The Quiet Life of a Monopolist: The Efficiency Losses of Monopoly Reconsidered
Bibliographic record
Abstract
In this paper we study the efficiency losses of monopoly by analyzing a model where a firm's total costs of production decrease with the manager's effort to control costs. We consider two separate cases with regard to ownership and control: (1) the owner of the firm manages the firm himself; and (2) the owner hires a manager to operate the firm. We demonstrate that even in the case where the owner manages the firm, the level of effort exerted by the owner-manager of a monopoly is not first-best. Interestingly, the productive inefficiency of monopoly in this case may be caused by too much rather than too little effort. In such a situation, moreover, the separation of ownership and control can mitigate the productive inefficiency of monopoly, thus raising the intriguing possibility that managerial slack can actually improve the efficiency of monopoly equilibrium. To phrase our results in Hicks'(1935) terminology, a monopolist does not necessarily live a quiet life, and a quiet life is not necessarily a bad thing from the perspective of economic efficiency.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".