What Do Shareholders Want? Consumer Welfare and the Objective of the Firm
Bibliographic record
Abstract
Shareholders want a firm's objective function to place some weight on consumer welfare, motivated by both self-interested and altruistic motivations.Firms have a unique technology for improving consumer welfare: lowering inefficient price markups, which increases consumer welfare more than it lowers profits.Optimal pricing formulas can be adapted to account for shareholders' marginal rate of substitution between profits and consumer welfare.Calibrations from preference parameters show many shareholders should place non-trivial weights on consumer welfare.A survey experiment on a representative sample elicits how shareholders would vote on resolutions giving strategic guidance to firms on what objective to pursue.Only 7% would vote for pure profit maximization.The median individual is indifferent between $0.44 in profits or $1 in consumer surplus, with those owning stocks preferring a lower weight on consumer welfare than non-stockholders.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".