Employing the methodology of multiple linear regression, this study delves into the primary determinants influencing real estate valuations in China in a systematic manner. In the midst of China's swift economic expansion, the real estate sector has evolved into a pivotal component of the economy, with fluctuations in property prices exerting a substantial influence on the stability of the socio-economic landscape. This paper aims to reveal the deep-seated reasons of China real estate price fluctuation through comprehensive analysis of various potential factors, and provide scientific basis for policy makers. The study selected data from 2010 to 2020. The empirical analysis results show that there is a significant negative correlation between the completed residential area and the real estate price, that is, the increase of supply will lead to the price decline, which is in line with the expectation of supply and demand theory. Housing cost has a significant positive impact on real estate prices, indicating that rising costs are an important factor in pushing up housing prices. The cost of land acquisition also has a positive impact on housing prices. Although its significance is slightly marginal, it confirms the important role of land cost in the formation of housing prices. However, the impact of development investment on housing prices is not significant, which may be related to various factors such as investment efficiency and market reaction time. The goodness of fit and significance analysis of the model show that the model can well explain and predict the changes of real estate prices, and the R-squared value is 0.76, indicating that the independent variable can explain 76% of the real estate price variation. The F-statistical value and its corresponding P value indicate that the model is statistically significant. Based on the results of empirical analysis, this paper puts forward the following policy suggestions: the government should stabilize housing prices by optimizing land policies and reducing land purchase fees; Optimize the investment structure and improve the efficiency of capital use; Comprehensively consider the market demand and policy environment, and formulate more comprehensive and accurate housing price control policies.
Wuyang Wang (Tue,) studied this question.