Investing in Influence: Investors, Portfolio Firms, and Political Giving
Bibliographic record
Abstract
Institutional ownership of U.S. corporations has increased ten-fold since 1950.We examine whether these new concentrated owners influence portfolio firms' political activities, as a window into the larger question of whether institutional investors can wield their control to extract benefits from portfolio firms.We find that after the acquisition of a large stake, a firm's political action committee (PAC) giving mirrors more closely that of the acquiring investment management company (in our preferred specification, a 31 percent increase in comovement).This pattern is observed for acquisitions driven by new index inclusions, which suggests that our findings result from a causal effect of acquisitions rather than other correlated shifts in political agendas.We argue that investors drive the convergence in giving -the effects are driven by more "partisan" investors, and we show that firms shift their giving more around acquisitions than investors do.Overall, our findings suggest that corporations' political business strategies are likely dictated by broader considerations than simple profit, and modeling corporate influence should take into account how corporations are governed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".