{"id":"W3124493420","doi":"","title":"Fiscal Forecasts at the FOMC: Evidence from the Greenbooks","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Romer; Economics; Fiscal policy; Inflation (cosmology); Unemployment; Monetary policy; Monetary economics; Federal funds; Unemployment rate; Macroeconomics; Econometrics","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":[0.005267987,0.0003111517,0.0003417399,0.003859221,0.0008436249,0.002448591,0.0008594647,0.0009927654,0.008185994],"category_scores_gemma":[0.06414539,0.0003366508,0.0002263191,0.004717612,0.0008252642,0.00271768,0.001119972,0.001476561,0.003833265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001885381,"about_ca_system_score_gemma":0.001750108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1385503,"about_ca_topic_score_gemma":0.09083698,"domain_scores_codex":[0.9974464,0.0004862799,0.0001186826,0.0003543963,0.001399802,0.0001945625],"domain_scores_gemma":[0.9126042,0.03979325,0.02069787,0.006664739,0.01832849,0.001911478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001300726,0.0001925824,0.5957299,0.0002688771,0.000272134,0.0003558444,0.005392585,0.007598986,0.000211805,0.01820327,0.2121383,0.1583349],"study_design_scores_gemma":[0.0001255632,0.0001572189,0.7297519,0.0006664351,0.0001320859,0.00009628168,0.004143419,0.007070576,0.00142757,0.007071108,0.2492198,0.0001380553],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8109101,0.007074988,0.003067786,0.01810655,0.0007272129,0.00006217675,0.04677791,0.0005831167,0.1126902],"genre_scores_gemma":[0.9543662,0.004006306,0.001075389,0.001107754,0.0005535011,0.00002730377,0.0255806,0.0001969717,0.01308601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1385503,"threshold_uncertainty_score":0.2754877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1727361887988341,"score_gpt":0.3135343299244315,"score_spread":0.1407981411255974,"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."}}