{"id":"W2772340637","doi":"10.3982/qe1851","title":"Permanent‐income inequality","year":2022,"lang":"en","type":"preprint","venue":"Quantitative Economics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Queen's University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economics; Permanent income hypothesis; Human capital; Market liquidity; Inequality; Consumption (sociology); Income shares; Economic inequality; Distribution (mathematics); Econometrics; Discounting; Income distribution; Labour economics; Wealth elasticity of demand; Income inequality metrics; Autonomous consumption; National wealth; Monetary economics; Macroeconomics; Finance; Debt","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001076378,0.0005338875,0.0008731632,0.0006748917,0.0003960349,0.0005560953,0.0008887255,0.0001846581,0.005224799],"category_scores_gemma":[0.0002745208,0.0006189362,0.0005089235,0.0003412231,0.0001154449,0.0008907354,0.002942296,0.000743999,0.001519074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000357681,"about_ca_system_score_gemma":0.0001118949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002075492,"about_ca_topic_score_gemma":0.0006142276,"domain_scores_codex":[0.9972751,0.00006343409,0.0009895891,0.0009963043,0.0002403297,0.0004352664],"domain_scores_gemma":[0.9973789,0.000141868,0.001322741,0.0008814615,0.0002524373,0.00002257891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009969041,0.0001407861,0.5530424,0.0005611694,0.0001083788,0.00001710754,0.0002825567,0.006046303,0.00000893665,0.4364949,0.003007371,0.0001903819],"study_design_scores_gemma":[0.001006176,0.00005573661,0.457251,0.0001843832,0.0006539914,0.000001081523,0.001096341,0.07540321,0.00001295362,0.1634899,0.2983051,0.002540188],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781393,0.000264651,0.00006437291,0.0003554417,0.002173033,0.0005189391,0.0001630833,0.0001688964,0.01815229],"genre_scores_gemma":[0.9909309,0.000162959,0.001672743,0.001964388,0.00133652,0.0001606233,0.002437092,0.0001251176,0.001209686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2952977,"threshold_uncertainty_score":0.9996262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05387522873207889,"score_gpt":0.2928536130704895,"score_spread":0.2389783843384106,"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."}}