Bank Integration and the Market for Corporate Control: Evidence from Cross-State Acquisitions
Bibliographic record
Abstract
Using the staggered and reciprocal passage of interstate bank deregulation as an exogenous variation in the degree of bank integration, we investigate how and why bank integration influences the market for corporate control for nonfinancial firms. We posit that bank integration affects acquisitions either through reducing the information asymmetry between acquirers and targets or through increasing credit supply. Our evidence is more consistent with the former channel. Specifically, we document that (1) cross-state acquisitions are more likely to occur between reciprocally deregulated states, and (2) firms are more likely taken over by out-of-state acquirers after deregulation; this effect is stronger for a target who borrows from an out-of-state bank, whose local bank is acquired by an out-of-state bank, and who is informationally more opaque. Announcement returns for acquirers of out-of-state (particularly private) targets increase after deregulation, consistent with better identification of higher-valued targets by acquirers after deregulation. This paper was accepted by Tomasz Piskorski, finance.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".