The Multijurisdictional Disclosure System and Value of Equity Offerings
Bibliographic record
Abstract
Abstract The Canada and US multijurisdictional disclosure system (MJDS) implemented in 1991 lowered the indirect barriers for investors and issuers by easing reporting and disclosure requirements for cross‐border issues. This paper examines the impact of the MJDS and related regulatory changes on Canada–US equity market segmentation using a sample of Canadian seasoned equity offerings in the 1991–1998 period. We find that the number of cross‐border issues by Canadian firms increased, and the typical negative stock price reaction that accompanies seasoned equity issues declined over time, supporting increased integration between the two markets after the MJDS. We also document that cross‐border issues experience about 1.4 per cent lower negative stock price reaction compared with domestic issues, consistent with Canada–US market segmentation. We find mixed support for Merton's (1987) investor recognition hypothesis. While Canadian firms cross‐listed in the US experience a less adverse price reaction to their cross‐border offerings compared with their non‐US‐listed peers, there is no significant difference between the two groups in the case of purely domestic issues.
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 | 0.001 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".