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Record W1943645239 · doi:10.1111/1911-3846.12176

The Role of Similar Accounting Standards in Cross‐Border Mergers and Acquisitions

2015· article· en· W1943645239 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 · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMergers and acquisitionsAccountingBusinessInternational tradeInternational economicsEconomicsFinance

Abstract

fetched live from OpenAlex

Abstract This study investigates whether differences in accounting standards across countries create information costs that inhibit firms from investing in foreign markets. Using the frequency and dollar magnitude of cross‐border mergers and acquisitions (M&As) from 32 countries over the period 1998–2004, we find that the aggregate volume of M&A activity across country pairs is larger for pairs of countries with similar Generally Accepted Accounting Principles ( GAAP ), and that this increased volume of M&A activity is driven by target countries that also have strong enforcement. We also find that the 2005 mandatory adoption of International Financial Reporting Standard ( IFRS ) attracted more cross‐border M&As among IFRS ‐adopting countries, and that this increase in M&A activity within the IFRS countries is more pronounced for country pairs with low similarity in GAAP in the pre‐ IFRS adoption period. Overall, our results highlight the role of accounting standards and enforcement in shaping cross‐border M&A activity.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
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 head0.053
GPT teacher head0.391
Teacher spread0.339 · 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