Executive compensation: A comparison between Canadian CEOs and their American counterparts
Bibliographic record
Abstract
While many researchers are still unsure as to why CEOs in the United States on average are compensated the highest on the global scale, this paper attempts to bridge the gap to this confusion by conducting a thorough analysis through the application of primary and secondary sources. The findings provided in this research are intended to lay the foundations to an underdeveloped total CEO compensation comparison between Canadian CEOs and American CEOs. This dissertation also investigates why there is a premium associated with US CEOs. An econometric model has been constructed to demonstrate some of the determinants influencing total CEO compensation, from which it can be understood that firm size is statistically significant. The longitudinal dataset included a final sample of 50 Canadian firms and 44 US firms, over the years 2009 to 2013 (See Appendix 9 and 10). An OLS baseline estimation was applied to test the model. Although, some of the initial results displayed significant relationships between firm performance, tenure, and board size with regards to total CEO compensation, the model was deemed to be relatively unfit at explaining the overall variation. This experiment was further extended using a cut-off rule of 2% from the upper and lower limits within each model to omit some of the outliers found in the dataset. Subsequently, OLS was conducted with robust standard errors to eliminate the presence of heteroskedasticity. Firm size still showed a positive and highly significant relationship under both samples. In addition, under both samples, firm performance was expressed by the return on assets and it illustrated a negative association with total CEO compensation. Although the financial crisis of 2007 and the adoption of a new Canadian accounting system were considered to be sound evidence for receiving results, which happened to be counter-intuitive to previous findings, this evidence may have be driven by the presence of an idiosyncratic sample. \n\nThis work remains to be the entire responsibility of the client. I am pleased for my dissertation to be shared and made available as an example of good practice.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".