{"id":"W2904965114","doi":"10.3390/jrfm11040090","title":"Bank Credit and Housing Prices in China: Evidence from a TVP-VAR Model with Stochastic Volatility","year":2018,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Real estate; Vector autoregression; Economics; Volatility (finance); Quarter (Canadian coin); China; Monetary economics; Bank credit; Financial economics; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008625037,0.000137808,0.0003955827,0.0002550804,0.0001238786,0.0001052196,0.0001277546,0.00005973557,0.00001688809],"category_scores_gemma":[0.0001229969,0.0001318336,0.00004016137,0.0001422289,0.0001041809,0.0004715286,0.00009179331,0.0001838205,0.000003968245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007465442,"about_ca_system_score_gemma":0.00002196254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003759222,"about_ca_topic_score_gemma":0.0003851473,"domain_scores_codex":[0.9989299,0.00001063521,0.0005577421,0.0002591297,0.00004424829,0.0001983484],"domain_scores_gemma":[0.9991482,0.00005897625,0.000547772,0.0001424346,0.00002977071,0.00007278795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001900638,0.0002782777,0.7841601,0.000168027,0.000112433,0.00007404667,0.007843524,0.009289235,0.000005061848,0.009381644,0.0003958,0.1863912],"study_design_scores_gemma":[0.001268056,0.0003143135,0.7920643,0.0003215673,0.00005389257,0.000005566558,0.0001265166,0.1517919,0.000002596591,0.05263833,0.001132889,0.000280066],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7959871,0.001022235,0.2018878,0.00006369311,0.0001613644,0.00009631786,0.00001577377,0.000004691971,0.0007610108],"genre_scores_gemma":[0.9854683,0.002942736,0.01126771,0.00003789078,0.0002550895,0.000002093099,4.507256e-7,0.00001218441,0.00001358179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1906201,"threshold_uncertainty_score":0.5376019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01700001676520049,"score_gpt":0.205173052723462,"score_spread":0.1881730359582615,"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."}}