Arrested Development: Theory and Evidence of Supply-Side Speculation in the Housing Market
Bibliographic record
Abstract
JOB MARKET PAPER This paper incorporates speculation into the standard supply-and-demand frame-work used to analyze housing booms and busts. Speculation reverses the common intu-ition that elastic housing supply attenuates housing booms. Housing market frictions make land a more attractive speculative investment than housing. As a result, unde-veloped land both facilitates construction and intensifies the speculation that causes booms and busts in house prices. This insight explains the frequent housing booms and busts that coincide with high construction activity (e.g. Las Vegas, 2000-2010). These episodes are most likely to occur when a housing market nears but has not yet reached a long-run development constraint. Consistent with the recent U.S. housing experience, the model predicts higher price volatility in neighborhoods where housing is more easily rented. Land is an asset whose price volatility can increase with its float.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".