XBRL Adoption and Bank Loan Contracting: Early Evidence
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
ABSTRACT: We examine how the adoption of the eXtensible Business Reporting Language (XBRL) for financial reporting impacts the pricing of bank loans. Using a sample of loans granted to U.S. borrowers from 2007–2013, we find that the adoption of XBRL is associated with a reduction in loan spreads. We further find that the reduction in loan spreads is greater for borrowers who have information that is inherently costlier to process. Results from a difference-in-differences specification along with other alternative research designs provide similar inferences. Subsequent to XBRL adoption, we further show that loan spreads are lower for firms that use more standardized XBRL tags and greater for those that use more extension elements. Overall, our results are consistent with the view that the XBRL mandate brings about an environment that enables lenders to gather and process information in a timelier manner and at a lower cost. JEL Classifications: M41; K22.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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