{"id":"W1975137172","doi":"10.1080/07474938.2011.553538","title":"Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors","year":2011,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Circus School; Concordia University","funders":"","keywords":"Heteroscedasticity; Unit root; Autoregressive conditional heteroskedasticity; Mathematics; Monte Carlo method; Econometrics; Sample size determination; Statistics; Unit root test; Asymptotic analysis; Asymptotic distribution; Cointegration; Estimator","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":[0.01115656,0.0005976326,0.001428228,0.001683684,0.000464466,0.001034471,0.001585037,0.001485661,0.002323281],"category_scores_gemma":[0.0851729,0.0004060181,0.0009299156,0.0021803,0.001182119,0.002281053,0.001585992,0.001286608,0.0005303093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004762434,"about_ca_system_score_gemma":0.001052915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337788,"about_ca_topic_score_gemma":0.001142418,"domain_scores_codex":[0.9922672,0.006004009,0.0001944561,0.0003371731,0.0009779109,0.0002192367],"domain_scores_gemma":[0.9517041,0.04219205,0.001917908,0.002574783,0.001364631,0.0002466443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005159192,0.0002190607,0.02191854,0.0003913014,0.0005274835,0.0008670538,0.0004138052,0.3569519,0.00256846,0.311332,0.005406767,0.2988878],"study_design_scores_gemma":[0.00007555646,0.0001708141,0.004327009,0.00007000865,0.00005879172,0.0002274501,0.0001310712,0.7469317,0.001832709,0.2439235,0.002200576,0.00005078913],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06798221,0.001067405,0.9268646,0.0003684636,0.00007608213,0.0000406553,0.0001279466,0.0006283946,0.002844267],"genre_scores_gemma":[0.8716152,0.0009782282,0.1253199,0.0002040404,0.0002079382,0.0001497856,0.0004201613,0.0001628893,0.0009417663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01115656,"threshold_uncertainty_score":0.05900222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3153720633229867,"score_gpt":0.2847558251072748,"score_spread":0.03061623821571197,"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."}}