{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02849066,0.001106398,0.003161565,0.00230103,0.001055016,0.003369478,0.004544386,0.004471956,0.006954098],"category_scores_gemma":[0.1470388,0.002968436,0.002392957,0.001830879,0.002920642,0.006112028,0.003441549,0.004629971,0.0007736009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117089,"about_ca_system_score_gemma":0.001714392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001839702,"about_ca_topic_score_gemma":0.002135766,"domain_scores_codex":[0.9873273,0.008641447,0.0005375181,0.001960201,0.0007443683,0.0007892333],"domain_scores_gemma":[0.7743853,0.2112795,0.004099146,0.007067082,0.002142404,0.001026609],"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":[0.0023464,0.0008111068,0.03498038,0.0007762795,0.001993697,0.0009030654,0.0007309297,0.2995971,0.004118531,0.4642356,0.005336545,0.1841704],"study_design_scores_gemma":[0.000161184,0.0001774912,0.003455877,0.00006871604,0.0001081837,0.0001287042,0.0000503883,0.8590145,0.001382352,0.1347729,0.0006210585,0.00005858069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03786261,0.0002906658,0.9601639,0.0003925639,0.0000683867,0.00005381558,0.0001072882,0.0002776972,0.0007832187],"genre_scores_gemma":[0.6927945,0.0004414503,0.2991635,0.0003592875,0.0003353742,0.0003501423,0.0007975121,0.0002405346,0.005517671],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02849066,"threshold_uncertainty_score":0.1506748,"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."}}