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Record W2969900707 · doi:10.1111/jfir.12188

OPERATING LEVERAGE AND UNDERINVESTMENT

2019· article· en· W2969900707 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsDebtLeverage (statistics)Capital structureOperating leverageBankruptcyEquity (law)Moral hazardEarningsMonetary economicsBusinessEconomicsFinanceMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Using a contingent claims model, we examine the impacts of both operating leverage and financial leverage on a firm's investment decisions in the context of capacity expansion. Our model shows that quasi‐fixed operating costs could significantly mitigate the underinvestment problem for debt‐financed firms. The existing debt induces equity holders to delay equity‐financed expansion because the expanded earnings base will also benefit the debt holders by lowering the bankruptcy risk. The operating costs decrease this type of wealth transfer from equity holders to debt holders by magnifying the bankruptcy risk of the existing debt upon investment. By applying the Cox proportional hazard model on a large sample of publicly traded U.S. firms over 1966–2016, we offer empirical support for the theoretical predictions. The results are robust to various measures of operating leverage.

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.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.132
GPT teacher head0.373
Teacher spread0.241 · 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