Impact of IFRS Convergence in India: An Evidence from First-Time Adoption of Indian Accounting Standards
Bibliographic record
Abstract
The aim of this paper is to examine the impact of legal creation of audit committees on financial firm performance. Precisely, we examine the impact of the establishment of audit committee, following the enactment of Ordinance No. 2008-1278, on financial firm market performance. Moreover, we investigate whether the audit committee characteristics such as independence of the members of the audit committees, the size; the accounting and financial expertise of the committee members as well as the frequency of audit committee meetings determine financial performance.We choose two measures for performance namely ROE and ROA. We conduct a panel study for a sample of 100 French companies listed on the Paris Stock Exchange from 2007 to 2015.The results show that the appearance of a legal text pushes the establishment of the committee but has no significant effect on the company's performance. This can be explained by the strong voluntary adoption of the audit committee following the publication of the Viénot Reports (Saada, 1998).
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How this classification was reachedexpand
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".