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Record W2090879595 · doi:10.5430/afr.v3n2p77

Whether Sensible Business Tool or Deceptive Scheme to Conceal, the Special Purpose Entities Are here to Stay

2014· article· en· W2090879595 on OpenAlexvenueno aff
Sunita Ahlawat, Danielle Bellomo, Kyle Ropp

Bibliographic record

VenueAccounting and Finance Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)Financial crisisAccountingFinancial statementBusinessSample (material)EconomicsActuarial scienceLawPolitical scienceAudit

Abstract

fetched live from OpenAlex

This study examines whether the corporate use of Special Purpose Entities (hereafter, SPE) has changed in the wake of many well-publicized business failures and laws that followed them. In response to the Enron scandal, the Financial Accounting Standards Board (hereafter, FASB) released revised guidance in 2003 (49R) on consolidation procedures involving SPEs. Again, as the Financial Crisis unfolded in 2008, the FASB issued yet another standard, Statement No. 166, on the topic. On surface, having to consolidate SPEs may make their use less attractive to management. We discuss whether SPEs are an appropriate business practice or a deceptive tool of concealment as we test whether the use of reported SPEs by S&P 500 firms declined as a result of the Sarbanes Oxley Law (hereafter, SOX), and whether the use of SPE (or Variable Interest Entities, VIE’s) in the banking sector declined as a result of the Financial Credit Crisis of 2008, or the subsequent passage of the Dodd-Frank law. Using a random sample of 30 S&P 500 firms, we compare the average number of reported SPEs pre (2001) and post (2004) SOX. We use another sample of 30 financial institutions to compare average number of reported SPE/VIEs during pre/post SOX (2001 vs. 2004), pre/post financial crisis of 2008 (2006 vs. 2009), and pre-post Dodd Frank Law (2010 vs. 2012) periods. The results show that major business failures, credit crisis, and the subsequent laws have not curbed the appetite of the business community for SPEs.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.031
GPT teacher head0.285
Teacher spread0.254 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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