The Research on Factors Influencing Housing Prices-Taking California for Example
DOI:
https://doi.org/10.54097/hqzskw61Keywords:
House price; interaction; linear regression way.Abstract
This article is about something on impacting factors of house prices. In this research, multiple linear regression is used as a method. Regression method is a scientific tool that provides insights into the dynamics of how a dependent X factor responds to changes in one or more independent variables. This research finds that there are many factors and Indies do influence on the housing prices, including GDP, CPI, Income, Urban population, Delinquency rate, etc. Most of those factors or Indies have positive correlation with housing price. And through further analysis selection and analysis, research find that CPI and GDP has positive relation vs housing price and its correlation degree is most highly in those factors. And then GDP and CPI working as independent variables in multi linear regression come to a model. For this model, T test, R-squared test, F test and practical test have been done to proof this model is reasonable. And this model can be used in practical housing price analysis.
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