{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:FPH3XMUL6DXCNAGOJ4Y2GPSJQV","short_pith_number":"pith:FPH3XMUL","schema_version":"1.0","canonical_sha256":"2bcfbbb28bf0ee2680ce4f31a33e49856d77caccad652a1f18c920c1ca61e2a6","source":{"kind":"arxiv","id":"1904.06843","version":1},"attestation_state":"computed","paper":{"title":"Estimation of Cross-Sectional Dependence in Large Panels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Bo Zhang, Guangming Pan, Jiti Gao, Yanrong Yang","submitted_at":"2019-04-15T05:15:05Z","abstract_excerpt":"Accurate estimation for extent of cross{sectional dependence in large panel data analysis is paramount to further statistical analysis on the data under study. Grouping more data with weak relations (cross{sectional dependence) together often results in less efficient dimension reduction and worse forecasting. This paper describes cross-sectional dependence among a large number of objects (time series) via a factor model and parameterizes its extent in terms of strength of factor loadings. A new joint estimation method, benefiting from unique feature of dimension reduction for high dimensional"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1904.06843","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2019-04-15T05:15:05Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"bc981b1c55c0200eec9eb7a27823a5042122fd77bf5a3a525105e060b8600b2f","abstract_canon_sha256":"aecacd922d7a3d48a622717862117e16dff95818aabd65542f417520557f7d14"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:36.009683Z","signature_b64":"w3Ax75b2IotbfrdbvCXeHCsobDnRVOaELv2zG/YQKa4N3cFgfDia43HZ4jAdTkwTQ00Nt4uzKPWH5/su5+r0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2bcfbbb28bf0ee2680ce4f31a33e49856d77caccad652a1f18c920c1ca61e2a6","last_reissued_at":"2026-05-17T23:48:36.009041Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:36.009041Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Estimation of Cross-Sectional Dependence in Large Panels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Bo Zhang, Guangming Pan, Jiti Gao, Yanrong Yang","submitted_at":"2019-04-15T05:15:05Z","abstract_excerpt":"Accurate estimation for extent of cross{sectional dependence in large panel data analysis is paramount to further statistical analysis on the data under study. Grouping more data with weak relations (cross{sectional dependence) together often results in less efficient dimension reduction and worse forecasting. This paper describes cross-sectional dependence among a large number of objects (time series) via a factor model and parameterizes its extent in terms of strength of factor loadings. A new joint estimation method, benefiting from unique feature of dimension reduction for high dimensional"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06843","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1904.06843","created_at":"2026-05-17T23:48:36.009149+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.06843v1","created_at":"2026-05-17T23:48:36.009149+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06843","created_at":"2026-05-17T23:48:36.009149+00:00"},{"alias_kind":"pith_short_12","alias_value":"FPH3XMUL6DXC","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"FPH3XMUL6DXCNAGO","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"FPH3XMUL","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV","json":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV.json","graph_json":"https://pith.science/api/pith-number/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/graph.json","events_json":"https://pith.science/api/pith-number/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/events.json","paper":"https://pith.science/paper/FPH3XMUL"},"agent_actions":{"view_html":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV","download_json":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV.json","view_paper":"https://pith.science/paper/FPH3XMUL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.06843&json=true","fetch_graph":"https://pith.science/api/pith-number/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/graph.json","fetch_events":"https://pith.science/api/pith-number/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/action/storage_attestation","attest_author":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/action/author_attestation","sign_citation":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/action/citation_signature","submit_replication":"https://pith.science/pith/FPH3XMUL6DXCNAGOJ4Y2GPSJQV/action/replication_record"}},"created_at":"2026-05-17T23:48:36.009149+00:00","updated_at":"2026-05-17T23:48:36.009149+00:00"}