Spatio-Temporal Hedonic Price Model to Investigate the Dynamics of Housing Prices in Contexts of Urban Form and Transportation Services in Toronto
Bibliographic record
Abstract
A spatio-temporal hedonic price model is developed for the Greater Toronto area to examine the effects of urban configurations and proximity to transit services on housing price. A spatial Durbin panel model is utilized to account for both spatial and temporal autocorrelation. This model is shown to have advantages through its ability to reduce the number of explanatory variables required to obtain a strong fit with empirical data. Analysis is completed for the period of 1996 to 2017 and distinctions are made in housing stock between single-family houses, townhouses, and condominiums. It is shown that heterogeneities exist between the hedonic representations of each dwelling type and that separate models should be employed for each. In all cases, the average income of the community, its distance to the central business district (CBD), and population and employment density are found to be significant factors in the determination of price.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".