{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000411545,0.00005879931,0.0001019006,0.0004891577,0.00002886279,0.00001941955,0.0000691258,0.00003651387,0.0004529414],"category_scores_gemma":[0.00002615771,0.00006838953,0.00003120665,0.001332339,0.000007750611,0.00007122986,0.000004097632,0.0000604724,0.0000797468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004009232,"about_ca_system_score_gemma":0.00001175939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003391422,"about_ca_topic_score_gemma":0.00004131766,"domain_scores_codex":[0.999593,0.000002064685,0.0001855097,0.00009725716,0.0000269932,0.00009515371],"domain_scores_gemma":[0.999712,0.00008506999,0.0000117074,0.0001441246,0.00002200309,0.00002510914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008178952,0.0001595479,0.4676573,0.0001051797,0.0004787242,0.00000271457,0.0006999161,0.05574503,0.0002800587,0.1743639,0.06461249,0.2358869],"study_design_scores_gemma":[0.0001635149,0.000003117092,0.845724,0.000009442915,0.00000903064,3.836868e-8,0.0000209282,0.00201297,0.0005894967,0.0003990889,0.1509805,0.00008788641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8869541,0.0008293462,0.007417493,0.0003412605,0.0006088055,0.0001145968,0.0001335045,0.0003657703,0.1032351],"genre_scores_gemma":[0.9987795,0.00006238489,0.0003544859,0.000171786,0.0000211447,0.00001370117,0.00005278073,0.000006789081,0.0005373687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3780667,"threshold_uncertainty_score":0.495939,"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."}}