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Record W7100138746

Federal Reserve Bank of Chicago Self-Employment as an Alternative to Unemployment

2011· article· en· W7100138746 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentWageWage growthLogitQuarter (Canadian coin)Odds
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.044
GPT teacher head0.303
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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