{"id":"W4226388878","doi":"10.1017/asb.2021.36","title":"MEAN–VARIANCE INSURANCE DESIGN WITH COUNTERPARTY RISK AND INCENTIVE COMPATIBILITY","year":2021,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Indemnity; Actuarial science; Incentive compatibility; Incentive; Moral hazard; Insurance policy; Auto insurance risk selection; Economics; Econometrics; Business; Liability insurance; Microeconomics","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":[0.004530904,0.0007931771,0.002011513,0.0006636176,0.0004722504,0.001871288,0.001537342,0.002600781,0.004491778],"category_scores_gemma":[0.01153124,0.0009521822,0.0009531217,0.0004982152,0.001675004,0.002299839,0.001446813,0.00182768,0.0003376781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001539007,"about_ca_system_score_gemma":0.001274085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007061061,"about_ca_topic_score_gemma":0.0004072496,"domain_scores_codex":[0.997242,0.001411915,0.0001032673,0.0005111836,0.0004477459,0.0002838716],"domain_scores_gemma":[0.99521,0.003046131,0.0006364725,0.0003825109,0.0003771273,0.000347713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003520605,0.0002297687,0.001295606,0.0001912539,0.0001020677,0.0003175994,0.0001778577,0.3467547,0.007113704,0.6147454,0.0017088,0.02701122],"study_design_scores_gemma":[0.0001104891,0.0002449458,0.00059302,0.00003166561,0.00003427234,0.0001168598,0.00002215592,0.7620741,0.0008593702,0.234957,0.0009215639,0.0000345495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1205889,0.0006843735,0.8629972,0.001786679,0.00009817592,0.0001129866,0.0001183911,0.0001742364,0.01343915],"genre_scores_gemma":[0.9583703,0.0002387904,0.03567327,0.0001029322,0.00009064861,0.00009637061,0.00003809404,0.00002979682,0.005359862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004530904,"threshold_uncertainty_score":0.02396202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0190185002477444,"score_gpt":0.1931729647853969,"score_spread":0.1741544645376525,"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."}}