numbers of households，land acquisition costs，production costs are the mainfactors affecting price volatility and the regional differences are significant. After weconsidered the consumer inertia in the model，the empirical result show that the sales area andnumbers of households turns to be insignificant，the consumer inertia appears significant. Thischange explains to some extent the non-demand effect on the housing price increase.(3) Value at Risk assessment by Monte Carlo simulation. Based on the AR-GARCHmodel，the author takes the Geometric Brownian motion as the housing price volatilitystochastic model and forecast the housing price index and VaR by Monte Carlo technique.Compared with the real change of the housing price index and the VaR，the AR-GARCHmodel underestimates the price risk. It is to say that，there is higher level price volatility riskin real housing market.