| The real estate market is an important pillar industry in China.On the one hand,the real estate market is closely related to economic growth;On the other hand,as an important consumption and investment object of Chinese households,housing is an indispensable asset for them.The healthy development of the real estate market is related to the living standard of Chinese households.Since the transition from the welfare housing allocation to the commercialized market,China’s real estate market has been developing rapidly,especially after 2016.However,even under the pressure of high house prices,affected by various reasons such as "difference between renting and purchasing" and traditional family concepts,Chinese households still have the phenomenon of "paying more attention to buying than renting".In order to alleviate the overheating of the housing sales market,the government has issued various real estate regulation policies to curb the demand for house purchase and develop the rental market,but the proportion of house purchase families in China still far exceeds that of rental families.This paper attempts to study the household tenure choice under the background of increasing house prices.In this paper,we first use the neural network model to estimate the rent in the future and calculate the basic value of the real estate by calculating the rent discount,then calculates the bubble.According to the measured bubble,it can be found that the bubble of second-hand housing is much higher than that of the first-hand housing market,and the bubble gap between first-hand and second-hand housing in first-tier cities tends to further expand,while second-tier cities tend to shrink.Then,this paper uses the estimated bubble and the city-level data from2011 to 2020 to conduct empirical analysis to illustrate the influencing factors of the bubble.The results show that educational resources have a greater impact on the housing market bubble.Then,by using bubbles as explanatory variables,we study the impact of bubbles on household tenure choice.The results show that,both first and second hand housing market bubble has a positive impact on the family purchase probability,and the influence of the first hand housing market bubble on family purchase decision is smaller than that of the second hand housing market bubble on family purchase decision.Then,this paper constructs a heterogeneous multi-agent model including developers and families,dynamically simulates the transaction process of China’s housing market,and studies the dynamic evolution process of housing market price and trading volume.The simulation results show that family psychological expectation and housing rental decision making behavior are the main reasons leading to the fluctuation of housing prices and bubbles in China.Among them,expectation plays a vital role in the appreciation of house prices.When households have trend extrapolation expectations,with the increase of house price rise,the investment demand of this type of households will increase,further pile up house prices and pile up expectations again.The two promote each other to form a vicious circle.One of the main contributions of this paper is that in the empirical analysis,the structure of the explained variable "house purchase decision" used in this paper is relatively novel.The structure of this index reflects a dynamic decision-making process of the household.In the theoretical research,we constructed a multi-agent simulation model including the first hand housing market,the second hand housing market and the rental market,and studied the relationship between the bubble and the household tenure choice,which provided new ideas and methods for the domestic research.Another major contribution is the innovative research of household tenure choice from the perspective of bubbles,linking the micro family decision-making behavior with the macro market performance,and studying the impact of the family’s micro behavior on the market. |
