{"id":"W2909382053","doi":"10.2139/ssrn.3212867","title":"CEO Compensation and Real Estate Prices: Pay for Luck or Pay for Action?","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Luck; Executive compensation; Compensation (psychology); Real estate; Action (physics); Business; Economics; Monetary economics; Financial economics; Microeconomics; Finance; Incentive; Psychology; Social psychology","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":[0.002573432,0.0002963691,0.0008143085,0.0008501415,0.0007138692,0.004475158,0.0007649084,0.003853957,0.02734361],"category_scores_gemma":[0.02869073,0.0003161167,0.0004712775,0.001165017,0.001496716,0.003543985,0.001038945,0.004190422,0.001746582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308933,"about_ca_system_score_gemma":0.001491507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008489954,"about_ca_topic_score_gemma":0.01570374,"domain_scores_codex":[0.9983404,0.0005020279,0.00009578354,0.0001697434,0.000320193,0.0005718446],"domain_scores_gemma":[0.9688201,0.01332659,0.01097093,0.0004882569,0.001429323,0.004964788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001175209,0.001202842,0.8717393,0.0001960041,0.000384556,0.000560024,0.001225316,0.001252066,0.0001881519,0.04250112,0.02859117,0.05098425],"study_design_scores_gemma":[0.000138679,0.0002342777,0.9332303,0.0003042926,0.0002703027,0.0004311572,0.006758127,0.003727501,0.0001681419,0.04015924,0.01448297,0.00009505407],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8436015,0.01774864,0.001487515,0.08636925,0.001518812,0.00004172547,0.0008645598,0.00003677606,0.04833109],"genre_scores_gemma":[0.9915855,0.0008444791,0.00008417345,0.0009916114,0.0006407485,0.000005802448,0.0001831112,0.00001073022,0.005653756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02734361,"threshold_uncertainty_score":0.09147346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03562891248892271,"score_gpt":0.2658710644280686,"score_spread":0.2302421519391459,"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."}}