{"id":"W1981771568","doi":"10.1016/j.intfin.2013.05.001","title":"Measuring cost efficiency in presence of heteroskedasticity: The case of the banking industry in Taiwan","year":2013,"lang":"en","type":"article","venue":"Journal of International Financial Markets Institutions and Money","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"St. Thomas University; University of St. Thomas; University at Buffalo; City University of New York","keywords":"Inefficiency; Cost efficiency; Econometrics; Heteroscedasticity; Economics; Stochastic frontier analysis; Estimation; Loan; Panel data; Business; Microeconomics; Finance; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005730907,0.0004035223,0.0009392916,0.001270101,0.0004668187,0.001998775,0.001098257,0.001412321,0.0007612134],"category_scores_gemma":[0.0179299,0.0003433776,0.0007582397,0.001491257,0.001006254,0.001768019,0.0008838982,0.0008364501,0.0000802585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002100066,"about_ca_system_score_gemma":0.001718714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04396312,"about_ca_topic_score_gemma":0.02976372,"domain_scores_codex":[0.9981222,0.001034226,0.0001498254,0.0002280196,0.0002116675,0.0002541597],"domain_scores_gemma":[0.9771697,0.01813178,0.002242125,0.000964371,0.001229893,0.0002620776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003677576,0.0004788861,0.3641106,0.0001543191,0.0005789758,0.002240638,0.0006318743,0.57609,0.002920846,0.02033208,0.0005738007,0.03152008],"study_design_scores_gemma":[0.00003337156,0.0001363939,0.120163,0.00001800862,0.0001564742,0.0001775366,0.001233066,0.8684942,0.00148158,0.007828401,0.0002278595,0.00005013665],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915066,0.0001028666,0.007460304,0.0002112611,0.000002645765,0.00001385687,0.00003839122,0.00001199824,0.0006522232],"genre_scores_gemma":[0.9989389,0.00002512837,0.0008764346,0.000004997766,0.000002488663,0.000002855266,0.00002374086,0.000001985621,0.000123469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04396312,"threshold_uncertainty_score":0.0874145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07073617405270195,"score_gpt":0.3373644175026899,"score_spread":0.2666282434499879,"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."}}