Regulatory Burden for Builders: Government's Effect on Housing Supply and Prices
Bibliographic record
Abstract
Having an affordable place to live is a key ingredient for a prosperous and healthy life. Unfortunately for many people, housing is becoming harder and harder to afford, with some markets in Canada priced out of reach for entire generations of middle-income citizens. Affordable rental housing is also very difficult to come by, especially for people towards the bottom of the income distribution. Canada's rental stock of housing is old and deteriorated, with very little development or maintenance of this class of housing over the past 30 years. Governments at all levels affect housing in a variety of ways, and governments and citizens alike should be concerned about the extra cost added to housing through regulatory burden as well as other policies that limit new housing supply. Municipal governments add to the cost of housing through fees and levies and limit supply through zoning laws. This creates a fiscal externality on upper levels of government, since housing becomes less affordable and social spending requirements increase for provincial and federal governments. Provincial governments also interfere with the housing market. Land transfer taxes make land more expensive, and rent controls discourage investment in new rental housing developments. Vacancy and foreign buyer taxes are implemented in order to try to add supply to the rental market and limit speculative demand. Carbon taxes make building supplies—especially the key building ingredient of concrete—more expensive.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".