The effect of house prices on fertility: evidence from Canada
Bibliographic record
Abstract
Abstract Persistent house price increases are a likely candidate for consideration in fertility decisions. Theoretically, higher housing prices will cause renters to desire fewer additional children, but home owners to desire more children if they already have sufficient housing and low substitution between children and other “goods”, and fewer children otherwise. In this paper, the authors combine longitudinal data from the Canadian Survey of Labour Income and Dynamics (SLID) and averaged housing price data from the Canadian Real Estate Association to estimate the effect of housing prices on fertility in a housing market that has historically been less volatile and more conservative than its American counterpart has. They ask whether changes in lagged housing price affect the marginal fertility of homeowner and renter women aged 18–45. They present results both excluding and including those who move outside their initial real estate board area, using initial area housing prices as an instrument in the latter case. For homeowners, but not renters, the authors predominantly find evidence that lagged housing prices have a positive effect on marginal fertility and possibly on completed fertility. These pro-natal effects are confined to non-movers.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".