{"paper":{"title":"A World of Ginis","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["q-fin.EC","stat.AP"],"primary_cat":"econ.GN","authors_text":"Lidia Ceriani, Paolo Verme","submitted_at":"2026-07-27T09:00:40Z","abstract_excerpt":"The Gini index remains the most important measure of economic inequality worldwide, and accurate estimates of this index are essential for effective public policies. Yet, Gini estimates for the same country and year vary considerably across data sources, a problem that remains largely unresolved. The paper reviews the largest global and regional databases providing Gini estimates, surveys the related literature, and constructs a unified dataset of 122,351 Gini observations spanning 222 countries and territories and 158 years, from 1867 to 2024. The analysis of this new dataset shows that incom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.24175","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.24175/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"}