{"id":"W3124126468","doi":"10.3386/w18533","title":"Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing","year":2012,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Energy Efficiency and Management","field":"Energy","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"California Energy Commission; Resources for the Future","keywords":"Nonlinear pricing; Electricity; Economics; Econometrics; Marginal cost; Electricity pricing; Business; Microeconomics; Electricity market; Financial economics; Engineering; Electrical engineering","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":[0.001259491,0.0001225241,0.0002500039,0.0002094112,0.000191303,0.0009323464,0.0003557159,0.0008712295,0.004283742],"category_scores_gemma":[0.01137911,0.0002120169,0.0002642326,0.0005636858,0.0006923975,0.001214907,0.0005007497,0.0007731962,0.0005265172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003003482,"about_ca_system_score_gemma":0.0001226262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003266395,"about_ca_topic_score_gemma":0.00279267,"domain_scores_codex":[0.9994712,0.0002384834,0.00002707686,0.0001073539,0.00009675166,0.00005919106],"domain_scores_gemma":[0.9922861,0.004840265,0.001408009,0.0007699553,0.0005450525,0.0001505922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001356893,0.0005194228,0.9231582,0.0001740504,0.0002245636,0.0001983463,0.002366414,0.002401584,0.00204227,0.01142021,0.004289255,0.0518488],"study_design_scores_gemma":[0.00009208285,0.0001834875,0.9657125,0.00003611116,0.0001208161,0.0001425571,0.004060521,0.00932942,0.0008215133,0.01507561,0.004383318,0.00004211761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860048,0.0002402614,0.001126932,0.001866755,0.000009734095,0.00001374213,0.0003936623,0.00001028684,0.01033383],"genre_scores_gemma":[0.9987842,0.0001856138,0.0001628429,0.0002873226,0.00001176942,0.000007211278,0.0001699968,0.000003174032,0.0003879304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004283742,"threshold_uncertainty_score":0.01433057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3689165027850592,"score_gpt":0.494182017951337,"score_spread":0.1252655151662779,"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."}}