The Costs of Issuing Private Versus Public Equity
Bibliographic record
Abstract
Canadian listed firms issue private offerings more often than public offerings. Yet the issuing cost of private investments in public equity (PIPEs) has neither been analyzed nor compared with the cost of conventional seasoned equity offerings (SEOs). We examine a sample of 2, 108 PIPEs and 1, 990 SEOs completed between 1993 and 2003, and show that, as expected, PIPEs are discounted more than SEOs, although the commissions paid to investment bankers are lower. When we control for size and other characteristics of the issuers, the difference between the total costs is 4%. Although this figure is significant, if the PIPE process allows firms to obtain financing four or six months earlier than via SEOs, the price gap may be economically justifiable. This finding may explain the rapid growth of the Canadian PIPE market. Les sociétés canadiennes inscrites en Bourse se financent de plus en plus fréquemment par placement privé, les PIPES. Le coût de ce type d'émission n'a jamais été comparé à celui des émissions publiques subséquentes (SEO). Nous analysons un échantillon de 2018 PIPES et 1990 émissions publiques, effectuées entre 1993 et 2003. Nous montrons que l'escompte est supérieur dans le cas des PIPEs, ce qui correspond aux attentes, mais les commissions payées aux courtiers sont inférieures. Lorsque la taille et les autres caractéristiques des émissions sont prises en compte, la différence entre les deux catégories d'émissions est de l'ordre de 4 %. Cet écart est statistiquement significatif. Toutefois, dans la mesure où l'émission privée peut permettre à l'entreprise d'obtenir les fonds six mois plus tôt que l'appel public, il peut être économiquement justifié de supporter ce coût supplémentaire. Cette situation pourrait expliquer la croissance des émissions privées.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 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".