{"id":"W4291321817","doi":"10.33423/jabe.v24i4.5354","title":"Autoregressive Distributed Lag (ARDL) Analysis of Foreign Portfolio Investments Determination in Nigeria","year":2022,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distributed lag; Economics; Exchange rate; Autoregressive model; Econometrics; Inflation (cosmology); Cointegration; Portfolio; Monetary economics; Causality (physics); Short run; Inflation rate; Interest rate; Granger causality; Portfolio investment; Financial economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006404337,0.0001461844,0.0008507451,0.001083377,0.00008604754,0.00004170919,0.0002203657,0.00007061328,0.0001363048],"category_scores_gemma":[0.00002951578,0.0001709542,0.0001487292,0.0005092007,0.00006299813,0.0002629532,0.0001172747,0.0001634176,0.000002275246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002548094,"about_ca_system_score_gemma":0.00004697959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004899387,"about_ca_topic_score_gemma":0.00002853177,"domain_scores_codex":[0.9982399,0.00000924525,0.00129605,0.0002226499,0.00002796146,0.0002042476],"domain_scores_gemma":[0.9978648,0.00004593928,0.001817059,0.0001615498,0.00003565089,0.00007493503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006495127,0.0005096784,0.4735993,0.0001029711,0.001390929,0.00002369095,0.00174234,0.06020921,0.00005503648,0.4576475,0.0005217906,0.003548029],"study_design_scores_gemma":[0.001935294,0.00008436404,0.6967125,0.000009987528,0.0001334214,0.00001953368,0.0007615492,0.02394005,0.00007789724,0.2728176,0.003162896,0.0003449074],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885629,0.0001854147,0.000330991,0.0001233768,0.0001889348,0.0001046523,0.0004106679,0.000003325198,0.01008969],"genre_scores_gemma":[0.9992566,0.0001177456,0.0002794465,0.0001730746,0.00006295976,0.00001405085,0.00006769395,0.00001513558,0.00001331432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2231132,"threshold_uncertainty_score":0.6971309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794820286198065,"score_gpt":0.2075859200785435,"score_spread":0.1896377172165628,"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."}}