THE IMPACT OF CORPORATE GOVERNANCE PRACTICES ON POST-MERGER PERFORMANCE
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.
Bibliographic record
Abstract
The relation between the post-merger performance and corporate governance mechanism is examined using Linear regression model for a sample of US, Canada, EU-28 and Western European countries listed firms for the period from 2003 to 2012. We also examine as to whether the use of International Financial Reporting Standards (IFRS) improves corporate transparency, therefore, increasing financial reporting quality. Using a sample of banks from international countries, we present the following key findings: post-merger performance is significantly better common law in countries than code law in countries with better IFRS group banks during the post-merger performance. We also find that local GAAP reporting allows a more transparent assessment of financial performance on the basis of traditional indicators making it a superior tool for assessing potential acquisition targets. This study analysis changes in a country legal regulation as a measure of corporate governance and shows that these regulations play an important role in merger activity. Legal origins and owner-protection mechanisms are important in explaining the relationship between the quality of accounting standards and corporate governance practices following IFRS adoption. Overall, our empirical findings result consistent with Ciobanu (2015) find that merger and acquisition is influenced both the legal origin and accounting regulations.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it