The Properties of Income Risk in Privately Held Businesses
Why this work is in the frame
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Bibliographic record
Abstract
Our paper represents the first attempt in the literature to estimate the properties of business income risk from privately held businesses in the US. Using a new, large, and confidential panel of US income tax returns for the period 1987-2009, we extensively document the empirical stylized facts about the evolution of various business income risk measures over time. We find that business income is much riskier than labor income, not only because of the probability of business exit, but also because of higher income fluctuations, conditional on no exit. We show that business income is less persistent, but is also characterized by higher probabilities of extreme upward transition, compared to labor income. Furthermore, the distribution of percent changes for business income is more dispersed than that for labor income, and it also indicates that business income faces substantially higher tail risks. Our results suggest that the high-income households are more likely to bear both the big positive and the big negative business income percent changes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it