The âNYSE Premiumâ: Decomposing the âUS Premiumâ in compensation for CEOs of cross-listed firms
Bibliographic record
Abstract
That American CEOs earn significantly more than their counterparts in other countries has been widely documented. The current study reveals that the “US premium” might be more accurately labelled the “NYSE premium”. Focusing on the constituent firms of the S&P/TSX Composite Index (the largest Canadian firms of which almost half are cross-listed on US exchanges) and after controlling for firm size, industry, and other firm level characteristics, the average premium paid to CEOs of Canadian firms listed on the NYSE was approximately 100% while the CEOs of Canadian firms listed on the Nasdaq or AMEX received no premium, when compared to CEOs of firms listed only on the TSX. Over time, the average NYSE premium has decreased from 130% in 1998 to 90% in 2010, consistent with the convergence of CEO compensation to US standards. However, there was a Nasdaq premium of 48% in 1998 which had become a Nasdaq discount of 65% by 2010, coinciding with an mass exodus of Canadian firms from the Nasdaq.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".