{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CR2JJJ4JFE7IPG6CMLKWB42KJI","short_pith_number":"pith:CR2JJJ4J","canonical_record":{"source":{"id":"2404.08365","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"econ.EM","submitted_at":"2024-04-12T10:09:06Z","cross_cats_sorted":[],"title_canon_sha256":"dc9ba4579a3a1f1bc2ba2b76981317c647d7ebe1d7c73e776bbb78afa1ef77af","abstract_canon_sha256":"a6e76af40259b41dfed5ee5b92c024bcafdad793ce1ab42c98f754c5d0d9e019"},"schema_version":"1.0"},"canonical_sha256":"147494a789293e879bc262d560f34a4a389aa0ca0d47910cc46d0dcc429ff51e","source":{"kind":"arxiv","id":"2404.08365","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08365","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08365v2","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08365","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_12","alias_value":"CR2JJJ4JFE7I","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_16","alias_value":"CR2JJJ4JFE7IPG6C","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_8","alias_value":"CR2JJJ4J","created_at":"2026-07-05T09:06:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CR2JJJ4JFE7IPG6CMLKWB42KJI","target":"record","payload":{"canonical_record":{"source":{"id":"2404.08365","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"econ.EM","submitted_at":"2024-04-12T10:09:06Z","cross_cats_sorted":[],"title_canon_sha256":"dc9ba4579a3a1f1bc2ba2b76981317c647d7ebe1d7c73e776bbb78afa1ef77af","abstract_canon_sha256":"a6e76af40259b41dfed5ee5b92c024bcafdad793ce1ab42c98f754c5d0d9e019"},"schema_version":"1.0"},"canonical_sha256":"147494a789293e879bc262d560f34a4a389aa0ca0d47910cc46d0dcc429ff51e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:04.963120Z","signature_b64":"/+3BZ6qkbOFnJ1h5ZtyjahIp/dayuxPpMJKzR0X2Fe+BF27f3v+Zbh+2yH9m32ANeAHVYzP27dlC0aXLP5BVDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"147494a789293e879bc262d560f34a4a389aa0ca0d47910cc46d0dcc429ff51e","last_reissued_at":"2026-07-05T09:06:04.962656Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:04.962656Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.08365","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:06:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"68oSTzfYGLTsrNt2cu+mqs8VCFv/SYX/MFs/x8hszqt0xfo+LGrVSQ5dA3IUDgdQ85Vk82+ITevEAGOYcbCIDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T06:06:32.554851Z"},"content_sha256":"eedf49de21561c4c6354c80010b430af743721423967a5505fae4ed83bd4e73d","schema_version":"1.0","event_id":"sha256:eedf49de21561c4c6354c80010b430af743721423967a5505fae4ed83bd4e73d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CR2JJJ4JFE7IPG6CMLKWB42KJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Estimation and Inference for Three-Dimensional Panel Data Models","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"econ.EM","authors_text":"Bin Peng, Fei Liu, Guohua Feng, Jiti Gao","submitted_at":"2024-04-12T10:09:06Z","abstract_excerpt":"Hierarchical panel data models have recently garnered significant attention. This study contributes to the relevant literature by introducing a novel three-dimensional (3D) hierarchical panel data model, which integrates panel regression with three sets of latent factor structures: one set of global factors and two sets of local factors. Instead of aggregating latent factors from various nodes, as seen in the literature of distributed principal component analysis (PCA), we propose an estimation approach capable of recovering the parameters of interest and disentangling latent factors at differ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08365","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2404.08365/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:06:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n8zYOEWsgjdH7ddY6q5F76Mixy95R3i3vu8Banqx3mHBCHDcQDHNfVyakVU5cdDOWNdEDe2wqNINQjupO6JnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T06:06:32.555248Z"},"content_sha256":"da348830da659912b1c5f1115184d4de337eb73ec9c2ff9007fd2c550a9570b4","schema_version":"1.0","event_id":"sha256:da348830da659912b1c5f1115184d4de337eb73ec9c2ff9007fd2c550a9570b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/bundle.json","