{"id":"W3212254896","doi":"10.1016/j.iref.2021.11.003","title":"Determinants of Return-maximizing CEO Equity & Cash compensation","year":2021,"lang":"en","type":"article","venue":"International Review of Economics & Finance","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Incentive; Executive compensation; Enterprise value; Equity risk; Return on equity; Equity (law); Business; Economics; Principal–agent problem; Equity value; Monetary economics; Microeconomics; Finance; Valuation (finance); Corporate governance; Profitability index","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001492289,0.000157843,0.0002407078,0.000548833,0.0003621519,0.001705862,0.0003739556,0.0008991063,0.009839291],"category_scores_gemma":[0.01262754,0.0001878839,0.0002244771,0.0004382239,0.0004897561,0.0005610352,0.0003944134,0.001104225,0.001053634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006514243,"about_ca_system_score_gemma":0.001072034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004680556,"about_ca_topic_score_gemma":0.006610431,"domain_scores_codex":[0.9994919,0.0001612408,0.00003064218,0.00006792237,0.00007231823,0.0001759981],"domain_scores_gemma":[0.9751652,0.01343767,0.007390158,0.000580287,0.0009010665,0.002525625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001715636,0.0002837947,0.9819008,0.00001927313,0.00005732741,0.0001193694,0.0001385948,0.001874009,0.0004731416,0.003414579,0.001380368,0.0101671],"study_design_scores_gemma":[0.000011951,0.00006565852,0.991819,0.00001428405,0.00003450665,0.00009601374,0.0003053153,0.003162492,0.0003280541,0.003084437,0.001070579,0.000007653003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993013,0.0006042566,0.0004432014,0.001250265,0.000009503897,0.00001113166,0.0002300926,0.00001839852,0.004420214],"genre_scores_gemma":[0.9991513,0.00006410986,0.0000461255,0.00002027478,0.00001162492,0.000001580214,0.00004520722,0.000002188969,0.0006574752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009839291,"threshold_uncertainty_score":0.03291571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05335372641611036,"score_gpt":0.2924661243972424,"score_spread":0.239112397981132,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}