Xiaohan Tu1, Junchi Wang1, Lilin Liang2, Xiaoli Liu1, Dongliang Wang3
1College of Economic and Management, Tianjin University of Science and Technology, Tianjin, 300457, China
2College of Marine and Environmental Science, Tianjin University of Science &Technology, Tianjin, 300457, China
3College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, 300457, China
The housing problem is related to the well-being of the people's livelihood, and the housing price problem has always been a hot topic of social concern. Since the beginning of the 21st century, the problem of expensive housing in big cities has become more prominent, and the problem of housing prices has plagued the people. With the rapid economic development of big cities, more and more people are pouring into big cities to work and buy houses, and house prices are also rising sharply. Due to the government's macro-control policies and the epidemic, housing prices have also been affected. This paper intercepts the time series data such as the average house price and the gross regional product (GDP), price index (CPI), the number of permanent residents and the per capita disposable income of residents in Wuhan from 2000 to 2020. Using multiple regression model, it is concluded that the demand-side factors such as GDP, price index and disposable income of residents in Wuhan will positively affect housing prices, and thus predict the fluctuation trend of house prices in Wuhan in the future and put forward corresponding suggestions.
Housing prices, GDP, CPI, Disposable income of residents, Multiple regression
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