{"id":"W2102591219","doi":"10.1111/1368-423x.00085","title":"Distributions of error correction tests for cointegration","year":2002,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":326,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Cointegration; Quantile; Statistic; Monte Carlo method; Sample (material); Sample size determination; Statistics; Error detection and correction; Mathematics; Standard error; Applied mathematics; Computer science; Econometrics; Algorithm; Physics","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":[0.03471177,0.0009402372,0.002401305,0.00854871,0.00116644,0.003836491,0.003000516,0.002958268,0.01026976],"category_scores_gemma":[0.3091626,0.0006699194,0.001706413,0.003775425,0.006115427,0.006184679,0.002798917,0.003847989,0.001290819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001754107,"about_ca_system_score_gemma":0.001350876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008256173,"about_ca_topic_score_gemma":0.0002996635,"domain_scores_codex":[0.9776174,0.01134476,0.001343772,0.00332841,0.005331697,0.001033837],"domain_scores_gemma":[0.529443,0.4350078,0.009049352,0.01551791,0.00954529,0.00143655],"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":[0.0004889946,0.0001697926,0.03261938,0.0006439192,0.0005402533,0.0007372724,0.001265217,0.09813496,0.001725003,0.7128655,0.007702791,0.1431069],"study_design_scores_gemma":[0.000149182,0.0002912709,0.01238804,0.0003972698,0.00009948306,0.000936773,0.0004856228,0.2011516,0.003928726,0.7743421,0.005669398,0.0001606052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1580335,0.001579242,0.8238596,0.001204921,0.0001824279,0.0004063149,0.00144817,0.002027543,0.01125831],"genre_scores_gemma":[0.9242057,0.0004905585,0.07033493,0.0002755024,0.0001944797,0.0009703716,0.001714117,0.0005157368,0.001298664],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03471177,"threshold_uncertainty_score":0.1835756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2330786530290661,"score_gpt":0.2757505888953286,"score_spread":0.04267193586626256,"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."}}