A Spatiotemporal Solution for the Simultaneous Sale Price and Time‐on‐the‐Market Problem
Bibliographic record
Abstract
There exists an important methodological challenge when dealing with sale price and time‐on‐the‐market variables because both variables are simultaneously determined and related to the motivation of the sellers and buyers. Exploiting the fact that transactions occur over space and time, we propose a two‐stage approach based on instrumental variables (IV) built from information collected from previous transactions. The unidirectional temporal property and the fact that other transactions are exogenous from the perspective of a single buyer or seller are exploited to evaluate the effect of the sale price on time‐on‐the‐market, and the effect of time‐on‐the‐market on the sale price. Based on 29,471 transactions occurring in the suburban neighborhood of Montréal (1992‐2000), the results suggest that, everything else being equal, houses staying longer on the market provide negative information to the market, which results in a lower final sale price, while the final sale price is negatively related to time‐on‐the‐market, indicating that houses of better quality (better amenities) stay less time on the market.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 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".