Modeling the Dynamics of Growth in Master-Planned Communities

Christopher K. Allsup, Irene S. Gabashvili
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Abstract

This paper describes how a time-varying Markov model was used to forecast housing development at a master-planned community during a transition from high to low growth. Our approach draws on detailed historical data to model the dynamics of the market participants, producing results that are entirely data-driven and free of bias. While traditional time series forecasting methods often struggle to account for nonlinear regime changes in growth, our approach successfully captures the onset of buildout as well as external economic shocks, such as the 1990 and 2008-2011 recessions and the 2021 post-pandemic boom. This research serves as a valuable tool for urban planners, homeowner associations, and property stakeholders aiming to navigate the complexities of growth at master-planned communities during periods of both system stability and instability.
总体规划社区的增长动态建模
本文介绍了如何利用时变马尔可夫模型来预测一个总体规划社区从高速增长向低速增长过渡期间的住房开发情况。我们的方法利用了详细的历史数据来模拟市场参与者的动态变化,得出的结果完全由数据驱动,没有任何偏差。传统的时间序列预测方法往往难以解释增长中的非线性制度变化,而我们的方法成功地捕捉到了增长的开始以及外部经济冲击,如 1990 年和 2008-2011 年的经济衰退以及 2021 年大流行后的经济繁荣。这项研究为城市规划者、房主协会和房地产利益相关者提供了一个宝贵的工具,帮助他们在系统稳定和不稳定时期驾驭总体规划社区增长的复杂性。
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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