Ownership Structure, Agency Problems, and Auditor Choice: Evidence from Western European Firms
Bibliographic record
Abstract
Recent evidence on the ownership structures of Western European firms reveals significant divergence between the ultimate ownership and control rights of the largest controlling shareholder, implying that their conflicting interests with minority shareholders is the main agency problem besetting firms in these countries. Prior research also implies that credible financial reporting constrains controlling shareholders’ opportunism by enabling minority investors to identify any diversion of corporate resources. In this paper, we examine whether external monitoring by a high-quality auditor helps reduce the agency problems embedded in the ultimate ownership structures of Western European firms. Consistent with the incentive alignment effect to maximize firm value to the benefit of all shareholders, we find strong, robust evidence that the demand for a Big Four auditor subsides with the ownership rights of the controlling shareholder. In contrast to recent research on East Asian firms, we find no evidence that the divergence between ownership and control rights affects auditor choice. However, we find that both firms with multiple large shareholders beyond the controlling owner and family-controlled firms are associated with lower demand for Big Four auditors. Collectively, our research suggests that Western European firms rely on superior external monitoring from Big Four auditors to moderate the agency problems evident in their ownership structures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".