The Effect of Fair Value Accounting on Firm Public Debt – Evidence from Business Combinations Under Common Control
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
We analyze the choice allowed to parent firms under IFRS of how to account for a business combination under common control (BCUCC), and provide evidence on the motivation to select fair values and the economic implications of this choice. A BCUCC is a merger of two firms owned by the same parent. Under IFRS, parent firms can use the acquisition method (fair values) to record the BCUCC or use assets’ historical cost. We show that parents are likely to choose fair values when they desire to increase the transparency of their financial reports and when they likely need to raise capital. Using propensity-score matching, we find that firms that used fair values are more likely to issue new public debt following the transaction. We also find that the cost of issuing new debt for these firms is 55 basis points lower than that of comparable firms that did not do BCUCCs. Our results suggest that using fair values in BCUCCs can increase transparency and lower firms’ cost of debt.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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