Year: 2024
Type: article
Abstract: Considering various factors that affect house prices, this study investigates whether housing prices in Sydney can maintain their value or even increase in the future. A multiple linear regression model was applied using a dataset obtained from Kaggle, which includes 11,161 real estate transactions in Sydney from 2016 to 2021. This paper uses it to explore the relationship between housing prices and 12 independent variables (originally 14 but some have to be abandoned), such as the number of bedrooms, property size, median suburban income, and distance to the central business district (CBD). The results indicate that some factors have a positive, negative, or no impact on house prices and that 39.6% of the real estate price is influenced by them, indicating a moderate level of predictability. These findings provide valuable insights for investors and policymakers interested in the dynamics of the Sydney real estate market, emphasizing the importance of geographic location and property attributes in determining housing prices.
DOI: 10.54097/gcmy5277
Author: Hengjia Xu
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4405842549