Macroeconomic shocks and racial labor market differences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We investigate the effects of three structural macroeconomic shocks (monetary, demand, and supply) on the labor market outcomes of black and white Americans using a factor‐augmented vector autoregression (FAVAR) framework with 136 U.S. macroeconomic indicators from 1973 to 2017. Our results indicate that adverse macroeconomic shocks have differential effects on labor market outcomes for blacks and whites, hurting blacks disproportionately more than whites. Black Americans' labor market outcomes appear to be significantly more sensitive to macroeconomic shocks than are the outcomes for white Americans. Our findings indicate that business‐cycle costs are disproportionately borne by black Americans and that racial inequality in the labor market rises in recessions. The strongest effects occur in recessions caused by supply side disturbances. Our results suggest policymakers should take these heterogeneous effects into account when designing policy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it