{"id":"W3125244804","doi":"10.1016/j.jeconom.2019.02.006","title":"Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator","year":2019,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; Social Sciences and Humanities Research Council of Canada; Renmin University of China","keywords":"Mathematics; Estimator; Pointwise; Common value auction; Nonparametric statistics; Delta method; Applied mathematics; Inference; Econometrics; Statistics; Computer science; Mathematical analysis; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.05594825,0.001063792,0.00674422,0.003269784,0.001170432,0.003504389,0.004657541,0.003550783,0.004722366],"category_scores_gemma":[0.2021324,0.002048714,0.00385445,0.00282308,0.003227828,0.007825769,0.002022812,0.004792326,0.0005660523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664453,"about_ca_system_score_gemma":0.00387515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01010212,"about_ca_topic_score_gemma":0.008704551,"domain_scores_codex":[0.9699574,0.02282265,0.001264639,0.003174745,0.001429509,0.001350994],"domain_scores_gemma":[0.7584561,0.2182477,0.003362901,0.0146037,0.004251985,0.001077706],"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":[0.001207369,0.0008506932,0.0272974,0.0005507962,0.002464995,0.0003315294,0.0007019729,0.2460323,0.001567806,0.537071,0.004903771,0.1770204],"study_design_scores_gemma":[0.0002565227,0.0003185191,0.003720255,0.00007817536,0.0002394362,0.0001995851,0.0001067629,0.8065239,0.0008800778,0.1857132,0.001884625,0.00007894237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0561214,0.001015277,0.9405386,0.0005836053,0.000125899,0.00008082271,0.00009291119,0.0002445317,0.001196957],"genre_scores_gemma":[0.6895235,0.0008912962,0.3043505,0.0002762442,0.0002807612,0.0001645033,0.0004355714,0.0001532629,0.003924263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05594825,"threshold_uncertainty_score":0.2958861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.214858324845076,"score_gpt":0.3601009489431205,"score_spread":0.1452426240980445,"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."}}