Credit Conditions and Consumption, House Prices and Debt: What Makes Canada Different?
Bibliographic record
Abstract
There is widespread agreement that, in the United States, higher house prices raise consumption via collateral or possibly wealth effects. The presence of similar channels in Canada would have important implications for monetary policy transmission. We trace the impact of shifts in non-price household credit conditions through joint estimation of a system of error-correction equations for Canadian aggregate consumption, house prices and mortgage debt. We find strong evidence that, after controlling for income and household portfolios, easier credit conditions raise house prices, debt and consumption. However, unlike in the United States, housing collateral effects on consumption are absent. Given credit conditions, rising house prices increase the mortgage down-payment requirement and reduce consumption, although there is evidence for some attenuation of this effect over the 2000s. We also find that high and rising levels of both house prices and debt since the late-1990s can be mostly explained by movements in incomes, housing supply, mortgage interest rates and credit conditions, suggesting that the outlook for house prices and debt could depend mainly on the future paths of these variables.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".