{"paper":{"title":"Extracting Geography from Trade Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.soc-ph"],"primary_cat":"q-fin.TR","authors_text":"Nicholas Marshall, Stefan Steinerberger, Tianhao Wu, Yuke Li","submitted_at":"2016-07-18T18:43:09Z","abstract_excerpt":"Understanding international trade is a fundamental problem in economics -- one standard approach is via what is commonly called the \"gravity equation\", which predicts the total amount of trade $F_ij$ between two countries $i$ and $j$ as $$ F_{ij} = G \\frac{M_i M_j}{D_{ij}},$$ where $G$ is a constant, $M_i, M_j$ denote the \"economic mass\" (often simply the gross domestic product) and $D_{ij}$ the \"distance\" between countries $i$ and $j$, where \"distance\" is a complex notion that includes geographical, historical, linguistic and sociological components. We take the \\textit{inverse} route and ask"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.05235","kind":"arxiv","version":2},"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"}