{"id":"W2742631142","doi":"","title":"Efficiency in Large Dynamic Panel Models with Common Factor","year":2008,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation du Risque; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Unobservable; Estimator; Dynamic factor; Macro; Econometrics; Identification (biology); Factor analysis; Nonlinear system; Panel data; Mathematics; Applied mathematics; Specification; Computer science; 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":[0.03655778,0.001512922,0.004836455,0.002325482,0.0014952,0.005313445,0.004415466,0.004013288,0.008508333],"category_scores_gemma":[0.1588035,0.003182929,0.003388262,0.003500813,0.003397636,0.008793586,0.003853634,0.003389078,0.001796186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002188564,"about_ca_system_score_gemma":0.001926956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01376527,"about_ca_topic_score_gemma":0.01007804,"domain_scores_codex":[0.9818875,0.01398558,0.0006769674,0.001959136,0.0007389185,0.0007517246],"domain_scores_gemma":[0.6983236,0.2762567,0.005286045,0.01659208,0.002699612,0.0008418868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003063228,0.000156101,0.006573336,0.0003580556,0.0007425377,0.0003720988,0.0004827477,0.6963896,0.0004271824,0.244268,0.008555487,0.04136858],"study_design_scores_gemma":[0.0000597632,0.00002122977,0.00109126,0.00004663724,0.00009631232,0.00004720476,0.00006619676,0.7527269,0.0001897408,0.24444,0.001187742,0.00002700284],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03790882,0.001389855,0.9525882,0.002163099,0.00008453357,0.0001003641,0.0009138886,0.0007063486,0.004144878],"genre_scores_gemma":[0.8100052,0.002739575,0.1603474,0.00122191,0.000595297,0.0006567648,0.004531877,0.001059093,0.01884296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03655778,"threshold_uncertainty_score":0.1933383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07314110909673183,"score_gpt":0.27855957922967,"score_spread":0.2054184701329382,"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."}}