Affiliations: College of Management, Liaoning University of Technology, Jinzhou, Liaoning 121001, China | E-mail: [email protected]
Correspondence:
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Corresponding author: College of Management, Liaoning University of Technology, Jinzhou, Liaoning 121001, China. E-mail: [email protected].
Abstract: In 2020, COVID-19 dragged down the economic development of various countries and the real estate industry was seriously affected. According to the meaning construction theory (SMT), this paper selects the real estate risk indicators to accurately measure the risk of Liaoning real estate. Based on the factor analysis method, the weight of real estate risk index in Liaoning province is calculated, which provides the basis for the further development of real estate risk in Liaoning province. According to the theory of spatial statistics, the real estate risk model of Liaoning province is constructed, and the real estate risk analysis of Liaoning province is completed. In order to accurately measure the effect of real estate risk spatial model in Liaoning province, the least square regression, spatial error regression, spatial error regression (FSEM) and spatial lag regression (FSLM) are compared. The regression effect of spatial lag regression model is the best. According to the results of the spatial model of real estate in Liaoning province, the spatial distribution of real estate in different cities in Liaoning province has a certain correlation, but the degree of connection is low. By using the spatial risk model of real estate in Liaoning province, the risk value of real estate in 2019 is low.
Keywords: Factor analysis, spatial statistics, real estate risk, combination method
