Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 39, 21 June 2024
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The research on factors influencing house value-take California as an example
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Abstract
Housing price is a popular and important topic in today’s society. This article aims to find the factors that have impacts on the housing price. To find the relationships between factors, this article uses Multiple Linear Regression as the method to perform a significant analysis of factors. 1000 samples of California’s block groups in 1990 are selected for this research. Based on the assumption, this research chooses 8 explanatory variables for the analysis. Because of the relationships between explanatory variables, the article also adds interaction terms between latitude and longitude, and population and total bedrooms to solve the multicollinearity problem among explanatory variables. To optimize model analysis effectiveness, this research compares the significance, VIF value, and GVIF value of explanatory variables. The analysis result shows that the geographical location (Latitude and longitude), the housing median age, the total bedrooms, the population, and the median income make significant impacts on the housing value. Among these factors, the median income is the main factor.
Keywords
Housing prices, multiple linear regression, interaction terms, California
References
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2. Rolfe S, et al. 2020 Housing as a social determinant of health and wellbeing: developing an empirically-informed realist theoretical framework, BMC Public Health 20, 1138.
3. Maclennan D, Ong R and Wood G 2015 Making connections: housing, productivity and economic development. Australian Housing and Urban Research Institute Limited, Melbourne.
4. Mao Y and Yao R 2020 A Geographic Feature Integrated Multivariate Linear Regression Method for House Price Prediction. 2020 3rd International Conference on Humanities Education and Social Sciences.
5. Garha N S and Azevedo A B 2021 Population and Housing (Mis)match in Lisbon, 1981–2018. A Challenge for an Aging Society. Soc. Sci., 102.
6. Hao Y, Zhuang L, Ying Z and Zhai J 2023 Influencing Factors of California Housing Prices in 1990: a Multiple Linear Regression Analysis. ICEMME, EAI.
7. Muzindutsi P F, et al. 2021 The effects of political, economic and financial components of country risk on housing prices in South Africa. International Journal of Housing Markets and Analysis.
8. Li N, Li R Y M and Nuttapong J 2022 Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database. Property Management796.
9. Özsoy O and Şahin H 2009 Housing price determinants in Istanbul, Turkey: An application of the classification and regression tree model. International Journal of Housing Markets and Analysis, 167-178.
10. Lin C T, et al. 2014 Effects of socioeconomic factors on regional housing prices in the USA. International Journal of Housing Markets and Analysis.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Mathematical Physics and Computational Simulation
- ISBN (Print)
- 978-1-83558-463-7
- ISBN (Online)
- 978-1-83558-464-4
- Published Date
- 21 June 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/39/20240571
- Copyright
- 21 June 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited