The "strength" of patent systems
Gaetan de Rassenfosse

TL;DR
This paper explores the multifaceted nature of patent system strength by analyzing statutory provisions, enforcement practices, and procedural friendliness, revealing systematic differences across jurisdictions that impact innovation and knowledge flow.
Contribution
It combines legal, administrative, and enforcement metrics to provide a comprehensive view of patent system strength, offering new insights into how regimes support innovation.
Findings
Significant variation in patent grant rates across jurisdictions.
Differences in procedural friendliness influence applicant success.
Enforcement effectiveness varies systematically among major patent offices.
Abstract
Patent systems vary widely in how rigorously they define and enforce inventors' rights. On one hand, formal statutes ("law on the books") set the scope of what can be patented and outline procedural safeguards. On the other hand, actual enforcement ("law in practice") determines whether those rights hold up in practice. To capture these dimensions, researchers have developed simple indices of legal provisions and more nuanced proxies for enforcement effectiveness, along with metrics of how applicant-friendly each office's procedures are. Comparative studies of "twin patents" -- identical inventions filed in multiple jurisdictions -- reveal systematic differences in grant rates and bar heights across major offices. By combining these approaches, we gain a multifaceted view of patent-system strength that balances statutory design, administrative practice, and actual enforcement. This…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIntellectual Property and Patents · Law, AI, and Intellectual Property · Pharmaceutical Economics and Policy
MethodsSparse Evolutionary Training
