{"id":"W2283866133","doi":"","title":"Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data","year":2008,"lang":"en","type":"preprint","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Output gap; Taylor rule; Monetary policy; Inflation (cosmology); Economics; Econometrics; Autoregressive model; Interest rate; Taylor series; Real-time data; Bayesian probability; Inflation targeting; Macroeconomics; Central bank; Mathematics; Computer science; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01789677,0.0009228684,0.001321402,0.0007972156,0.0004552645,0.003488156,0.00118631,0.001299211,0.002097057],"category_scores_gemma":[0.09058728,0.000642039,0.001035053,0.001178089,0.0008760139,0.003115774,0.001222201,0.002389252,0.000583739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001781462,"about_ca_system_score_gemma":0.002520818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0114705,"about_ca_topic_score_gemma":0.006952698,"domain_scores_codex":[0.9908896,0.006404039,0.0004953868,0.0007768148,0.001221169,0.0002129865],"domain_scores_gemma":[0.9704235,0.02116826,0.003617066,0.001785509,0.002761102,0.0002444642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000472248,0.0002012171,0.01760817,0.0003743675,0.0004386226,0.000433644,0.0006595009,0.7929863,0.001507576,0.07057297,0.006360194,0.1083853],"study_design_scores_gemma":[0.000092935,0.0002265019,0.004840849,0.0002201439,0.0001082873,0.00005499966,0.0002459717,0.938388,0.00251295,0.04898316,0.004249704,0.00007639989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2160649,0.002237356,0.7568495,0.003422796,0.000469901,0.000431437,0.0008860925,0.0007591141,0.01887891],"genre_scores_gemma":[0.7902383,0.0008813016,0.2040523,0.0004221331,0.0001414619,0.0003135341,0.0007620802,0.0001431544,0.003045698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01789677,"threshold_uncertainty_score":0.0946483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0803024772604769,"score_gpt":0.2591806040965045,"score_spread":0.1788781268360276,"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."}}