{"id":"W2160615331","doi":"10.1111/1468-2354.t01-1-00045","title":"The Distribution of Earnings in an Equilibrium Search Model with State‐Dependent Offers and Counteroffers*","year":2002,"lang":"en","type":"article","venue":"International Economic Review","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":165,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wage dispersion; Earnings; Productivity; Wage; Economics; Distribution (mathematics); Dispersion (optics); Ex-ante; Labour economics; Efficiency wage; Homogeneous; General equilibrium theory; Construct (python library); Microeconomics; Econometrics; Macroeconomics; Computer science; Finance","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":[0.001512036,0.00009942481,0.0002740265,0.00005407308,0.00002857088,0.00006338755,0.0002621335,0.00002965893,0.0001041024],"category_scores_gemma":[0.0000440623,0.00008308869,0.0000406227,0.00004713931,0.00008158728,0.0002756359,0.00006127426,0.0001187973,0.00001647043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002182795,"about_ca_system_score_gemma":0.00001446051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002192384,"about_ca_topic_score_gemma":0.0001456759,"domain_scores_codex":[0.9988545,0.00002649768,0.0006530446,0.0002600416,0.00004782483,0.0001581143],"domain_scores_gemma":[0.9993329,0.00007814011,0.0002847608,0.0002095035,0.00004742235,0.00004724841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002083054,0.0002430836,0.4265134,0.0007320199,0.0002384929,0.000009784069,0.0006003251,0.01139574,0.00001820993,0.5378217,0.0003991546,0.02181983],"study_design_scores_gemma":[0.001108277,0.0001560786,0.05086601,0.0005055314,0.00001004423,0.00001226612,0.00004373719,0.9186229,0.0000188248,0.01690461,0.01137159,0.0003801895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878049,0.005629974,0.001256582,0.001967562,0.000121709,0.0002310976,0.0004384837,0.000006284562,0.002543333],"genre_scores_gemma":[0.9686916,0.03060261,0.00003957425,0.0001582025,0.00001626947,0.00001394743,0.00005835493,0.00000841269,0.0004110558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9072271,"threshold_uncertainty_score":0.3388258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03726880517164449,"score_gpt":0.2635831765045282,"score_spread":0.2263143713328837,"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."}}