{"id":"W2797698245","doi":"10.5539/ijef.v10n5p184","title":"The Impact of RMB Exchange Rate Fluctuation on Price Level in China: An Empirical Analysis Based on the Vector Error Correction Model","year":2018,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Renminbi; Exchange rate; Economics; Error correction model; Effective exchange rate; China; Index (typography); Econometrics; Monetary economics; Price index; Price level; Transfer (computing); Consumer price index (South Africa); International economics; Cointegration; Monetary policy; Computer science","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":[0.004409601,0.0007352403,0.0009481348,0.001431117,0.0004824483,0.001650672,0.001387277,0.001069578,0.002656562],"category_scores_gemma":[0.01189026,0.0004748498,0.001544265,0.002124576,0.0008032152,0.001638929,0.0009357535,0.001704499,0.0005455217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032367,"about_ca_system_score_gemma":0.001429748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04764062,"about_ca_topic_score_gemma":0.01302547,"domain_scores_codex":[0.997641,0.0006130115,0.0002280158,0.0005985502,0.0005171328,0.0004023649],"domain_scores_gemma":[0.9895675,0.005642411,0.002374565,0.000896425,0.001078399,0.0004406791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003501783,0.0002870332,0.9070539,0.0001274925,0.0006601018,0.001209147,0.0005762154,0.06533519,0.000747584,0.003139405,0.002069482,0.01844427],"study_design_scores_gemma":[0.00007315856,0.0002983821,0.5078171,0.00003833818,0.0004203694,0.0002832846,0.0004001366,0.4870534,0.0008735912,0.001396218,0.001268805,0.00007732989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938775,0.0002504017,0.004135149,0.0003289887,0.00003032857,0.0000291236,0.0003741381,0.00009167744,0.0008826666],"genre_scores_gemma":[0.9978257,0.0001661978,0.0003698176,0.00002822215,0.00002230488,0.00001680218,0.0007335448,0.00001358063,0.0008237055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04764062,"threshold_uncertainty_score":0.09472662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05338098944494561,"score_gpt":0.2793427897133887,"score_spread":0.2259618002684431,"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."}}