Residential Segregation in General Equilibrium
Bibliographic record
Abstract
Black households in the United States with high levels of income and education (SES) typically face a stark tradeoff when deciding where to live. They can choose neighborhoods with high levels of public goods or a high proportion of blacks, but very few neighborhoods combine both, a fact we document clearly. In the face of this constraint, we conjecture that racial sorting may dramatically lower the consumption of local public goods by high-SES blacks. To shed light on this, we estimate a model of residential sorting using unusually detailed restricted Census microdata, then use the estimated preferences to simulate a counterfactual world in which racial factors play no role in household residential location decisions. Results from this exercise provide the first evidence that sorting on the basis of race gives rise to significant reductions in the consumption of local public goods by black and high-SES black households in particular. These consumption effects lead to significant losses of welfare and are likely to have important intergenerational implications.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".