Housing markets are inherently spatial, yet many existing models fail to capture this spatial dimension. Here we introduce a new graph-based approach for incorporating a spatial component in a large-scale urban housing agent-based model (ABM). The model explicitly captures several social and economic factors that influence the agents' decision-making behaviour (such as fear of missing out, their trend following aptitude, and the strength of their submarket outreach), and interprets these factors in spatial terms. The proposed model is calibrated and validated with the housing market data for the Greater Sydney region. The ABM simulation results not only include predictions for the overall market, but also produce area-specific forecasting at the level of local government areas within Sydney. In addition, the simulation results elucidate movement patterns across submarkets, in both spatial and homeownership terms, including renters, first-time home buyers, as well as local and overseas investors.

中文翻译：

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社会影响对澳大利亚房地产的影响：基于空间代理模型的市场预测

住房市场本质上是空间的，但许多现有模型未能捕捉到这个空间维度。在这里，我们介绍了一种新的基于图的方法，用于将空间组件纳入基于大规模城市住房代理的模型 (ABM)。该模型明确地捕捉了影响代理决策行为的几个社会和经济因素（例如对错失的恐惧、他们的趋势跟随能力以及他们的子市场外展的强度），并从空间角度解释这些因素。所提出的模型已使用大悉尼地区的住房市场数据进行校准和验证。ABM 模拟结果不仅包括对整个市场的预测，还包括在悉尼地方政府区域层面上的特定区域预测。此外，