{"id":"W2128362579","doi":"10.1016/j.jeconom.2011.01.007","title":"Inference with dependent data using cluster covariance estimators","year":2011,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":264,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Estimator; Heteroscedasticity; Mathematics; Autocorrelation; Inference; Wald test; Statistics; Series (stratigraphy); Statistical inference; Covariance; Asymptotic distribution; Spatial analysis; Cluster (spacecraft); Econometrics; Applied mathematics; Statistical hypothesis testing; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02992986,0.001040137,0.002954235,0.00323676,0.001510911,0.003006707,0.004467854,0.002717307,0.003201919],"category_scores_gemma":[0.1571742,0.002200207,0.003605936,0.003895635,0.002874012,0.005249015,0.003373187,0.0039405,0.0005799389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536813,"about_ca_system_score_gemma":0.002994893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009982368,"about_ca_topic_score_gemma":0.007736164,"domain_scores_codex":[0.9819971,0.01196371,0.0007597209,0.003405451,0.001411943,0.0004621393],"domain_scores_gemma":[0.7932207,0.1702695,0.005134651,0.02433211,0.006138607,0.0009043536],"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":[0.0007025427,0.0004384342,0.02418175,0.0003821331,0.003462305,0.0004693128,0.0006927109,0.334726,0.001299857,0.4923461,0.007537238,0.1337616],"study_design_scores_gemma":[0.00009213787,0.00003964634,0.001606312,0.00002751181,0.0001380035,0.00007502652,0.00004582008,0.7810079,0.0006307058,0.2153396,0.0009653789,0.0000319966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007917698,0.0001031869,0.9913253,0.0001114006,0.00003814652,0.00003278978,0.00007683047,0.0001584994,0.0002361303],"genre_scores_gemma":[0.3483776,0.0004359688,0.6460538,0.0002899612,0.0003338124,0.0003657205,0.001483498,0.000263632,0.00239594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02992986,"threshold_uncertainty_score":0.1582862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4978358075823746,"score_gpt":0.2771576014143565,"score_spread":0.2206782061680181,"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."}}