Value of Transit as Reflected in U.S. Single-Family Home Premiums
Bibliographic record
Abstract
Although transit accessibility premiums have been rigorously studied at the local and regional levels for more than 40 years, drawing conclusions about premiums on a national scale requires a meta-analysis. Estimating effect size is a primary purpose of a meta-analysis. Effect size was calculated in 2007 by using pre-2003 studies but has not been studied since. This study sought to fill gaps in the literature by conducting a regression analysis and a thorough meta-analysis that reviewed 114 studies published from 1976 to 2014. Of 114 U.S. and Canadian single-family studies, a sample of 45 single-family studies was selected for further analysis. Compared with the previous meta-analysis, the current analysis found that, overall, U.S. and Canadian studies reported lower premiums on average for single-family houses. The average single-family home premium of 2.3% was significantly lower than the 4.2% premium calculated by the previous meta-analysis. It was found that reported transit premiums were decreasing over time as more variables, such as walkability of station areas, were statistically controlled. It was also found that compact regions with greater accessibility via transit produced higher transit premiums and transit premiums were neutral with respect to technology (light versus heavy rail) once regional compactness was controlled for. These findings suggest that to get the most out of transit investments, planners and public officials must make an effort to create compact regional development patterns and that single-family housing may not be the best use in areas close to transit.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.014 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".