{"id":"W2810619779","doi":"10.5539/ijef.v10n7p177","title":"Technical Efficiency and Technical Change in Africa: The Role of Money from the Diasporas","year":2018,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Ghana","keywords":"Technical change; Total factor productivity; Economics; Technical progress; Productivity; Panel data; Malmquist index; Technological change; Estimation; Index (typography); Econometrics; Demographic economics; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001392407,0.0002927838,0.0003147688,0.001177657,0.0005532251,0.001285624,0.0002117214,0.0002510807,0.00168759],"category_scores_gemma":[0.005097726,0.000109773,0.0002561444,0.001783215,0.0009521581,0.001311352,0.001200375,0.0003664536,0.0001637105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005043487,"about_ca_system_score_gemma":0.0004236539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004571442,"about_ca_topic_score_gemma":0.005597237,"domain_scores_codex":[0.9993917,0.0002379176,0.00004818209,0.00006472093,0.00006988744,0.0001875686],"domain_scores_gemma":[0.9961682,0.001442867,0.001656554,0.0002240814,0.0002609217,0.000247392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002149314,0.0001111643,0.9310177,0.0002004516,0.000167807,0.001685779,0.007495894,0.001419158,0.002092256,0.007634904,0.0002798386,0.04768019],"study_design_scores_gemma":[0.000005068303,0.00007074258,0.9879232,0.00009579497,0.00005403344,0.0002995891,0.005583621,0.0006703138,0.0008249633,0.001048307,0.003414081,0.00001039882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970973,0.000539473,0.0001819861,0.0001422566,0.00000247541,0.000004477616,0.00005836252,0.000001844726,0.001971768],"genre_scores_gemma":[0.9991891,0.0003372751,0.0001093927,0.00001502743,0.000005564536,0.000003302965,0.0000410734,0.000001415313,0.0002979098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004571442,"threshold_uncertainty_score":0.009089649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03202194960100543,"score_gpt":0.2303025903132659,"score_spread":0.1982806407122605,"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."}}