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Debt Structure

2020· article· en· W4248554024 on OpenAlex
Paolo Colla, Filippo Ippolito, Kai Li

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Financial Economics · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaBAFFI CAREFIN
KeywordsCapital structureDebt levels and flowsDebtInternal debtDebt-to-GDP ratioRecourse debtSenior debtDebt ratioBusinessExternal debtMonetary economicsEquity valueFinancial systemEconomicsFinancial economicsFinance

Abstract

fetched live from OpenAlex

We review the literature on debt structure, which is a central element in a firm's capital structure. We first survey both theoretical and empirical research pertaining to debt characteristics—maturity and priority—and debt types—bank loans, corporate bonds, credit lines, commercial paper, and capital leases. We then present comprehensive empirical evidence on public US firms’ debt structure over the period 2002–2018, highlighting that more than three-quarters of US firms concentrate their borrowing in one debt type, and offer some suggestive explanations for the observed pattern. Finally, we discuss directions for future research, including a better understanding of debt structure choices by non-US firms and by private firms, the cross-sectional and temporal variations in debt structure, the corporate policy implications of firms’ debt structure choices, and the interaction between types of assets and debt structure.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.533

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)0.0000.000

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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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