Application of Multiple Equal Linear Regression Model on Real Estate Batch Valuation

Hui-ling Yang *

School of Business, Guangdong University of Foreign Studies, Guangzhou, China

Jun-sheng Chen

School of Business, Guangdong University of Foreign Studies, Guangzhou, China

*Author to whom correspondence should be addressed.


Abstract

Linear regression method is one of the methods for assessing real estate batch. The defects of simple linear regression method are analyzed concretely in this paper, by selecting Foshan city real estate trading information for samples with empirical method. Equal linear regression is applied to analyze the housing prices in Foshan, by comparing the effect of linear regression and standard regression analysis of data, observing different regression models, analyzing the impact of pings number, room number, hall number, number of bathrooms and the age of the building variables on housing prices, to improve the linear regression method. The results show that if using the standard square regression to analyze, there may be undervalued and overvalued, which cannot correctly reflect what is the real factors that influence the estate price. This paper found that in the high-priced estate, if using the standard linear regression to estimate there, the number of rooms and the age of the building will be undervalued, and the number of bathrooms will be overvalued.

Keywords: Batch valuation, property valuation, analysis of regression, multiple equal linear regression


How to Cite

Yang, Hui-ling, and Jun-sheng Chen. 2018. “Application of Multiple Equal Linear Regression Model on Real Estate Batch Valuation”. Journal of Economics, Management and Trade 21 (5):1-7. https://doi.org/10.9734/JEMT/2018/41833.

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