{"id":"W2979571572","doi":"10.3386/w26367","title":"Subsidy Targeting with Market Power","year":2019,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; London School of Economics and Political Science; Georgia State University; Pennsylvania State University; University of Connecticut; University of Pennsylvania; Rice University; State University of New York; Agency for Healthcare Research and Quality; Yale University","keywords":"Subsidy; Market power; Economics; Business; Power (physics); Natural resource economics; Microeconomics; Market economy","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":[0.00203629,0.0005105715,0.0006744231,0.000630036,0.0005766419,0.002500456,0.000834702,0.001314407,0.0147937],"category_scores_gemma":[0.01598966,0.0003628153,0.0007481431,0.0007310911,0.00193234,0.003287983,0.00197588,0.001445791,0.0008870575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00199339,"about_ca_system_score_gemma":0.001356476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002509127,"about_ca_topic_score_gemma":0.001899637,"domain_scores_codex":[0.997583,0.000744195,0.00007739159,0.0004673575,0.0006147838,0.0005131423],"domain_scores_gemma":[0.9917501,0.004100241,0.00271044,0.0007297542,0.0004257053,0.0002837729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001472437,0.0003671802,0.02723378,0.0001573107,0.00009519588,0.0005537143,0.0003092664,0.06991658,0.003170986,0.8282105,0.005565918,0.06427243],"study_design_scores_gemma":[0.0002931513,0.00040295,0.02372143,0.00008058792,0.0001413982,0.000597326,0.0002743018,0.2019316,0.004654854,0.7454076,0.02244687,0.00004788508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5079312,0.0009599983,0.1888242,0.005547444,0.0001175247,0.000520685,0.0005698963,0.0005293064,0.2949997],"genre_scores_gemma":[0.9900351,0.0001300487,0.002879924,0.0003062202,0.000076436,0.00007989382,0.00003958869,0.00001711416,0.006435652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0147937,"threshold_uncertainty_score":0.04948986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3961120551639023,"score_gpt":0.4920196053016965,"score_spread":0.09590755013779417,"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."}}