{"id":"W3124441593","doi":"","title":"Identification of Technology Shocks in Structural VARs","year":2006,"lang":"en","type":"preprint","venue":"Toulouse Capitole Publications (University Toulouse 1 Capitole)","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Technology shock; Business cycle; Econometrics; Inflation (cosmology); Nominal interest rate; Economics; Aggregate (composite); Identification (biology); Shock (circulatory); Monetary policy; Macroeconomics; Real interest rate; Dynamic stochastic general equilibrium","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006307012,0.0005879684,0.00129635,0.004811874,0.0002712331,0.0001706752,0.001926231,0.00117843,0.0004908611],"category_scores_gemma":[0.0001607112,0.0008831505,0.0004333837,0.001405144,0.000408216,0.000838995,0.0008542532,0.001118994,0.0004229974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075801,"about_ca_system_score_gemma":0.0002176212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01007595,"about_ca_topic_score_gemma":0.001350877,"domain_scores_codex":[0.9958029,0.00007217435,0.001753124,0.001440977,0.0001197614,0.0008110575],"domain_scores_gemma":[0.995172,0.00007675318,0.00211168,0.002278131,0.0001523314,0.0002091379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001589305,0.001231171,0.300539,0.0008747514,0.0008859414,0.00004995907,0.007010374,0.07264425,0.0003847973,0.5827559,0.0294219,0.00404301],"study_design_scores_gemma":[0.005143236,0.0002029041,0.4908786,0.0002572556,0.0002953412,0.00008179811,0.003163932,0.187319,0.001145096,0.2497564,0.05710403,0.004652502],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820318,0.001576938,0.001988461,0.003994261,0.0008092357,0.0009407341,0.002680843,0.0003191382,0.005658624],"genre_scores_gemma":[0.9921632,0.0004060359,0.001203053,0.00006803311,0.0001900608,0.00003122203,0.000775454,0.0000819128,0.005080995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3329995,"threshold_uncertainty_score":0.9993619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805928680590921,"score_gpt":0.211760322325334,"score_spread":0.1837010355194248,"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."}}