{"id":"W1561871134","doi":"","title":"The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity","year":2000,"lang":"en","type":"article","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Cointegration; Purchasing power parity; Estimator; Econometrics; Seemingly unrelated regressions; Mathematics; Covariance matrix; Statistical hypothesis testing; Statistics; Economics","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":[0.001260773,0.0001664111,0.0001642476,0.0001498417,0.01097618,0.0002250135,0.000311529,0.0001267104,0.00002235267],"category_scores_gemma":[0.001499773,0.0001159433,0.00008903126,0.0005092635,0.0002200349,0.0004238077,0.000113773,0.000222344,0.00001372618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006797337,"about_ca_system_score_gemma":0.0003221126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004874201,"about_ca_topic_score_gemma":0.000490997,"domain_scores_codex":[0.9981211,0.00009505407,0.0004458901,0.0004027776,0.0006699132,0.0002653074],"domain_scores_gemma":[0.997731,0.001112127,0.0002727277,0.0002775376,0.0004872439,0.0001193279],"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":[0.001520567,0.0001355179,0.01721642,0.00001710424,0.00008773615,0.0001545956,0.02294856,0.05156653,0.06914848,0.07552103,0.002701309,0.7589821],"study_design_scores_gemma":[0.000726385,0.00006410018,0.01047319,0.00007400884,0.00002187543,0.0002624009,0.005601443,0.9527428,0.0005896168,0.0107696,0.01846495,0.0002096945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583321,0.0007609013,0.007734512,0.001051982,0.0002032736,0.0002616974,0.00001414733,0.00008129024,0.03156007],"genre_scores_gemma":[0.9708174,0.00002577535,0.003375646,0.0001048847,0.00002590235,0.000008255284,0.00001175197,0.000009269318,0.02562115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9011762,"threshold_uncertainty_score":0.9903114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02448938021152628,"score_gpt":0.2462308939333973,"score_spread":0.2217415137218711,"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."}}