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Record W1903789114 · doi:10.1111/1911-3838.12049

The Convergence of <scp>IFRS</scp> and U.S. <scp>GAAP</scp>: Evidence from the <scp>SEC</scp>'s Removal of Form 20‐F Reconciliations

2015· article· en· W1903789114 on OpenAlexaffvenue
Stuart Mestelman, Emad Mohammad, Mohamed Shehata

Bibliographic record

VenueAccounting Perspectives · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsValuation (finance)Fair valueStock (firearms)AccountingBusinessGeography

Abstract

fetched live from OpenAlex

Abstract We use the SEC 's 2007 decision that eliminates the reconciliation requirement for foreign listed private issuers ( FPI s) reporting under IFRS as a natural experiment to examine whether IFRS and U.S. GAAP produce accounting information of comparable quality. We conduct statistical analyses using a sample of 563 firm‐year observations of FPI s during the period 2002 through 2008 for a panel of 70 FPI s that report under IFRS as our treatment group and 46 FPI s that report under U.S. GAAP as our control group. Using a stock‐valuation model and a difference‐in‐differences ( DD ) analysis of scaled residuals we examine whether the reconciliation values reported by IFRS FPI s prior to 2007 were value relevant and if the elimination of the reconciliation information in the post‐intervention period (2007 and 2008) has adversely affected the information available to investors to make stock‐valuation decisions. The results for the 2002 through 2006 period suggest that the reconciliation values for book value were value relevant. The DD analysis shows that while the residual‐value model incorporating reconciliation information produced comparable scaled stock price residuals for IFRS and U.S. GAAP FPI s prior to 2007, the removal of the reconciliation information did not lead to statistically significant increases in scaled stock price residuals for IFRS and U.S. GAAP FPI s.

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 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)0.104
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.104
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
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 head0.024
GPT teacher head0.238
Teacher spread0.215 · 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 teacher head, not a consensus.

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

Citations8
Published2015
Admission routes2
Has abstractyes

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