Application of A System Dynamic Model on U.S. Regional Real Estate Industry

This research strives to explore and simulate the dynamics of regional real estate markets within the United States using the system dynamics methodology. Building upon the original model by John Sterman, the study expands it by introducing new structures related to construction-in-progress, unit prices, alternative funds, and sales. The model undergoes calibration utilizing historical data from 1975 to 2021, with a focus on its capacity to simulate key parameters such as start rate, construction-in-progress rate, construction rate, and price. Although calibration fitness demonstrates a reliable match for trends, it exhibits limitations in representing dynamics over short time periods and seasonality. Utilizing the calibrated model, the study generates forecasts for future real estate market trends under three scenarios: baseline, standard growth, and elevated interest rate. The forecast results emphasize the influential role of space demand, the effect of interest rates on prices, and the reinforcing feedback loop of future prices. The study highlights potential avenues for model enhancement and establishes a foundation for subsequent research.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Zhang, Tianyi

Advisor dc:contributor.advisor

• Rahmandad, Hazhir

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/151843

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151843