{"id":"W2952007299","doi":"10.1080/01621459.2021.1981913","title":"Saddlepoint Approximations for Spatial Panel Data Models","year":2021,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Collegio Carlo Alberto; McGill University; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Estimator; Edgeworth series; Resampling; Mathematics; Applied mathematics; Gaussian; Econometrics; Monte Carlo method; Panel data; Dimension (graph theory); Cumulant; Series (stratigraphy); Covariate; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.01356556,0.001359164,0.002094312,0.002332828,0.0006128922,0.002088273,0.003568372,0.002096436,0.006818844],"category_scores_gemma":[0.05845126,0.001348403,0.00262941,0.002368159,0.002211109,0.004325333,0.002868705,0.004713665,0.001559597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001722534,"about_ca_system_score_gemma":0.0015877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005602158,"about_ca_topic_score_gemma":0.004853752,"domain_scores_codex":[0.9963077,0.002398153,0.0001726677,0.0003890615,0.0005680971,0.0001643745],"domain_scores_gemma":[0.9674123,0.02741064,0.001300582,0.001838726,0.001723121,0.000314689],"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":[0.00003866238,0.00003147819,0.001634982,0.0001838801,0.0001314825,0.0001953457,0.0002734041,0.3565893,0.0003988938,0.6141306,0.004293527,0.02209834],"study_design_scores_gemma":[0.00001085711,0.00001114887,0.0002012953,0.00003695345,0.00001480291,0.0000314968,0.00002071723,0.7855418,0.0001134909,0.2119196,0.002084327,0.00001350565],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001630144,0.000290933,0.9966984,0.0002487672,0.00002954253,0.00001899694,0.00009475778,0.0001182599,0.0008699838],"genre_scores_gemma":[0.2940396,0.003660156,0.6809595,0.001068425,0.0004630316,0.001071929,0.001996652,0.0009298159,0.01581092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01356556,"threshold_uncertainty_score":0.07174236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1087650211398521,"score_gpt":0.280812262977202,"score_spread":0.17204724183735,"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."}}