{"id":"W4316035329","doi":"10.1016/j.qref.2023.01.002","title":"Geopolitical risks and tourism stocks: New evidence from causality-in-quantile approach","year":2023,"lang":"en","type":"article","venue":"The Quarterly Review of Economics and Finance","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Quantile; Econometrics; Volatility (finance); Economics; Stock (firearms); China; Tourism; Univariate; Outlier; Causality (physics); Geopolitics; Financial economics; Geography; Multivariate statistics; Statistics; Mathematics; Political 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":[],"consensus_categories":[],"category_scores_codex":[0.001729139,0.0001961644,0.0007925067,0.00008312264,0.00007449929,0.00005360566,0.0002898265,0.00009166901,0.00004405857],"category_scores_gemma":[0.00008863383,0.000181364,0.00009684162,0.0001953792,0.0001560489,0.0002167562,0.00007908276,0.0001988823,0.00002737308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003214549,"about_ca_system_score_gemma":0.0000375393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003464048,"about_ca_topic_score_gemma":0.0001484974,"domain_scores_codex":[0.998099,0.00004941898,0.0009713816,0.0005405564,0.00002254614,0.0003170626],"domain_scores_gemma":[0.9985788,0.000335269,0.0004054613,0.0005930472,0.00001730577,0.00007005478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007301995,0.0001249577,0.1156556,0.002790979,0.00009852026,0.000005868606,0.001620643,0.00004921658,0.000001826366,0.8062805,0.002276303,0.0710226],"study_design_scores_gemma":[0.0006160383,0.0002159376,0.3256452,0.001696104,0.00003065301,0.000006657993,0.0001391117,0.2208372,0.000001176693,0.4307161,0.01957646,0.0005193825],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8997993,0.09581536,0.0003154136,0.001516418,0.0001405629,0.0004426382,0.000244437,0.00001288803,0.001712999],"genre_scores_gemma":[0.7068781,0.2919599,0.0004795483,0.0002668431,0.00007734484,0.0000309857,0.00001859151,0.00001666577,0.0002720228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3755644,"threshold_uncertainty_score":0.7395809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07915690747225937,"score_gpt":0.2828400614878583,"score_spread":0.2036831540155989,"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."}}