Using Panel Data to Estimate Income Under‐Reporting by the Self‐Employed
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
Self‐employment income is believed to be understated in economic statistics but there is debate about the extent of under‐reporting. This paper refines the widely used method of Pissarides and Weber ( Journal of Public Economics , Vol. 39, No. 1 (1989), pp. 17–32) that relies on discrepancies between food shares and reported incomes. Our panel data approach disentangles under‐reporting from fluctuations in transitory income and gives a point estimate of the under‐reporting rate. Previous studies just give an interval estimate and also make the unlikely assumption that under‐reporting is independent of transitory income fluctuations. Panel data from K orea and R ussia are used to illustrate the method, and suggest that in both countries almost one‐quarter of the income of self‐employed households is not reported.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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