{"paper":{"title":"Machine-learned patterns suggest that diversification drives economic development","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.GN","q-fin.EC"],"primary_cat":"physics.soc-ph","authors_text":"Andres Gomez-Lievano, Charles D. Brummitt, Matthew H. Bonds, Ricardo Hausmann","submitted_at":"2018-12-09T18:00:46Z","abstract_excerpt":"We develop a machine-learning-based method, Principal Smooth-Dynamics Analysis (PriSDA), to identify patterns in economic development and to automate the development of new theory of economic dynamics. Traditionally, economic growth is modeled with a few aggregate quantities derived from simplified theoretical models. Here, PriSDA identifies important quantities. Applied to 55 years of data on countries' exports, PriSDA finds that what most distinguishes countries' export baskets is their diversity, with extra weight assigned to more sophisticated products. The weights are consistent with prev"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03534","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}