{"id":"W3108228977","doi":"10.2139/ssrn.2915814","title":"Coordinating Expectations through Central Bank Projections","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of Victoria","funders":"","keywords":"Heuristics; Economics; Rational expectations; Output gap; Econometrics; Inflation targeting; Ex-ante; Inflation (cosmology); Credibility; Proxy (statistics); Central bank; Microfoundations; Monetary policy; Computer science; Monetary economics; Macroeconomics","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":[0.008846039,0.0008470632,0.0008882717,0.0009539757,0.0009527036,0.008082529,0.0008975301,0.001597411,0.007111294],"category_scores_gemma":[0.06066328,0.001123524,0.0003944963,0.001315083,0.0009508794,0.00588217,0.00249032,0.00298411,0.002296643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970526,"about_ca_system_score_gemma":0.004009335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005758201,"about_ca_topic_score_gemma":0.005209983,"domain_scores_codex":[0.9961364,0.002182154,0.0002041916,0.0005661733,0.0006368896,0.0002742382],"domain_scores_gemma":[0.9805201,0.01061552,0.002604125,0.00146522,0.003968293,0.0008268014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002763774,0.0002395965,0.02324188,0.0002407973,0.0002580766,0.0004217693,0.003248571,0.4135087,0.005579426,0.3355365,0.04870724,0.1662537],"study_design_scores_gemma":[0.0001393085,0.0001457869,0.005747402,0.00009937923,0.00008539626,0.00005770204,0.0009847509,0.645726,0.003627165,0.3283353,0.01493851,0.0001132992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3129198,0.001487948,0.5101754,0.02215253,0.001807479,0.0001675884,0.002032816,0.003455441,0.1458009],"genre_scores_gemma":[0.9795853,0.0002621725,0.01621794,0.0002569637,0.0001939059,0.00004608779,0.0003715564,0.0001785388,0.002887598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008846039,"threshold_uncertainty_score":0.04678291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06147337455790415,"score_gpt":0.2659721020975,"score_spread":0.2044987275395959,"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."}}