Factors influencing housing prices: A case study of Shanghai

Housing is a major consumer good for residents, and housing prices affect people's quality of life and happiness. This paper analyzes the factors influencing housing prices based on the housing price dataset for Shanghai in 2023-2024. Comparison is made via multiple linear regression model to discover the difference between with and without considering interaction terms, assessing the importance and accuracy of the two models' results, and optimizing the model. According to the analysis, living area, decoration type, and building usage are the factors most positively correlated with housing prices. The number of bathrooms, living rooms, and bedrooms also shows a significant positive correlation with housing prices. Additionally, building type and the construction age of the house are negatively correlated with housing prices, and this correlation is very significant. Finally, the housing area weakens the positive impact of the number of bathrooms and bedrooms on housing prices.

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Publication Details

Journal
Theoretical and Natural Science
Published
2024-09-27
DOI
https://doi.org/10.54254/2753-8818/52/2024ch0125
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
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Factors influencing housing prices: A case study of Shanghai

Xinning Fang
Theoretical and Natural Science
Housing Market and Economics
article

Factors influencing housing prices: A case study of Shanghai

Xinning Fang
article en

Abstract

Housing is a major consumer good for residents, and housing prices affect people's quality of life and happiness. This paper analyzes the factors influencing housing prices based on the housing price dataset for Shanghai in 2023-2024. Comparison is made via multiple linear regression model to discover the difference between with and without considering interaction terms, assessing the importance and accuracy of the two models' results, and optimizing the model. According to the analysis, living area, decoration type, and building usage are the factors most positively correlated with housing prices. The number of bathrooms, living rooms, and bedrooms also shows a significant positive correlation with housing prices. Additionally, building type and the construction age of the house are negatively correlated with housing prices, and this correlation is very significant. Finally, the housing area weakens the positive impact of the number of bathrooms and bedrooms on housing prices.

Theoretical and Natural ScienceVol. 52(1)
Openalex Percentile: Top 79%
Housing Market and Economics
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