基于GM (1, 1)模型的房地产价格分析与预测——以上海市为例

Analysis and Forecast of Real Estate Prices Based on the GM (1, 1) Model—A Case Study of Shanghai

摘要: 房地产行业是我国经济的支柱产业，对地区经济发展和居民生活水平影响巨大，房地产价格变动因此成为一项重要的民生问题。本文以上海市为例，首先采用灰色关联度模型从供需层面、经济层面、政策层面和其他多个维度的层面中筛选房地产价格主要影响因素，随后基于其2010年~2021年的商品房住宅均价的相关数据，采用GM (1, 1)模型对其未来5年房地产价格进行预测分析。结果显示，上海市房地产价格受人均可支配收入、生产总值、人均GDP、金融存款余额量、住宅开发投资额等因素影响最为显著；同时，预测未来5年上海市房地产价格将持续上涨，年增幅约为9%。

Abstract: The real estate industry is a cornerstone of China’s economy, exerting a significant impact on regional economic development and residents’ living standards. Therefore, fluctuations in real estate prices have become an important issue affecting people’s livelihoods. Taking Shanghai as an example, this article first uses the grey relational model to select the main influencing factors of real estate prices from the perspectives of supply and demand, economy, policies, and other dimensions. Then, based on the related data of the average price of commercial residential buildings from 2010 to 2021, the GM (1, 1) model is employed to analyze and predict the future real estate prices for the next 5 years. The results indicate that real estate prices in Shanghai are significantly influenced by factors such as per capita disposable income, gross domestic product (GDP), per capita GDP, financial deposit balance, and residential development investment. Additionally, it is predicted that Shanghai’s real estate prices will continue to rise over the next 5 years, with an annual growth rate of approximately 9%.