state_url":"https://pith.science/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-27T06:06:32Z","links":{"resolver":"https://pith.science/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI","bundle":"https://pith.science/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/bundle.json","state":"https://pith.science/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CR2JJJ4JFE7IPG6CMLKWB42KJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CR2JJJ4JFE7IPG6CMLKWB42KJI","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a6e76af40259b41dfed5ee5b92c024bcafdad793ce1ab42c98f754c5d0d9e019","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"econ.EM","submitted_at":"2024-04-12T10:09:06Z","title_canon_sha256":"dc9ba4579a3a1f1bc2ba2b76981317c647d7ebe1d7c73e776bbb78afa1ef77af"},"schema_version":"1.0","source":{"id":"2404.08365","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08365","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08365v2","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08365","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_12","alias_value":"CR2JJJ4JFE7I","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_16","alias_value":"CR2JJJ4JFE7IPG6C","created_at":"2026-07-05T09:06:04Z"},{"alias_kind":"pith_short_8","alias_value":"CR2JJJ4J","created_at":"2026-07-05T09:06:04Z"}],"graph_snapshots":[{"event_id":"sha256:da348830da659912b1c5f1115184d4de337eb73ec9c2ff9007fd2c550a9570b4","target":"graph","created_at":"2026-07-05T09:06:04Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2404.08365/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hierarchical panel data models have recently garnered significant attention. This study contributes to the relevant literature by introducing a novel three-dimensional (3D) hierarchical panel data model, which integrates panel regression with three sets of latent factor structures: one set of global factors and two sets of local factors. Instead of aggregating latent factors from various nodes, as seen in the literature of distributed principal component analysis (PCA), we propose an estimation approach capable of recovering the parameters of interest and disentangling latent factors at differ","authors_text":"Bin Peng, Fei Liu, Guohua Feng, Jiti Gao","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"econ.EM","submitted_at":"2024-04-12T10:09:06Z","title":"Estimation and Inference for Three-Dimensional Panel Data Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08365","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:eedf49de21561c4c6354c80010b430af743721423967a5505fae4ed83bd4e73d","target":"record","created_at":"2026-07-05T09:06:04Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a6e76af40259b41dfed5ee5b92c024bcafdad793ce1ab42c98f754c5d0d9e019","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"econ.EM","submitted_at":"2024-04-12T10:09:06Z","title_canon_sha256":"dc9ba4579a3a1f1bc2ba2b76981317c647d7ebe1d7c73e776bbb78afa1ef77af"},"schema_version":"1.0","source":{"id":"2404.08365","kind":"arxiv","version":2}},"canonical_sha256":"147494a789293e879bc262d560f34a4a389aa0ca0d47910cc46d0dcc429ff51e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"147494a789293e879bc262d560f34a4a389aa0ca0d47910cc46d0dcc429ff51e","first_computed_at":"2026-07-05T09:06:04.962656Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:06:04.962656Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/+3BZ6qkbOFnJ1h5ZtyjahIp/dayuxPpMJKzR0X2Fe+BF27f3v+Zbh+2yH9m32ANeAHVYzP27dlC0aXLP5BVDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:06:04.963120Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.08365","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eedf49de21561c4c6354c80010b430af743721423967a5505fae4ed83bd4e73d","sha256:da348830da659912b1c5f1115184d4de337eb73ec9c2ff9007fd2c550a9570b4"],"state_sha256":"9440d157cbd848cbd7062df6d528df6a968c0d8a0ebbe28dee11a996ed42440c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"htzQUCcQmuyye8/uLf+l2VMvkZQhcsOeFQFSlwtEcsjh60sWsNjJYFcbjzlQ2h+QP/ZImK8Xlb4rvY5mrjMUCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T06:06:32.557480Z","bundle_sha256":"44054e7f1b59b5def2b1acc1b64b85734037e6ac8a914ffa4943573672f9291d"}}