Year: 2025
Type: conference-paper
Abstract: This article analyzes the data of gross domestic product, consumer price index, per capita disposable income, total real estate development investment, annual population at the end of each year, national sales area of commercial housing, and national sales of commercial housing from 2008 to 2022. Multiple linear regression, stepwise regression, Lasso regression, and random forest models are established to compare the national average housing sales with other factors. The regression model is analyzed using R language, and the best model is selected by comparing and adjusting the values and significant variables of R2, VIF, RMSE, MSE. On the basis of this model, analyze the relationship between housing prices and each factor, and provide corresponding countermeasures and suggestions.
Authors: Jiaxin Ou, Jiaoxia Zhang
Institution: Beijing Institute of Technology
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
Funder: Beijing Institute of Technology
Award: G191575292
OpenAlex ID: W4410776471