Patent Collateral, Investor Commitment, and the Market for Venture Lending
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.
Bibliographic record
Abstract
The use of debt to finance risky entrepreneurial-firm projects is rife with informational and contracting problems. Nonetheless, we document widespread lending to startups in three innovation-intensive sectors and in early stages of development. At odds with claims that the secondary patent market is too illiquid to shape debt financing, we find that intensified patent trading increases the annual rate of startup lending, particularly for startups with more re- deployable (less firm-specific) patent assets. Exploiting differences in venture capital (VC) fundraising cycles and a negative capital-supply shock in early 2000, we also find that the credibility of VC commitments to refinance and grow fledgling companies is vital for such lending. Our study illuminates friction-reducing mechanisms in the market for venture lending, a surprisingly active but opaque arena for innovation financing, and tests central tenets of contract theory.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it