An Empirical Study on the Influencing Factors of Second-Hand Housing Prices Based on the OLS-WLS Model
DOI:
https://doi.org/10.54097/rr66k248Keywords:
Second-Hand Housing Prices; Multiple Linear Regression; WLS Correction; Influencing Factors; Beijing.Abstract
This study investigates the second-hand housing market in Beijing, focusing on building area and school district status as the core variables, while controlling for housing features such as renovation level, heating type, and elevator availability. The effects of these factors on housing prices are quantified by using a multiple linear regression model. After conducting normality and heteroscedasticity tests on the residuals, and applying weighted least squares (WLS) correction, the results indicate that building area and school district status have significant positive impacts on housing prices. Elevator availability increases prices, centralized heating has a negative effect, and high-end renovation is not statistically significant. The adjusted of the model is 0.687, indicating a good overall fit. The findings of this study provide practical guidance for buyers and offer a reference for government housing market regulation.
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