How Does Market Competition Affect Shareholder Voting? Evidence from Branching Deregulation in the U.S. Banking Market
Bibliographic record
Abstract
Exploiting interstate branching deregulations during 1994–2005 as exogenous shocks to banking market competition, we examine the impact of increased market competition on shareholder voting in the U.S. banking industry. Voting is one of the primary mechanisms through which shareholders participate in corporate governance and “voice” their opinions to company management, yet little is known about how external market environments shape shareholder voting behavior. Using a difference-in-differences design, and a sample of 596 banks (17,783 bank-year proposals), we are the first to provide large-sample, systematic evidence that the intensification of market competition leads to an increase in rates of disapproval for management proposals. We further document that the relation between the two is more pronounced among states with higher degrees of deregulation and weaker levels of pre-deregulation competition. Overall, our findings are consistent with the notion that increased competition among U.S. banks induces more shareholders to vote against management proposals.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".