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Record W3013638899 · doi:10.1111/1911-3846.12611

Financial Reporting and Trade Credit: Evidence from Mandatory <scp>IFRS</scp> Adoption*

2020· article· en· W3013638899 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueContemporary Accounting Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
FundersHong Kong Polytechnic UniversityNational Natural Science Foundation of ChinaAccounting and Finance Association of Australia and New Zealand
KeywordsBusinessComparabilityTrade creditEnforcementInternational Financial Reporting StandardsMarket liquidityQuality (philosophy)AccountingCredit referenceFinanceFinancial systemCredit risk

Abstract

fetched live from OpenAlex

ABSTRACT We investigate the effect of mandatory IFRS adoption on trade credit. We document that firms in countries that adopt IFRS receive more trade credit from their suppliers, consistent with improved financial reporting quality and comparability playing a role in facilitating informal financing. This increase is larger for countries with a low level of societal trust, a poor pre‐IFRS‐adoption information environment, and stronger legal enforcement. These cross‐sectional results suggest that the conditions under which higher‐quality information is made publicly available affect suppliers' decisions to provide trade credit. This increase is also larger for firms with greater exposure to foreign markets, a finding that highlights the importance of more comparable international financial reporting standards in facilitating cross‐country trade credit. We also find that IFRS adoption has a stronger positive effect on trade credit for firms with greater liquidity needs. Finally, we find that firms in countries that adopt IFRS also extend more trade credit to their customers. Overall, our results support the notion that financial reporting can have a causal effect on trade credit.

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)0.003
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.004
Open science0.0010.001
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 head0.125
GPT teacher head0.304
Teacher spread0.179 · 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