{"id":"W4414151078","doi":"10.3982/ecta19106","title":"Who Benefits From Surge Pricing?","year":2025,"lang":"en","type":"article","venue":"Econometrica","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Network of European Institutes for Advanced Study; Digital Technology Supercluster; Stanford Institute for Economic Policy Research; University of Pennsylvania; John S. and James L. Knight Foundation; Charles Warren Center for Studies in American History, Harvard University; Stanford University","keywords":"Boom; Welfare; Counterfactual thinking; Surge; Matching (statistics); Salient","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001465927,0.0001181039,0.0004415858,0.0004708129,0.0005220728,0.001854567,0.0004823058,0.001447738,0.018796],"category_scores_gemma":[0.008965367,0.000153698,0.0005251126,0.0005955987,0.001044898,0.00279836,0.0006865812,0.001309989,0.001674411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006376344,"about_ca_system_score_gemma":0.0009296808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001765736,"about_ca_topic_score_gemma":0.003361858,"domain_scores_codex":[0.9992002,0.0003217752,0.00002016541,0.00006889416,0.0001076475,0.0002814254],"domain_scores_gemma":[0.9958364,0.002197319,0.0007559024,0.0001694637,0.0002958505,0.0007451441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008805565,0.001148951,0.3506917,0.0004861504,0.0004627451,0.001243861,0.001725548,0.001749746,0.0009354539,0.05963897,0.1159346,0.4651018],"study_design_scores_gemma":[0.0003995852,0.0009640842,0.5022911,0.0012622,0.0007057489,0.003854234,0.02486811,0.01095606,0.001612621,0.3134367,0.1395272,0.0001222989],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7029827,0.01947748,0.002808397,0.1643878,0.000872945,0.00006644569,0.001324685,0.0001161406,0.1079633],"genre_scores_gemma":[0.9924375,0.001710107,0.000115638,0.003185858,0.0004258773,0.000007832351,0.00008466565,0.0000102487,0.002022274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.018796,"threshold_uncertainty_score":0.06287885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009121869285237104,"score_gpt":0.2019656107293726,"score_spread":0.1928437414441355,"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."}}