Financialization, and Macroeconomic Performance
Bibliographic record
Abstract
We empirically examine the relationship between U.S. output and household debt. To account for structural change due to financial liberalization, we divide the sample at the fourth quarter of 1982. We find structural differences between earlier and later business cycles for the U.S. household sector and its relation to the macroeconomy. In the regression analysis for pre-1982, we find no evidence that the household debt variables had any negative effect on output. However, we find some evidence that the household debt variables have negative effects on output for the post-1982 period. A formal structural break test provides evidence of a structural change in the relationship of U.S. output to household debt. Unit root tests for the separate samples show that none of the household variables possesses a unit root in the earlier period, yet all of them do in the later period, indicating fundamental differences between earlier and later periods in terms of the data generating process.
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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 | 0.001 | 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 | 0.000 | 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) | 0.005 | 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".