{"id":"W2153019345","doi":"10.3968/j.css.1923669720141001.4214","title":"A Long-Run Dynamic Analysis of FDI, Growth and Oil Export in GCC Countries: An Evidence from VECM Model","year":2014,"lang":"en","type":"article","venue":"Canadian social science","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variance decomposition of forecast errors; Economics; Error correction model; Impulse response; Foreign direct investment; Shock (circulatory); Vector autoregression; Short run; International economics; Econometrics; Monetary economics; Macroeconomics; Cointegration; International trade; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001334417,0.0004932132,0.0004469114,0.0008928125,0.0003050998,0.001214424,0.0003746534,0.0005843557,0.002265811],"category_scores_gemma":[0.004235721,0.0002285586,0.0007042898,0.001287309,0.0004977887,0.0007277216,0.000658586,0.0008116485,0.0003481029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007982654,"about_ca_system_score_gemma":0.0009805845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04540716,"about_ca_topic_score_gemma":0.02057409,"domain_scores_codex":[0.9995484,0.0001820195,0.00002944973,0.0000910178,0.00004690126,0.0001021926],"domain_scores_gemma":[0.9967119,0.002033128,0.0006388162,0.0001658159,0.0003037743,0.0001465901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004031193,0.000208953,0.6869931,0.00020664,0.0009958419,0.00193008,0.0007227434,0.2601693,0.001770733,0.01912877,0.003356921,0.02411374],"study_design_scores_gemma":[0.00004732186,0.0002887517,0.2861343,0.0001178726,0.0005618413,0.0003899007,0.00158322,0.696648,0.001182219,0.008916315,0.004054735,0.00007550958],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991764,0.0006653588,0.004118395,0.0006472814,0.00002590686,0.000009026913,0.000624596,0.0000610733,0.002084258],"genre_scores_gemma":[0.9973307,0.0004021874,0.0005629361,0.00003765808,0.00001422228,0.000007357834,0.0006744717,0.000009747222,0.0009607428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04540716,"threshold_uncertainty_score":0.09028578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964426795744332,"score_gpt":0.2247917272226189,"score_spread":0.2051474592651756,"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."}}