A System Dynamics Approach for Study of Population Growth and the Residential Housing Market in the US
The US Consensus bureau estimated the total construction spending at 1,320,305 Million Dollars, in February 2020, with an increase of 1.1% since last February. The construction market is large, and risky. Prediction of the market behavior, for several years ahead, is needed in order to take strategic investment decision for long and expensive projects. The goal of this research is to study the relationship between population growth and the housing market. To that end, a system dynamics model is developed. System dynamics is a top-down approach that starts with the high-level behavior of a complex system to simulate the behavior of that system over time. The developed model simulates the housing market by matching the population growth with the housing demand in monthly time steps. As such, the parameters of the developed model include birth rate, life expectancy, immigration, emigration, and construction seasonality. Using these parameters, the model simulates the population size and demand for housing. For validation, the outputs of the model are compared with real-life data for the US. When complete, the model should assist market researchers in simulating the housing market. This research benefits large real estate developers, construction companies, governmental and financial agencies.
G. G. Ali et al., "A System Dynamics Approach for Study of Population Growth and the Residential Housing Market in the US," Procedia Computer Science, vol. 168, pp. 154 - 160, Elsevier B.V., May 2020.
The definitive version is available at https://doi.org/10.1016/j.procs.2020.02.281
Complex Adaptive Systems Conference (2019: Nov. 13-15, Malvern, PA)
Civil, Architectural and Environmental Engineering
Engineering Management and Systems Engineering
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2020 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
13 May 2020
Civil Engineering Commons, Operations Research, Systems Engineering and Industrial Engineering Commons