{"id":"W2989762109","doi":"10.1016/j.jmoneco.2020.07.007","title":"Taking off into the Wind: Unemployment Risk and State-Dependent Government Spending Multipliers","year":2019,"lang":"en","type":"preprint","venue":"Journal of Monetary Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"HEC Montréal; Fonds de Recherche du Québec-Société et Culture","keywords":"Economics; Unemployment; Consumption (sociology); Government spending; Shock (circulatory); Recession; Labour economics; Incomplete markets; Multiplier (economics); Aggregate demand; Precautionary savings; Monetary economics; Involuntary unemployment; Population; Macroeconomics; Microeconomics; Monetary policy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001735395,0.0004222534,0.0008609756,0.0007097151,0.0005655026,0.00218252,0.0004944135,0.001561606,0.006214044],"category_scores_gemma":[0.01532714,0.0004187506,0.0004027786,0.0008555363,0.0007994263,0.002560106,0.0009713877,0.002304088,0.0002457438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005625946,"about_ca_system_score_gemma":0.0008045806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004797141,"about_ca_topic_score_gemma":0.005523989,"domain_scores_codex":[0.999765,0.00008890456,0.0000122219,0.00004985463,0.00002091869,0.00006302643],"domain_scores_gemma":[0.9930288,0.005146245,0.0009618125,0.0002675308,0.0002226848,0.0003729288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006918565,0.0002974618,0.1187552,0.0002240812,0.0004675264,0.001161571,0.001047335,0.1555272,0.001325834,0.6616571,0.01205376,0.04679114],"study_design_scores_gemma":[0.00008179634,0.0001243161,0.05007795,0.0001443214,0.000243349,0.0002077251,0.000644068,0.3203863,0.0004619704,0.624847,0.00270864,0.00007254852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618472,0.001905499,0.01844675,0.008306825,0.0001763614,0.00001363058,0.0004359668,0.00005096137,0.008816727],"genre_scores_gemma":[0.9940013,0.0007495122,0.000628906,0.0001098528,0.0001469984,0.000007986197,0.0001042849,0.00001607295,0.004234997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006214044,"threshold_uncertainty_score":0.02078807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306725139346684,"score_gpt":0.2098113837689626,"score_spread":0.1867441323754958,"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."}}