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Record W4361206992 · doi:10.3390/jrfm16040213

The Impact of FASB Staff Position APB 14-1 on Corporate Financing: A Debt Contracting Perspective

2023· article· en· W4361206992 on OpenAlexaffvenue
Justin Yiqiang Jin, Kiridaran Kanagaretnam, Na Li

Bibliographic record

VenueJournal of risk and financial management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsYork UniversityMcMaster University
Fundersnot available
KeywordsBusinessIssuerLoanDebtLeverage (statistics)CashFinanceAccountingPosition (finance)Financial system

Abstract

fetched live from OpenAlex

Using a set of hand-collected data, we study the economic consequences of FASB Staff Position APB 14-1, which was adopted in 2008 and intended to increase reported interest expense and decrease reported leverage. First, we document that issuers are more likely to respond to APB 14-1 by reducing the outstanding amount of cash-settled convertible debt when they are more able to bear the cost of repurchase. Second, we explore the debt contracting explanations for issuers’ repurchase decisions. In particular, we focus on the contracting practice for GAAP changes and the inclusion of financial covenants related to interest coverage ratios. We find that issuers are less likely to repurchase the outstanding cash-settled convertibles when their bank loan contracts allow them to request a freeze on GAAP provisions to exclude mandatory GAAP changes in calculating accounting-based covenants. Further, when firms’ bank loan contracts contain financial covenants related to interest coverage ratios, issuers are more likely to repurchase outstanding cash-settled convertibles to avoid technical default due to the higher reported interest expense resulting from requirements under APB 14-1. These empirical results are consistent with the notion that firms do respond to mandatory GAAP changes when they are more able to afford the cost of such responses. Furthermore, debt contracting practices can help explain firms’ decisions to respond to mandatory GAAP changes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.014
GPT teacher head0.235
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

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