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Record W3123578579 · doi:10.1002/mde.2924

Market value, market share, and mergers: Evidence from a panel of U.S. firms

2018· article· en· W3123578579 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueManagerial and Decision Economics · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of WaterlooWestern University
FundersUniversity of GuelphDuke Energy
KeywordsEndogeneityMarket share analysisStock marketMarket valuePanel dataMarket shareBusinessShareholder valueShareholderStock dilutionMarket value addedEnterprise valueValue (mathematics)Monetary economicsEconomicsMarket microstructureRestricted stockFinanceEconometricsCorporate governanceOrder (exchange)

Abstract

fetched live from OpenAlex

Improving shareholder value has often been cited as a merger determinant. Because mergers create larger firms and less competition, they may increase shareholder value through higher market share and stock‐market value. We investigate merger impacts on firms' stock‐market value and market share. We construct panel data from 4 different data sources on public merging and non‐merging U.S. manufacturing firms for 1980–2003. Instrumental variables and factors such as R&D, patents, and citations control for endogeneity. We find that mergers are positively correlated with stock‐market value and market share.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.219
Teacher spread0.187 · 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