Federal Reserve Bank of Chicago Self-Employment as an Alternative to Unemployment
Bibliographic record
Abstract
for their helpful comments and insights. The views expressed here are not necessarily those of the Federal Reserve Bank of Chicago or the Federal Reserve System. Data from the NLSY show that more than a quarter of all younger men experience some period of self-employment. Many of them return to wage work. This paper analyzes a simple model of job search and self-employment where self-employment provides an alternative source of income for unemployed workers. Self-employment is distinct from wage sector employment in two important respects. First, self-employment is a low-income, low-variation alternative to wage work. Second, once a worker enters self-employment, he loses eligibility to receive unemployment insurance benefits—at least until he returns to wage sector employment. The model suggests that flows into self-employment are countercyclical and flows out of self-employment are procyclical. Data from the NLSY for males at least 21 years of age are used to investigate how demographic and economic variables influence the decision to become self-employed. Fixed effects and random effects logit results indicate that young men are more likely to be self-employed when their wage work opportunities are more limited. Specifically, higher local unemployment rates lead workers to self-select into self-employment, as does past unemployment experience. The process is different for Whites and Nonwhites with education being irrelevant for White self-employed workers. In contrast, for Nonwhites higher education reduces the probability of entering self-employment. 2 I.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.145 | 0.035 |
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 source (direct Gemma or distilled Codex), 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".