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A Study On The Relationship Between Housing Prices And Highly Educated Population Mobility

Posted on:2021-06-27Degree:MasterType:Thesis
Country:ChinaCandidate:H L LiFull Text:PDF
GTID:2517306224472984Subject:Technical Economics and Management
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Compared with developed countries,China’s urbanization rate still has a certain gap.In the future,there will be a large number of people pouring into the city.At the same time,in recent years,some cities have introduced relevant policies on talent introduction.However,since 2016,the price of housing has increased too much.In 2018,Huawei moved out of Shenzhen again.Under the background of such high price of housing,will the brain drain in the city lead to the decrease of human capital stock? At the same time,what will be the impact of a large number of highly educated people gathering in the city on the price of housing in the city.At present,scholars focus on the impact of the number and structure of population migration on housing prices,while the impact of urban housing prices on the floating population with high education is relatively small and inconsistent.In this context,this paper takes the mutual influence of urban housing price and high educated population as the starting point,clarifies the relationship between housing price and urban high educated population flow,and puts forward corresponding measures to solve the problem of high educated population flow and housing based on the actual needs of high educated population flow,and further puts forward suggestions for the city to attract high educated population,so as to promote the city High quality development.This paper puts forward four research hypotheses after combing the theory of house price and population migration,and then analyzes the current situation of house price and floating population.In order to test the four hypotheses of this paper,using panel data of 231 cities in China from 2010 to 2016,this paper establishes panel data regression model and PVAR regression model for empirical analysis,and divides the cities in China into three categories to explore the relationship between housing prices and the flow of highly educated population at the national and regional levels.In terms of panel data regression,the independent fixed effect regression equation of housing price and the proportion of high educated floating population is established.The control variables are urban income,infrastructure,basic education,medical services,fixed asset investment,real estate housing investment and industrial structure.Based on the regression results of the above two models,this paper draws the following conclusions:(1)the mobility of highly educated population has an obvious effect on the urban housing price,in a class of cities,the aggregation of highly educated population has a greater impact on the housing price;(2)the housing price has a greater impact on the flow of highly educated population in different cities The dynamic impact is not consistent.In the whole country,the increase of urban housing price will not hinder the inflow of highly educated population.In the first class of cities,the housing price has an inverted U-shaped impact on the flow of highly educated population,which first attracts and then suppresses,and has a significant positive U-shaped impact in the third class of cities;(3)the impact of urban high educated population flow and housing price is lagging behind.According to the above conclusions,this paper puts forward relevant policy recommendations in three aspects: reasonable control of housing prices,urban human capital accumulation and urban livability.The main creative points of this paper are as follows: 1.Research data: when measuring the floating population with high education background,the dynamic monitoring data of the national floating population in 2011-2017 are selected and sorted into panel data.2.Research perspective: from the perspective of urban floating population with high education background,study the relationship between housing price and floating population with high education background.
Keywords/Search Tags:housing price, floating population, proportion of high education, Panel data regression, PVAR model regression
PDF Full Text Request
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