{"id":"W4391620698","doi":"10.2139/ssrn.4718771","title":"Inference for Two-Stage Extremum Estimators","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Estimator; Extremum estimator; Asymptotic distribution; Approximate Bayesian computation; Invariant estimator; M-estimator; Mathematics; Monte Carlo method; Applied mathematics; Sampling distribution; Bootstrapping (finance); Instrumental variable; Inference; Mathematical optimization; Statistics; Computer science; Efficient estimator; Minimum-variance unbiased estimator; Econometrics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00139029,0.0001697075,0.0001479756,0.0002900521,0.0002614288,0.0007477927,0.0002419535,0.00004210064,0.0002256709],"category_scores_gemma":[0.0001144037,0.0001476214,0.0001510503,0.0003306129,0.00002560753,0.0009564925,0.00006295301,0.0008925231,0.0001175367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001824182,"about_ca_system_score_gemma":0.0005848964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001596805,"about_ca_topic_score_gemma":0.0007072221,"domain_scores_codex":[0.9978987,0.000008174503,0.0002420391,0.0002177624,0.0001800103,0.001453298],"domain_scores_gemma":[0.9995806,0.000111359,0.00008381889,0.0001224051,0.00008636613,0.00001550109],"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":[0.00005843713,0.00003393339,0.01362803,0.0001511668,0.0001077713,0.0000210057,0.00004069788,0.0000401938,0.001082128,0.6545615,0.0005604214,0.3297148],"study_design_scores_gemma":[0.001886201,0.00008316534,0.002350974,0.0003662037,0.0006728932,0.0002252294,0.001481227,0.08113253,0.00005737089,0.5262409,0.3843908,0.001112502],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6342563,0.01172597,0.3245397,0.002980416,0.003954533,0.0007371058,0.000008347952,0.0007411888,0.02105643],"genre_scores_gemma":[0.9952145,0.0001616048,0.00009884855,0.000170661,0.00110006,0.00001482016,0.000007069651,0.00003991073,0.003192568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3838304,"threshold_uncertainty_score":0.7210982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01931204702585941,"score_gpt":0.2869089270818682,"score_spread":0.2675968800560088,"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."}}