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Record W2972595894 · doi:10.1287/mnsc.2019.3329

Bank Integration and the Market for Corporate Control: Evidence from Cross-State Acquisitions

2020· article· en· W2972595894 on OpenAlexaff
Kose John, Qianru Qi, Jing Wang

Bibliographic record

VenueManagement Science · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDeregulationMarket for corporate controlBusinessFinancial systemControl (management)Information asymmetryMonetary economicsReciprocalState (computer science)Mergers and acquisitionsKeiretsuBank regulationEconomicsFinanceMarket economyCorporate governance

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.671
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.253
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2020
Admission routes1
Has abstractyes

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