Share classes, families and asset purchases: Canadian evidence
Bibliographic record
Abstract
Purpose The purpose of this paper is to test if relative asset purchase values (RAPVs) differ between single- and dual-class purchasers (not) differentiated by family ownership for Canadian firms. Design/methodology/approach The paper uses multivariate regressions and 2SLS estimations of simultaneous equations models with both continuous and dichotomous endogenous variables. Data on share structures and family involvements are hand collected. Findings RAPVs for dual-class purchasers are significantly different (larger) than their single-class counterparts only for family-controlled samples. Larger RAPVs for dual-class purchases are associated with higher degrees of dual-class structures, higher family ownerships and with boards with no more than one family member. Research limitations/implications RAPV is important because of its common use as a primary determinant of the wealth effects of M&As, its use as an exchange-rate proxy in two-stage regressions used to determine the amount of abnormal returns attributable to short selling activity around M&A announcements, and its use as a channel for conveying information about deal complexity, seller’s bargaining power, additional monitoring benefits from purchase and/or greater challenges in incorporating a purchase into existing assets. Larger sample size would facilitate more differentiated examinations. Practical implications Findings imply that dual-class share structures assist family shareholders in elevating their control over corporate decisions involving asset purchases. Social implications This paper furthers the authors’ knowledge about the effects of agency issues on corporate decisions. Originality/value It provides an extension and robustness test of the US evidence for asset purchases by providing evidence for Canada given its greater preponderance of families as the ultimate controlling shareholders, restricted or subordinated voting shares issued and pyramidal structures.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".