{"id":"W4285271103","doi":"10.1093/rcfs/cfac019","title":"Agency Conflicts and Investment: Evidence from a Structural Estimation","year":2022,"lang":"en","type":"article","venue":"The Review of Corporate Finance Studies","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Leverage (statistics); Shareholder; Agency cost; Business; Principal–agent problem; Investment (military); Agency (philosophy); Finance; Compensation (psychology); Economics; Monetary economics; Corporate governance","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":[0.01147159,0.0006687457,0.001334545,0.0012185,0.0009724189,0.003510501,0.001614008,0.001698718,0.008698218],"category_scores_gemma":[0.07913619,0.0008182239,0.001063173,0.002228875,0.001953111,0.002639484,0.0018787,0.003159846,0.000884616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001905308,"about_ca_system_score_gemma":0.001091335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01265419,"about_ca_topic_score_gemma":0.01092714,"domain_scores_codex":[0.9926201,0.004873835,0.0003704412,0.0009841417,0.0006363873,0.0005151017],"domain_scores_gemma":[0.7164285,0.2234847,0.04663901,0.007826706,0.003526306,0.002094844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00127456,0.001078563,0.6728715,0.0003452727,0.002727326,0.0008949972,0.001236504,0.1528088,0.0007792558,0.1017445,0.009625659,0.05461315],"study_design_scores_gemma":[0.0005272055,0.0006117505,0.2219755,0.0002122386,0.001271565,0.000339773,0.0008849123,0.5928968,0.001141067,0.1720354,0.007974528,0.000129329],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422418,0.003639115,0.03836247,0.004878017,0.0000611299,0.00008907617,0.0008851578,0.0001621476,0.009681136],"genre_scores_gemma":[0.996104,0.0005875956,0.00170406,0.0001242415,0.00004605861,0.00002323689,0.0004163833,0.00001799099,0.0009764434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01265419,"threshold_uncertainty_score":0.06066829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08762660139539576,"score_gpt":0.2852431333686392,"score_spread":0.1976165319732435,"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."}}