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Analyzing housing supply location choice: a comparative study of the modelling frameworks
1Department of Civil and Mineral Engineering, University of Toronto, 35 St George St, GB305, Toronto, ON, M5S 1A4, Canada. yyu.zhang@mail.utoronto.ca.
Scientific Reports
|January 16, 2024
Summary
This study compares two housing supply models for urban planning. While one model better predicts new housing locations, the other excels at explaining individual project choices, improving urban microsimulation systems.
Area of Science:
- Urban Planning and Simulation
- Geographic Information Systems
- Econometrics
Background:
- Housing supply is a critical factor in land use simulations within urban microsimulation systems.
- Urban simulation models have transitioned from static housing supply inputs to dynamic, agent-based approaches.
- Understanding the spatial distribution of new housing is essential for accurate urban planning.
Purpose of the Study:
- To predict the location of new housing supply.
- To compare two distinct modeling frameworks for housing supply distribution.
- To evaluate the effectiveness of different approaches in urban microsimulation.
Main Methods:
- Application of multinomial logit and nested logit models.
- Analysis of a Toronto empirical dataset on housing development.
- Comparison of location-choice versus development-choice modeling frameworks.
Main Results:
- The development-choice model demonstrated superior goodness-of-fit and prediction accuracy.
- The location-choice model provided better insights into individual project locational preferences.
- Key factors influencing housing supply distribution include project type, cost, housing price, sales volume, and population density.
Conclusions:
- Both modeling approaches offer valuable insights for urban planning and microsimulation.
- The findings contribute to the literature on housing modeling and urban microsimulation.
- The study informs the configuration of housing supply models in urban microsimulation systems.
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