Year: 2024
Type: article
Abstract: This paper is about analyzing dataset recorded between 1975 and 2021 about the house prices in United State and uses multiple linear regression to plot linear equation to help to predict the future house prices. The data includes some essential factors, population for example, that influences house prices index both directly and indirectly and did a further analysis to find the correlation between these factors and house prices index, and the correlation between each influencing factors. These factors all have difference significance level comparing to house price index, making it worth to find out even deeper the most influencing factors that affect house price index so the most important factors can be deduced. In the result, real disposable income is being concluded as the most important factors effecting the house price index among all other factors. In addition, the author also uses determinant coefficient to further confirm the accuracy of the multiple linear regression, making sure linear regression is a valid method to analyze the significance of all influencing factors.
DOI: 10.54097/gfxf8r63
Author: Jinhe Liu
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4405842708