{"id":"W2073169695","doi":"10.1007/s11127-011-9811-1","title":"Modeling local growth control decisions in a multi-city case: Do spatial interactions and lobbying efforts matter?","year":2011,"lang":"en","type":"article","venue":"Public Choice","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec; Université du Québec à Montréal","funders":"","keywords":"Interdependence; Economics; Imperfect; Control (management); Public finance; Locale (computer software); Politics; Spatial econometrics; Microfoundations; Econometrics; Microeconomics; Endogenous growth theory; Econometric model; Economic geography; Public economics; Macroeconomics; Political science; Economic growth","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":[0.003687539,0.0007625032,0.001800541,0.001233709,0.001075011,0.003416147,0.002655219,0.004235272,0.0121866],"category_scores_gemma":[0.01056136,0.001106699,0.001400064,0.001645787,0.001780734,0.002882543,0.001759362,0.002649955,0.0007743702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003709755,"about_ca_system_score_gemma":0.00208505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09211731,"about_ca_topic_score_gemma":0.07825104,"domain_scores_codex":[0.9983783,0.0007778287,0.00003584668,0.0002603199,0.00005765432,0.0004901054],"domain_scores_gemma":[0.9900592,0.007235059,0.00119481,0.0003237149,0.0003155611,0.0008717116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004205332,0.0005267977,0.02876535,0.00004740989,0.0001713981,0.0004000387,0.0002317727,0.9401684,0.0003802344,0.02388927,0.001180287,0.003818443],"study_design_scores_gemma":[0.00006102526,0.00006635395,0.002743084,0.00000895236,0.00006719607,0.00001836716,0.0004235205,0.9908743,0.0001250179,0.005250421,0.0003430186,0.00001864043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634625,0.0003075509,0.02543996,0.003549352,0.00003849215,0.00006923066,0.0006347545,0.00007461672,0.006423481],"genre_scores_gemma":[0.9921517,0.0001364318,0.001892664,0.00008119248,0.00002727439,0.00004397711,0.0001950416,0.00002005653,0.005451754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09211731,"threshold_uncertainty_score":0.1831623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.115474572951367,"score_gpt":0.2637014616961473,"score_spread":0.1482268887447802,"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."}}