{"id":"W3122812010","doi":"","title":"Semiparametric Innovation-Based Tests of Orthogonality and Causality Between Two Infinite-Order Cointegrated Ceries with Application to Canada/US Monetary Interactions","year":2011,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Montréal; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; McGill University","keywords":"Mathematics; Econometrics; Autoregressive model; Test statistic; Univariate; Cointegration; Autocorrelation; Series (stratigraphy); Statistic; Statistics; Statistical hypothesis testing; Multivariate statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.006803825,0.0005117182,0.001016022,0.002063443,0.0004146375,0.001283599,0.001381651,0.0006117501,0.001593723],"category_scores_gemma":[0.03977051,0.0002912804,0.0008171467,0.002042941,0.001922655,0.0009823598,0.002303625,0.0009132987,0.0001039696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095063,"about_ca_system_score_gemma":0.002611084,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01439607,"about_ca_topic_score_gemma":0.01231581,"domain_scores_codex":[0.9957624,0.002295165,0.0002061428,0.0004404992,0.0009725864,0.0003231739],"domain_scores_gemma":[0.9660137,0.02666346,0.004121677,0.001405113,0.001359165,0.0004368372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004596415,0.0003850152,0.07971036,0.0002016014,0.000722921,0.0007990843,0.0008253735,0.4935942,0.003889565,0.1970252,0.0007128156,0.2216743],"study_design_scores_gemma":[0.0000483636,0.0001833765,0.02172259,0.00001552415,0.00007362762,0.00007908664,0.0001500609,0.9130971,0.001236107,0.06267697,0.0006519486,0.00006518326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4379786,0.0002175798,0.5591058,0.0001573942,0.00001418762,0.00008404697,0.0001620292,0.0002940646,0.001986312],"genre_scores_gemma":[0.9500326,0.00008391806,0.04904797,0.00003164065,0.00001708567,0.00006722894,0.0001896908,0.00002437001,0.0005055133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9856039,"threshold_uncertainty_score":0.03598249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04336298651435174,"score_gpt":0.3000623648856702,"score_spread":0.2566993783713185,"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."}}