An Investigation of the Housing Market and the Supply Modelling Process
Bibliographic record
Abstract
This research investigates the housing market and housing supply modelling processes. The main goal of this research is to study the residential housing provision mechanisms in depth to extend the housing supply component in the housing submodule of the Integrated Land use, Transportation, Environment (ILUTE) microsimulation systems. Following a comprehensive review on the current integrated urban models, this research examines the housing price variation from both the spatial and temporal dimensions, and revisits the current framework of the housing submodule of the ILUTE systems. To fill the research gap in the oversimplified supply side in most urban simulation models, the research develops a multi-phases supply modelling framework, which determines the available new housing supply at each location by month through three stages: (1) total number of monthly housing starts of the city, (2) monthly housing starts at each location, and (3) construction duration of each residential project. Each stage carries different characteristics and different models are built to capture the unique features of each phase. In Phase I, the monthly housing starts is modelled through an Autoregressive Distributed Lag (ARDL) model that captures the temporal variation of housing construction activities from a city level. In Phase II, the spatial distribution of housing supply is initially represented using logit choice models, incorporating experiments on both the location-conditional development choice model and project location choice model, and then an adjusted Multiple Discrete-Continuous Extreme Value (MDCEV) model is developed to determine the location and amount of housing supply simultaneously. In Phase III, housing completions are modelled through a Cox Proportional Hazard (CPH) model which determines the construction duration of residential projects in a survival analysis approach. Each phase is connected with another sequentially, and the output generated from one phase serves as the input for the model of the next phase. A unique feature of the multi-phases residential supply framework is that it integrates three crucial phases that cover and represent a whole cycle of housing development process, from initiation to completion. Empirical results based on the Greater Toronto and Hamilton Area (GTHA) indicate reasonable and satisfactory modelling performance. The research provides urban planners and modellers with a robust and comprehensive tool for understanding and predicting housing supply dynamics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".