Disentangling Demand And Supply Shocks In The Real Estate Market

As one of the important pillar industry of national economy,it is very importantfor real estate market to be in healthy operation,because the stability anddevelopment of the financial market has a close relationship with it. to someextent,development and prosperity of the real estate business, will be along with thesteady development of financial markets, in the same way, the real estate businessdepression, also can to a certain extent come with low financial markets. Therefore,we need to study from the perspective of supply and demand of housing prices, andfind out the root cause of fluctuations,then we can develop effective rein in propertyprices rise too much, so the constraints based on SVAR inspection symbols on theeffectiveness of the real estate market supply and demand impact study is verymeaningful.Nowadays,many researchers use structural vector auto-regression model,inorder to identify the impact of sign restrictions, but so far, there is no systematic wayto verify the fact that sign restrictions can be efficient in identifying the impact,although being setted in an idealized conditions,the conditions are under the signrestrictions specified effects of various shocks, but a series of problems still exist,such as data adjustments、omissions variables or measurement errors.For the reasonthat these problems exist, sign restrictions would not accurately reflect shock effect.The purpose of this paper is to identify the impact, to test the effectiveness of thesymbolic constraints.In order to accomplish this goal, we set up a simplified systemwhich contains three variables including actual reaction index of economic activity,the actual housing price and housing supply. In the model, the symbols we set come from the impact of the housing supply and demand.Demand shock include aggregatedemand shock which have been specified in the corresponding impulse response, onthe other hand, we can obtain the residual fluctuations.Joining the fluctuations canobtain the identified shocks,.Studies have shown that if the identified shocks meetsome of the weak column limit sign constraints, our analysis process can not only testsymbols used by previous researchers, could also apply further eliminate constraintsand help us do more accurate impulse response. More general argument is that ourresearch proves that how to identify the general constraints, especially our constraintmodel architecture can identify the symbol.We establish a model of a real estate market with three variables, which includesthe housing market prices, indicators that can reflect the actual economic activity andthe housing supply of housing market. On the basis of this model, we have done thestatistical test for he model including the likelihood ratio test, impulse responseanalysis and forecast error variance decomposition. The main conclusions are asfollows:Firstly，by doing the impact of forecast error variance decomposition for shocks,we found that the part of the price change the aggregate demand shock may explainare in change over time, especially, the role of practical economic activities playingon price change has also been gradually weakened.Secondly,Based on the supply and demand shocks of the real estate market, wetested the sign constraints in identifying the impact on the issue of effectiveness.Onthe basis of sign constraints,the method of modeling the volatility of the shocks byusing the Markov switching mechanism is efficient.Thirdly,policy recommendations: the influence of the actual economic activitiespiaying on the real estate market price is at weakened gradually, for to control thehousing price being reasonabe and effective,the government should take appropriatemeasures. According to the results of this article, the political advice includes: the government needs to clear their own role in the property market, clear its own dutywhich is trying to solve the problem of rural residents to buy a house, maintain ahealthy and orderly development of the real estate market and use tax to regulate thesupply and demand of the real estate market and hit some speculators.