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The Empirical Of Relationship Between Population Structure And Commercial Housing Price

Posted on:2019-06-13Degree:MasterType:Thesis
Country:ChinaCandidate:Y Z ChenFull Text:PDF
GTID:2347330542473417Subject:Technical Economics and Management
Abstract/Summary:PDF Full Text Request
China's housing market has experienced the process of housing distribution and rationing from urban welfare to marketization.With the socio-economic development,the demand for housing in the market and the inflow of financial capital have brought the housing market to unprecedented heights."People" as the main use of housing,is closely related to the housing market.General Secretary Xi Jinping clearly pointed out in the report of the 19 th NPC that it is necessary to recognize clearly that the orientation of housing is based on housing and put an end to the phenomenon that property prices are being scorched higher in the market.At present,the population has begun to enter the stage of aging,the process of urbanization is also progressing day by day.The population structure has undergone tremendous changes.Therefore,during the period of major changes in the demographic structure,how to realize the "soft landing" in the housing market and what kind of interactive mechanism exists between them? Based on the previous studies,this paper has carried out this issue in-depth discussion.Taking Hangzhou as an example,this paper takes the natural structure of the population(sex ratio,dependency ratio,proportion of labor resources),socioeconomic structure(household size,income structure,industrial structure of employees)and geographical structure(net migration rate of population,the proportion of non-agricultural population)three aspects to research the inherent relationship with Hangzhou's housing market.First of all,this paper defines the related concepts and puts forward the corresponding hypotheses on the basis of theoretical analysis.By collecting the data of population structure and housing prices from 1994 to 2015,VAR models are established to test the hypotheses,then use impulse response function and analysis of variance decomposition to explain.The empirical results show that the change of housing prices in Hangzhou is related to the dependency ratio,the proportion of labor resources,household size,income structure,net migration rate of population and the proportion of non-agricultural population,but not relevant with the sex ratio and the industrial structure of employees.From the perspective of the natural structure of the population,it's own interpretation of housing price changes in Hangzhou is not strong.In the long run,the dependency ratio of dependents in the society is stronger than that of proportion of labor resources.From the perspective of population and socio-economic structure,household size is the main factor affecting housing prices in Hangzhou.Income structure will have a greater impact on housing prices in a short period of time,but it is not the major factor.From the aspect of population geography structure,in the long run,the proportion of non-agricultural population is the main factor affecting housing prices.The impact of net population migration on housing prices is timelagged.Finally,based on the empirical conclusions and analysis,this paper puts forward the relevant policy suggestions for the development of Hangzhou's future commodity housing market: 1)increase the types of housing construction,improve the basic facilities,adjust the unit area of new housing;2)Resolutely oppose speculation in the housing market and establish a new mechanism for low-rent housing and social security housing;3)Establish an integrated management model for migrants and improve the early warning mechanism for floating population;4)According to the local level of social and economic development,control the population urbanization rate;5)Strengthen the construction of population database,pay attention to the internal connection between population factors and housing market,and give play to the leading role of government.
Keywords/Search Tags:population structure, VAR model, House price
PDF Full Text Request
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