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Does the tax deductibility of interest affect financial reporting?

2025· article· en· W4412601344 on OpenAlexaff
Shawn X. Huang, Kenneth J. Klassen, Kaishu Wu

Bibliographic record

VenueJournal of Accounting and Public Policy · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAffect (linguistics)AccountingBusinessActuarial sciencePsychology

Abstract

fetched live from OpenAlex

Many countries have imposed tax policies that limit the deductibility of interest costs, creating a plausibly exogenous increase in the net cost of borrowing. The limits are based on financial accounting numbers, adding a new incentive into managers’ choices. Firms in these countries are also expected to rely less on debt financing and face weaker demand for conservative financial reporting from creditors as compared to firms in other countries. Tests employ a large sample of U.S. firms around the implementation of interest limits under the Tax Cuts and Jobs Act, and a second set of firms in OECD countries from 1985 to 2013 subjected to similar limitations. Exploiting these two settings and difference-in-differences research designs, we provide evidence that the adoption of these tax deductibility limits reduces conditional conservatism of firms’ financial reporting. Overall, our findings suggest that the tax rules affecting the deductibility of interest have important impacts on corporate financial reporting. Such changes can have unintended consequences for other decisions of interest to tax policy makers, such as investment choices documented by others.

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)0.008
metaresearch head score (Gemma)0.084
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 score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.084
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.291
Teacher spread0.253 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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