Study on rent pricing of public housing in Qingdao

Shuang Chen, Junjun Hou, Dan Li
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Abstract

As a form of housing security provided by the government, the pricing of public rental housing has always been a concern. Research on the pricing of public rental housing can help deepen our understanding of the supply and demand relationship and rental formation mechanism in the housing market. Currently, research mainly adopts pricing methods based on cost, income, and market orientation. Therefore, this paper takes the relevant data that affects the rental prices of public rental housing in Qingdao as a basis, and uses multiple regression analysis and principal component analysis to construct a multiple linear regression model with the rental prices of public rental housing in Qingdao as the dependent variable and 8 indicators affecting rental prices as independent variables. Based on the model, the rental prices for the first quarter of 2023 are predicted, and the results are close to the actual results. Finally, based on the model and predicted values, combined with relevant policies of public rental housing in Qingdao, suggestions for pricing public rental housing are given. By applying the above model, we can comprehensively understand the factors that affect the pricing of public rental housing and provide some reference value for solving urban housing problems.
青岛公租房租金定价研究
作为政府提供的一种住房保障形式,公租房的定价问题一直备受关注。对公租房定价的研究有助于加深对住房市场供求关系和租金形成机制的认识。目前,研究主要采用基于成本、收入和市场导向的定价方法。因此,本文以影响青岛市公租房租金价格的相关数据为基础,采用多元回归分析法和主成分分析法,构建了以青岛市公租房租金价格为因变量,以影响租金价格的8个指标为自变量的多元线性回归模型。根据模型,对 2023 年第一季度的租金价格进行预测,结果与实际结果接近。最后,根据模型和预测值,结合青岛市公租房相关政策,给出公租房定价建议。通过运用上述模型,可以全面了解影响公租房定价的因素,为解决城市住房问题提供一定的参考价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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