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Trademarks and the cost of equity capital

2023· article· en· W4388085253 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Corporate Finance · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceFundamental Research Funds for the Central UniversitiesEuropean Accounting AssociationNational Natural Science Foundation of ChinaAccounting and Finance Association of Australia and New ZealandAdvanced Accelerator ApplicationsCanadian Academic Accounting AssociationAmerican Accounting Association
KeywordsBusinessEquity (law)Cost of capitalMonetary economicsEconomicsMicroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Employing a sample of 4655 U.S. public firms from 1993 to 2017, we document robust evidence that firms with more registered trademarks have a lower cost of equity. We further show that the equity financing cost is lower for firms with better-protected trademarks in difference-in-differences estimation based on the enactment of the Federal Trademark Dilution Act in 1996. In addition, our analysis reveals that the effect of trademarks on the cost of equity is achieved through the informational channel, the disciplinary channel, and the stabilizing cash flow channel. These results suggest that trademarks play an important role in alleviating the equity financing cost, thus clarifying the underlying mechanism that brand equity creates value.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.242
Teacher spread0.198 · 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