Personal Bankruptcy Law and Innovation around the World
Bibliographic record
Abstract
Because corporate limited liability protects the founder’s personal assets, creditors often require founders of new, small and risky firms to contract around limited liability by pledging their personal assets as collateral for loans to their firms. This makes personal bankruptcy law (PBL) relevant to corporate finance. We find that pro-debtor PBL reforms increase the number of patents filed, citations to those patents, and début patents by firms with no previous patents. These reforms also redistribute innovation across industries in closer alignment to its distribution in the U.S., which we take to approximate industry innovative potential. These effects are driven by firms without histories of high intensity patenting and are damped in countries that impose minimum capital requirements on new firms. Firms with largescale legacy technology may avoid radical innovations that devalue that technology. Consequently, new, initially small and risky firms often develop the disruptive innovations that contribute most to economic growth. Consistent with this, we also find pro-debtor PBL reforms increasing allocative investment efficiency. Our difference-in-differences regressions use patents and PBL reforms for 33 countries from 1990 to 2002, with subsequent years used to measure citations to patents in this period.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".