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Record W2191912818 · doi:10.3386/w25922

Employee Costs of Corporate Bankruptcy

2019· report· en· W2191912818 on OpenAlexafffund
John M. Graham, Hyunseob Kim, Si Li, Jiaping Qiu

Bibliographic record

VenueNational Bureau of Economic Research · 2019
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsMcMaster UniversityWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of CanadaKwanjeong Educational FoundationAlfred P. Sloan FoundationNational Science Foundation
KeywordsBankruptcyBusinessAccountingActuarial scienceFinance

Abstract

fetched live from OpenAlex

An employee's annual earnings fall by 10% the year her firm files for bankruptcy and fall by a cumulative present value of 67% over seven years.This effect is more pronounced in thin labor markets and among small firms that are ultimately liquidated.Compensating wage differentials for this "bankruptcy risk" are approximately 2.3% of firm value for a firm whose credit rating falls from AA to BBB, about the same magnitude as debt tax benefits.Thus, wage premia for expected costs of bankruptcy are of sufficient magnitude to be an important consideration in corporate capital structure decisions.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.413
GPT teacher head0.455
Teacher spread0.042 · 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; both teacher heads agree on what is shown here.

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

Citations55
Published2019
Admission routes2
Has abstractyes

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