The information advantage of forthcoming patents on debt financing
Notice bibliographique
Résumé
Purpose The United States Patent and Trademark Office (USPTO) issues a notice of allowance (NOA) prior to a patent being granted, which serves to notify firms of forthcoming patents. An NOA could also serve as a positive signal. Credit rating agencies (CRAs) are exempt from regulation fair disclosure. Firms can disclose credible patent information to CRAs with minimal proprietary costs. When firms seek to fund their innovative activities through corporate bonds, they may benefit from disclosing their forthcoming patents to CRAs. This study focuses on CRAs' ex ante information advantage and examines the impact of private information on borrowers' initial credit rating and the cost of debt. Design/methodology/approach This paper studies how NOAs affect credit ratings and borrowing costs in the corporate bond market. We find that firms with forthcoming patents tend to receive better credit ratings and exhibit a lower cost of debt. Moreover, this informational advantage persists when considering the subsequent economic impact of the patents. Further subsample analyses show that the information advantage of forthcoming patents is more pronounced during non-crisis periods and for investment-grade bonds and bonds issued by large firms, as they are more likely to have a lower cost of debt even after controlling for the credit ratings. Our findings are robust for both the propensity score matching approach and the entropy balancing method. Findings We find that issuing firms with forthcoming patents tend to receive better credit ratings and exhibit a lower cost of debt. This informational advantage is retained even after accounting for the subsequent economic impact of the patents. Further subsample analyses show that the information advantage of forthcoming patents is more pronounced during non-crisis periods and for investment grade bonds and bonds issued by large firms as they are more likely to have a lower cost of debt even after controlling for the credit ratings. Our findings are robust for a propensity score matched approach and the entropy balancing method. Research limitations/implications Our study has some limitations. Our results depend on the data we have for NOA disclosures. There may be hidden factors that affect both patenting and bond issuance that we cannot observe. Our analysis is limited to U.S. firms, so the results may not be applicable in other countries with different regulations or market conditions. We also focus only on NOAs; however, other kinds of private information could matter. Future studies could examine international settings, consider other types of intangible assets or investigate how changes in regulation or CRA practices impact the use of private information in debt markets. Practical implications Our research identifies a gap in the literature concerning the role of NOAs in public debt issuance, providing a comprehensive analysis of how these patents affect credit ratings and borrowing costs – a dimension previously lacking in the existing literature. For managers, this implies a practical pathway to reducing capital costs by sharing innovation milestones with rating agencies. Investors can better interpret bond market signals by understanding when and how private information reaches CRAs. For policymakers, our work highlights the importance of transparency and the potential consequences of regulatory exemptions for CRAs with regard to selective information access. Social implications Our findings add to existing theories on information asymmetry and signaling by demonstrating that CRAs play a central role in bringing private information about innovation into the public bond market. By highlighting this process, our study connects research on rating agencies, innovation and bond pricing and shows how sharing selective information with rating agencies can have a direct impact on a firm's ability to raise capital and the terms it receives. Originality/value We provide new empirical evidence that in the corporate bond market, forthcoming patents can improve credit ratings, which in turn reduces the cost of debt financing at the time of bond issuance. Our study identifies a gap in the literature concerning the role of NOA in public debt issuance, providing a comprehensive analysis of how these patents affect credit ratings and borrowing costs – a dimension previously lacking in the existing literature. For practitioners, our findings suggest that strategically disclosing forthcoming patents to CRAs can be a valuable tool for firms seeking to optimize bond issuance conditions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».