{"id":"W2274206508","doi":"10.1111/jmcb.12416","title":"House Prices and Government Spending Shocks","year":2017,"lang":"en","type":"article","venue":"Journal of money credit and banking","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; Carleton University; Toronto Metropolitan University; Bank of Canada; Université de Sherbrooke","funders":"","keywords":"Dynamic stochastic general equilibrium; Economics; Government spending; Government (linguistics); Value (mathematics); Monetary economics; Collateralized debt obligation; House price; Demand shock; Shadow (psychology); Macroeconomics; Econometrics; Keynesian economics; Monetary policy; Finance; Welfare; Market economy","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":[],"consensus_categories":[],"category_scores_codex":[0.0008479953,0.00009907452,0.0003212072,0.00007187864,0.0003285246,0.00048763,0.0001880436,0.00005985977,0.00006127271],"category_scores_gemma":[0.0001362655,0.0001001677,0.00006083712,0.00001388353,0.00005955452,0.0006301352,0.000114606,0.0001512642,0.000005957059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006342263,"about_ca_system_score_gemma":0.000006298796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002576989,"about_ca_topic_score_gemma":0.00001024751,"domain_scores_codex":[0.9991957,0.000004051342,0.0004513978,0.0001404926,0.00004534356,0.0001630071],"domain_scores_gemma":[0.998657,0.00004504211,0.001044437,0.0001570529,0.00001015013,0.00008635786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006667811,0.00003490948,0.9675591,0.00003879497,0.00009519375,0.00003753503,0.000642466,0.00001555815,0.00009721869,0.008379498,0.0007968758,0.02223616],"study_design_scores_gemma":[0.002159995,0.0002715278,0.892886,0.0002164479,0.00005546627,0.0002167044,0.0003856949,0.003442021,0.0002964727,0.03885131,0.06068618,0.0005321432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739851,0.00108033,0.0004900548,0.0004341965,0.0008288716,0.00003510323,0.000006602229,0.000006446027,0.02313327],"genre_scores_gemma":[0.9951892,0.002833138,0.001142326,0.00003995117,0.0006959907,3.901217e-7,1.373152e-7,0.00001758466,0.00008126092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07467308,"threshold_uncertainty_score":0.4702227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03244525594465201,"score_gpt":0.2258725815585461,"score_spread":0.1934273256138941,"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."}}