Agglomeration Spillovers and Wage and Housing Cost Gradients across the Urban Hierarchy
Bibliographic record
Abstract
The tyranny of distance in terms of its effect on median earnings and housing costs is examined for rural and urban U.S. counties. First, we develop a series of distance metrics for an area’s remoteness from multiple tiers of the urban hierarchy. Second, we consider geographical access of buyers and sellers through market-potential measures typical of those used in empirical studies of the New Economic Geography. The results reveal penalties of about 5 to 9% for median earnings and 12 to 17% for housing costs due to remoteness from the combined tiers of the urban hierarchy. Differences in market potential also influence factor prices, but these effects are generally smaller than those produced by urban hierarchy distances. Thus, it appears that empirical tests of New Economic Geography models need to consider sources of agglomeration spillovers beyond aggregate market potential. Visually depicting these results using maps illustrates that urban hierarchy distance penalties dominate in the western U.S., but the influence of market potential and urban hierarchy are about equal in the East.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".