{"id":"W4289823626","doi":"10.2139/ssrn.4176998","title":"Estimating the Feedback Among Credit Rating Agencies and its Impact on the Municipal Bond Market","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ceteris paribus; Credit rating; Bond credit rating; Incentive; Yield (engineering); Bond; Economics; Endogeneity; Actuarial science; Bond market; Econometrics; Business; Credit risk; Microeconomics; Monetary economics; Finance; Credit reference","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003864554,0.0001504865,0.0002040258,0.0001076238,0.002174244,0.0001691939,0.0003829376,0.00003537204,0.0003808863],"category_scores_gemma":[0.0003794693,0.0001025577,0.0001492071,0.0002816312,0.00007046854,0.0001863903,0.0001365107,0.001740883,0.00001484109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00073205,"about_ca_system_score_gemma":0.0002900921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002089864,"about_ca_topic_score_gemma":0.0002355911,"domain_scores_codex":[0.9981556,0.00006573107,0.0004146613,0.0001969391,0.0001004458,0.001066625],"domain_scores_gemma":[0.9990224,0.000264164,0.000429448,0.0002115978,0.00002272932,0.00004969106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008233487,0.00005875892,0.05270306,0.000004620017,0.0001878377,0.000004642351,0.003828483,0.01618473,0.00001750369,0.9162922,0.004763586,0.005872231],"study_design_scores_gemma":[0.0006846524,0.0006751743,0.2901664,0.00002011555,0.00003170921,0.0003294251,0.009282243,0.2735734,0.00000718967,0.4183556,0.006448536,0.0004255979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875141,0.004930492,0.0005067131,0.001601289,0.0003772646,0.0001821561,0.00004592615,0.00001342107,0.004828668],"genre_scores_gemma":[0.9972308,0.000444239,0.00003497001,0.00004947176,0.0005067033,0.00002724315,0.000003252434,0.00002178292,0.001681534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4979366,"threshold_uncertainty_score":0.9991248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01825104565285796,"score_gpt":0.2358825784416541,"score_spread":0.2176315327887962,"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."}}