{"id":"W2904041857","doi":"10.2139/ssrn.3037449","title":"Responses to Saving Commitments: Evidence from Mortgage Run-Offs","year":2017,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Debt; Constraint (computer-aided design); Short run; Population; Shared appreciation mortgage; Earnings; Mortgage insurance; Economics; Mortgage underwriting; Monetary economics; Budget constraint; Balance sheet; Business; Finance; Microeconomics","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":[0.002654689,0.0002937543,0.0005164807,0.00086689,0.00049264,0.001551209,0.000871648,0.002084118,0.01225956],"category_scores_gemma":[0.03312736,0.0003579263,0.0003271184,0.001387408,0.0008070662,0.001022929,0.001621075,0.00227824,0.003296378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003043709,"about_ca_system_score_gemma":0.0003102358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003062143,"about_ca_topic_score_gemma":0.003877547,"domain_scores_codex":[0.9984726,0.0005715819,0.0001713412,0.0002274964,0.0002914467,0.0002654341],"domain_scores_gemma":[0.9404641,0.02020367,0.02830563,0.003883951,0.003188018,0.003954608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004893593,0.001755756,0.9436357,0.000252647,0.0004307067,0.0005742495,0.002485404,0.001506059,0.001544719,0.00275411,0.008156199,0.03201088],"study_design_scores_gemma":[0.00008605716,0.0004239665,0.990598,0.00005025269,0.00006987123,0.0001211282,0.001855792,0.0005422345,0.0004893558,0.001394701,0.004346328,0.00002231122],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926866,0.0003174419,0.0001604383,0.0007540614,0.00002827764,0.00002151783,0.00154493,0.00001468139,0.004471961],"genre_scores_gemma":[0.9941901,0.0004317337,0.0001044648,0.0001892463,0.00006729118,0.00003958618,0.00264342,0.00001373914,0.002320283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01225956,"threshold_uncertainty_score":0.04101223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06016739987802239,"score_gpt":0.2814459350117383,"score_spread":0.2212785351337159,"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."}}