Managerial risk aversion and the structure of executive compensation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Research question/issue We examine how chief executive officers' (CEOs) innate risk aversion influences the size and structure of their compensation contracts. In so doing, we estimate managerial risk aversion based on the Big Five personality traits—openness, conscientiousness, extraversion, agreeableness, and neuroticism—inferred using IBM's Personality Insights service. Research findings/insights We provide evidence that executives' inherent risk aversion is related to their compensation structure. Contrary to agency theory predictions, we find that more risk‐averse CEOs receive more cash‐based and less equity‐based compensation but receive lower total compensation. This relationship is moderated by differences in firms' resource advantages. Theoretical/academic implications Despite the theoretical prediction that managerial risk aversion is a key factor determining the structure of executives' compensation contracts, there is limited empirical evidence on whether firms adjust the components of compensation based on CEOs' risk preferences. Our results help us better understand the interplay between CEO personality and executive compensation. Practitioner/policy implications This study offers important implications for organizations in that knowledge about executives' inherent risk aversion is important and relevant for designing effective compensation contracts.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it