{"id":"W3121432732","doi":"","title":"Decomposing Wage Inequality Change Using General Equilibrium Models","year":2002,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Economics; General equilibrium theory; Counterfactual thinking; Inequality; Technological change; Econometrics; Wage inequality; Wage; Economic inequality; Consumption (sociology); Applied general equilibrium; Labour economics; Macroeconomics; Mathematics","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":[0.001765797,0.000702414,0.0007612544,0.001477071,0.000514199,0.001604292,0.000816528,0.000854962,0.005002631],"category_scores_gemma":[0.005477732,0.0004080097,0.001530875,0.001543083,0.0007883388,0.001746414,0.0009933757,0.001210087,0.0003770474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001741638,"about_ca_system_score_gemma":0.0006352836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01406535,"about_ca_topic_score_gemma":0.01167187,"domain_scores_codex":[0.99922,0.0003394991,0.00002472356,0.0001287104,0.0001094414,0.0001775502],"domain_scores_gemma":[0.9988602,0.0006359448,0.0002190946,0.0001447134,0.00008797886,0.00005201505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001249537,0.0001426581,0.01743305,0.00006365685,0.0001759547,0.000211888,0.0004132213,0.8198623,0.001007302,0.1410926,0.001137415,0.01833502],"study_design_scores_gemma":[0.00001596928,0.00002565811,0.006728293,0.00001264025,0.00002119267,0.00002068515,0.0001635019,0.894856,0.0001962277,0.09695186,0.0009932134,0.00001463771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.580442,0.0005643098,0.4032033,0.001190435,0.00005760122,0.0001111424,0.0007722644,0.0003074385,0.01335148],"genre_scores_gemma":[0.9745807,0.0003411495,0.02142301,0.00008829086,0.00003276987,0.00006913269,0.0004692076,0.00005098483,0.002944736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01406535,"threshold_uncertainty_score":0.02796698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1350703161875335,"score_gpt":0.260657539844654,"score_spread":0.1255872236571205,"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."}}