Abstract
This article studies the real estate batch evaluation model in Yuzhong District, Chongqing City. By analyzing 350 real second-hand housing listing data in October 2023 as sample data, a feature price model is established and a spatial econometric model is constructed based on the regression results to seek the most suitable model for batch evaluation of second-hand housing in Yuzhong District, Chongqing City. The results show that there is a significant spatial correlation between sample data, and both the spatial error model and spatial lag model in the spatial econometric model have improved the evaluation results of the traditional feature price model. However, the spatial lag model has the best performance in all indicators. Applying the spatial econometric model to real estate batch evaluation can improve the accuracy and fairness of the evaluation results.
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