{"id":"W4394565252","doi":"10.2139/ssrn.4787389","title":"Consumption Dynamics and Welfare Under Non-Gaussian Earnings Risk","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Welfare; Earnings; Dynamics (music); Consumption (sociology); Economics; Gaussian; Econometrics; Labour economics; Demographic economics; Physics; Finance; Market economy; Sociology","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":[0.001797211,0.0003314312,0.001081071,0.0006790645,0.0005941503,0.002840688,0.0005684177,0.001554358,0.006082746],"category_scores_gemma":[0.008463115,0.0004036893,0.0006193282,0.0008117337,0.001707733,0.003140385,0.001637702,0.001366581,0.0004897598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698425,"about_ca_system_score_gemma":0.0008308653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007428735,"about_ca_topic_score_gemma":0.005068379,"domain_scores_codex":[0.9995825,0.0001096812,0.0000136599,0.00006813659,0.00003562224,0.0001904227],"domain_scores_gemma":[0.9962507,0.00233162,0.0006022417,0.0002104393,0.0002080947,0.0003969243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001934862,0.0008862944,0.08938435,0.00017219,0.0002535254,0.001760241,0.002390815,0.2017913,0.008042275,0.6484625,0.005969579,0.0389521],"study_design_scores_gemma":[0.0001151313,0.0003504926,0.07541921,0.00004685394,0.00008816674,0.0004398661,0.002596865,0.4653329,0.000770327,0.4531546,0.001593253,0.00009230943],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815108,0.0002009614,0.0105232,0.001887034,0.00001442216,0.00001331945,0.0003447972,0.00005878579,0.005446554],"genre_scores_gemma":[0.9919227,0.0002044161,0.0006066986,0.00008143015,0.00001902868,0.000009897401,0.0001379651,0.00001500903,0.007002789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007428735,"threshold_uncertainty_score":0.02034879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005009702461801922,"score_gpt":0.2165174221301595,"score_spread":0.2115077196683575,"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."}}