{"id":"W3124213313","doi":"10.1017/s1365100519000890","title":"INTEREST RATES, MONEY, AND ECONOMIC ACTIVITY","year":2019,"lang":"en","type":"article","venue":"Macroeconomic Dynamics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Divisia monetary aggregates index; Divisia index; Economics; Broad money; Econometrics; Monetary policy; Shock (circulatory); Monetary economics; Vector autoregression; Industrial production; Granger causality; Autoregressive conditional heteroskedasticity; Macroeconomics; Central bank; Statistics; Mathematics; Quantitative easing; Energy (signal processing)","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":[0.001404236,0.0003880097,0.000390599,0.001545016,0.0003406868,0.00261396,0.0004394144,0.0009229273,0.003722563],"category_scores_gemma":[0.01648061,0.0001817517,0.0002326185,0.003655358,0.0007026614,0.002111462,0.0008239921,0.0009384235,0.0009277018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006725627,"about_ca_system_score_gemma":0.0003281225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002291868,"about_ca_topic_score_gemma":0.002059701,"domain_scores_codex":[0.9992298,0.0003753164,0.00007907029,0.0001256155,0.0001310905,0.0000590301],"domain_scores_gemma":[0.9918185,0.0037475,0.003350533,0.0003543684,0.0004437939,0.0002852154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005184324,0.0002770627,0.4564424,0.0005246612,0.0004109027,0.0009209274,0.001765873,0.02625217,0.001048253,0.3702827,0.009185925,0.1323707],"study_design_scores_gemma":[0.00006959177,0.0003495434,0.4809618,0.0005638722,0.0003053926,0.001587931,0.001707825,0.03483826,0.001495355,0.3813507,0.09659238,0.0001773835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8438712,0.03916256,0.02332882,0.009569496,0.0004752518,0.00006452566,0.003182339,0.000195545,0.08015024],"genre_scores_gemma":[0.9845617,0.006658418,0.002218568,0.0002591464,0.0003989989,0.00003621675,0.0008456503,0.00002249144,0.004998645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003722563,"threshold_uncertainty_score":0.01245314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03570398129720395,"score_gpt":0.2291995355919267,"score_spread":0.1934955542947228,"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."}}