Does pre‐packed bankruptcy create value? An empirical study of postbankruptcy employment retention in The Netherlands
Bibliographic record
Abstract
Abstract In recent years, there has been growing interest in whether pre‐packed bankruptcy can be a mechanism through which firms facing imminent insolvency can preserve value. Although an extensive body of literature exists on “pre‐packs,” whether such techniques really preserve value remains ambiguous. By analysing bankruptcy proceedings filed with Dutch courts in the period 2012–2018 through the lenses of real options and debt overhang theory, we examined employment retention postbankruptcy as a consequence of the type of bankruptcy proceeding (pre‐packed bankruptcy and conventional bankruptcy) and the severity of prebankruptcy financial distress. The results show that in the Netherlands, a pre‐packed bankruptcy, when compared with a conventional bankruptcy proceeding, positively impacts employment retention rates after bankruptcy. The severity of financial distress before bankruptcy does not affect employment retention rates postbankruptcy. This implies that despite the amount of resource slack, the preservation of employee value is better served under a pre‐packed bankruptcy than a conventional bankruptcy proceeding. This finding is important for insolvency practice, as up to 22 June 2017, employee rights in the Netherlands (including redundancy) were not considered to be automatically transferred to the firm acquiring the bankrupt debtor's assets when a pre‐packed bankruptcy was applied. Implications for insolvency regulation and practice are discussed.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".