{"id":"W1658635941","doi":"10.1198/073500107000000089","title":"The Sensitivity of Productivity Estimates","year":2008,"lang":"en","type":"article","venue":"Journal of Business and Economic Statistics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Productivity; Econometrics; Nonparametric statistics; Estimation; Economics; Data envelopment analysis; Instrumental variable; Parametric statistics; Productivity model; Total factor productivity; Statistics; Mathematics; Macroeconomics","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":[0.1251642,0.001630256,0.002055651,0.007125971,0.001217876,0.007767894,0.002792589,0.00328992,0.004606282],"category_scores_gemma":[0.6191704,0.001149423,0.00251441,0.006663352,0.004519048,0.007271746,0.007896409,0.005076616,0.001467889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003130608,"about_ca_system_score_gemma":0.001326365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003174212,"about_ca_topic_score_gemma":0.0009762686,"domain_scores_codex":[0.8379499,0.111716,0.01085244,0.01339951,0.02304902,0.003033076],"domain_scores_gemma":[0.2544113,0.6725149,0.02191537,0.03697109,0.01363841,0.0005489906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001291294,0.0002064629,0.2645658,0.002515049,0.006354935,0.00123976,0.00655765,0.1332368,0.001958182,0.2319763,0.01448942,0.3356083],"study_design_scores_gemma":[0.0002174121,0.0004309381,0.1453656,0.00254733,0.001660305,0.002115657,0.007457024,0.1192567,0.01304102,0.6416378,0.06575266,0.0005174276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.243258,0.02109686,0.6229965,0.02222102,0.002984455,0.0006608216,0.004820805,0.00152276,0.08043878],"genre_scores_gemma":[0.9552205,0.003428864,0.0335795,0.002242363,0.001113036,0.0003868436,0.001530806,0.0004182005,0.002079779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1251642,"threshold_uncertainty_score":0.6619395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.030703893834087,"score_gpt":0.2124396513206658,"score_spread":0.1817357574865787,"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."}}