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Record W4401686605 · doi:10.3390/jrfm17080367

The Impact of Corporate Reputation on Cost of Debt: A Panel Data Analysis of Indian Listed Firms

2024· article· en· W4401686605 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.

venuePublished in a venue whose home country is Canada.
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 risk and financial management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Identity and Reputation
Canadian institutionsnot available
Fundersnot available
KeywordsReputationWeighted average cost of capitalBusinessDebtPanel dataFinanceDebt ratioCost of capitalAccountingEconomicsFinancial capitalProfit (economics)MicroeconomicsCapital formation

Abstract

fetched live from OpenAlex

The study analyses the impact of financial reputation on the cost of debt financing for Indian companies. In doing so, panel regression analysis is performed using firm-specific data on 395 Indian listed firms covering 2002–2017. The paper uses market capitalization as a benchmark of financial reputation. For robustness check, excess of market value over book value is also used as a proxy of financial reputation. The study found that the reputation of a firm in financial markets plays a vital role in determining the cost of financing. The results provide evidence supporting a significant negative relationship between financial reputation and the cost of debt. The findings provide motivation for corporate managers to invest in reputation-building activities to reduce the cost of borrowing. The relevance of reputation in lowering the cost of debt capital has garnered limited attention, especially in emerging economies like India. This study is a preliminary attempt to link two strands of research in the Indian context: financial reputation and the cost of debt.

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 score0.856
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.039
GPT teacher head0.270
Teacher spread0.231 · 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