{"id":"W1977434222","doi":"10.1016/j.jeconom.2007.05.011","title":"Adaptive consistent unit-root tests based on autoregressive threshold model","year":2007,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Unit root; Autoregressive model; Mathematics; Threshold model; Unit root test; Asymptotic distribution; Null (SQL); Null hypothesis; Applied mathematics; Econometrics; Bounded function; Monte Carlo method; Simple (philosophy); Limit (mathematics); Cointegration; Mathematical optimization; Statistics; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002696064,0.0003157887,0.0008944109,0.003151767,0.0001293234,0.0001036633,0.0004940553,0.0002151871,0.0004127548],"category_scores_gemma":[0.0006293576,0.0003283937,0.0004623199,0.0006150048,0.0001075218,0.0005198426,0.00004589411,0.0005470883,0.0003061498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005026536,"about_ca_system_score_gemma":0.0001068551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003272761,"about_ca_topic_score_gemma":0.00001926397,"domain_scores_codex":[0.9970437,0.00001441534,0.001875288,0.000363717,0.00009017016,0.0006126532],"domain_scores_gemma":[0.9962199,0.0005447991,0.002243313,0.0004505561,0.00009254446,0.0004488419],"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":[0.0004580503,0.000701741,0.2245831,0.00003548365,0.0003641826,0.000126944,0.0004305024,0.6961898,0.000004562693,0.06818902,0.006428505,0.002488064],"study_design_scores_gemma":[0.00336016,0.001700465,0.1213792,0.0000801753,0.00004887901,0.00008316273,0.0001615044,0.8283864,0.0001540601,0.03184981,0.01196966,0.0008264565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8559156,0.002228469,0.03549393,0.0009311461,0.001434383,0.0002817116,0.0003329985,0.00002916458,0.1033526],"genre_scores_gemma":[0.9942112,0.00007991716,0.003382771,0.001297625,0.0003600788,0.000002065881,0.000006138208,0.00004329784,0.0006169362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1382955,"threshold_uncertainty_score":0.9999168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3874366846053098,"score_gpt":0.2700113432257979,"score_spread":0.1174253413795119,"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."}}