{"id":"W3005889938","doi":"10.1016/j.chieco.2022.101825","title":"Monetary stimulus policy in China: The bank credit channel","year":2022,"lang":"en","type":"article","venue":"China Economic Review","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Economics; Monetary economics; Collateral; Monetary policy; Credit channel; Stimulus (psychology); Loan; China; Macroeconomics; Finance; Inflation targeting","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":[0.001539072,0.0003924264,0.0005828853,0.002044986,0.0008280997,0.002650763,0.0004029215,0.001013828,0.002275988],"category_scores_gemma":[0.001990008,0.0001504684,0.0002663872,0.003466463,0.001243578,0.00118877,0.0005755309,0.0008223663,0.000150847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004408897,"about_ca_system_score_gemma":0.01066752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05234531,"about_ca_topic_score_gemma":0.04836768,"domain_scores_codex":[0.9995909,0.00009579283,0.00003557291,0.0000470853,0.0001304813,0.0001001186],"domain_scores_gemma":[0.9990257,0.00023054,0.0002197138,0.00003766256,0.0003840197,0.0001022742],"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":[0.0007810181,0.0002159882,0.06772509,0.005471523,0.0005149835,0.001192529,0.001681734,0.01836803,0.003614963,0.4105254,0.1011951,0.3887136],"study_design_scores_gemma":[0.0005181018,0.0003431999,0.5776986,0.002170877,0.0008767495,0.0003488993,0.00179097,0.02045778,0.002619116,0.06238013,0.3306147,0.0001808707],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4640417,0.4016682,0.001421014,0.05679259,0.001759997,0.00008463768,0.001011663,0.0001161079,0.07310405],"genre_scores_gemma":[0.8908582,0.1002836,0.0002278068,0.001913363,0.001233066,0.00002400203,0.0001976365,0.00001188003,0.005250405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05234531,"threshold_uncertainty_score":0.1040813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02175478132617636,"score_gpt":0.2452732103394704,"score_spread":0.223518429013294,"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."}}