{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:63VIVQ6NY5SIMZJU3D7GYZEHUY","short_pith_number":"pith:63VIVQ6N","schema_version":"1.0","canonical_sha256":"f6ea8ac3cdc764866534d8fe6c6487a63f2a648e3917202c16c77493577dce33","source":{"kind":"arxiv","id":"2511.16029","version":3},"attestation_state":"computed","paper":{"title":"Possibilistic Instrumental Variable Regression with Potentially Invalid Instruments","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["econ.EM","math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Gregor Steiner, Jeremie Houssineau, Mark F.J. Steel","submitted_at":"2025-11-20T04:20:42Z","abstract_excerpt":"Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in practice. In this paper, we propose a novel method based on possibility theory that performs posterior inference on the treatment effect, conditional on a user-specified set of potential violations of the instrument exogeneity assumption. Our method can provide valid results even when only a single, potentially invalid, instrument is available. Crucially, and in contrast with existing methods, we prove a finite-sample"},"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":"2511.16029","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2025-11-20T04:20:42Z","cross_cats_sorted":["econ.EM","math.ST","stat.TH"],"title_canon_sha256":"fc030c93cea4f3dbefde3d6a9628b0b5b7a1686da6ba6681b6a82c6b03abe4a1","abstract_canon_sha256":"0da709d9d38acfd7a6d48bfced0c5ffdc0b3b3993b9fec0b513b6a667d5fe365"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T01:16:01.113576Z","signature_b64":"SXMhdINB8cTmorfXeUB7zinziVVv00N7CKfQ3/QdiRtWYtfxx76081otMwrrrA6ZUUXG8E7Uh9uD1MoxCmMpDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6ea8ac3cdc764866534d8fe6c6487a63f2a648e3917202c16c77493577dce33","last_reissued_at":"2026-07-07T01:16:01.112530Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T01:16:01.112530Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Possibilistic Instrumental Variable Regression with Potentially Invalid Instruments","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["econ.EM","math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Gregor Steiner, Jeremie Houssineau, Mark F.J. Steel","submitted_at":"2025-11-20T04:20:42Z","abstract_excerpt":"Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in practice. In this paper, we propose a novel method based on possibility theory that performs posterior inference on the treatment effect, conditional on a user-specified set of potential violations of the instrument exogeneity assumption. Our method can provide valid results even when only a single, potentially invalid, instrument is available. Crucially, and in contrast with existing methods, we prove a finite-sample"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.16029","kind":"arxiv","version":3},"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/2511.16029/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2511.16029","created_at":"2026-07-07T01:16:01.112659+00:00"},{"alias_kind":"arxiv_version","alias_value":"2511.16029v3","created_at":"2026-07-07T01:16:01.112659+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.16029","created_at":"2026-07-07T01:16:01.112659+00:00"},{"alias_kind":"pith_short_12","alias_value":"63VIVQ6NY5SI","created_at":"2026-07-07T01:16:01.112659+00:00"},{"alias_kind":"pith_short_16","alias_value":"63VIVQ6NY5SIMZJU","created_at":"2026-07-07T01:16:01.112659+00:00"},{"alias_kind":"pith_short_8","alias_value":"63VIVQ6N","created_at":"2026-07-07T01:16:01.112659+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/63VIVQ6NY5SIMZJU3D7GYZEHUY","json":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY.json","graph_json":"https://pith.science/api/pith-number/63VIVQ6NY5SIMZJU3D7GYZEHUY/graph.json","events_json":"https://pith.science/api/pith-number/63VIVQ6NY5SIMZJU3D7GYZEHUY/events.json","paper":"https://pith.science/paper/63VIVQ6N"},"agent_actions":{"view_html":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY","download_json":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY.json","view_paper":"https://pith.science/paper/63VIVQ6N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2511.16029&json=true","fetch_graph":"https://pith.science/api/pith-number/63VIVQ6NY5SIMZJU3D7GYZEHUY/graph.json","fetch_events":"https://pith.science/api/pith-number/63VIVQ6NY5SIMZJU3D7GYZEHUY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY/action/storage_attestation","attest_author":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY/action/author_attestation","sign_citation":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY/action/citation_signature","submit_replication":"https://pith.science/pith/63VIVQ6NY5SIMZJU3D7GYZEHUY/action/replication_record"}},"created_at":"2026-07-07T01:16:01.112659+00:00","updated_at":"2026-07-07T01:16:01.112659+00:00"}