{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:P5QQS6B7M25VDT3HEWMAF43DDC","short_pith_number":"pith:P5QQS6B7","schema_version":"1.0","canonical_sha256":"7f6109783f66bb51cf67259802f3631894fb0ddf067c39402ed0e14ea8e99973","source":{"kind":"arxiv","id":"2011.03593","version":3},"attestation_state":"computed","paper":{"title":"Instrumented Difference-in-Differences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Ashkan Ertefaie, Dylan S. Small, James Flory, Sean Hennessy, Ting Ye","submitted_at":"2020-11-06T20:49:40Z","abstract_excerpt":"Unmeasured confounding is a key threat to reliable causal inference based on observational studies. Motivated from two powerful natural experiment devices, the instrumental variables and difference-in-differences, we propose a new method called instrumented difference-in-differences that explicitly leverages exogenous randomness in an exposure trend to estimate the average and conditional average treatment effect in the presence of unmeasured confounding. We develop the identification assumptions using the potential outcomes framework. We propose a Wald estimator and a class of multiply robust"},"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":"2011.03593","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-11-06T20:49:40Z","cross_cats_sorted":[],"title_canon_sha256":"4867c642f211b3ef76f8d0354c504c774c86714f5699e16f6df01088d9048bcc","abstract_canon_sha256":"f376c5e08c27fb7e273582877a27080cdbf091d83eba850ff02211a3181b870d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:29:46.517377Z","signature_b64":"3+nIaCIGjjhnaNbWepXw6woRt/vq01Y/BUt9uokk0rMsH5iAogm7GmPrHwR1OmNttf8SbrVt/bgiFqDM8+UsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f6109783f66bb51cf67259802f3631894fb0ddf067c39402ed0e14ea8e99973","last_reissued_at":"2026-07-05T03:29:46.516995Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:29:46.516995Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Instrumented Difference-in-Differences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Ashkan Ertefaie, Dylan S. Small, James Flory, Sean Hennessy, Ting Ye","submitted_at":"2020-11-06T20:49:40Z","abstract_excerpt":"Unmeasured confounding is a key threat to reliable causal inference based on observational studies. Motivated from two powerful natural experiment devices, the instrumental variables and difference-in-differences, we propose a new method called instrumented difference-in-differences that explicitly leverages exogenous randomness in an exposure trend to estimate the average and conditional average treatment effect in the presence of unmeasured confounding. We develop the identification assumptions using the potential outcomes framework. We propose a Wald estimator and a class of multiply robust"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.03593","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/2011.03593/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":"2011.03593","created_at":"2026-07-05T03:29:46.517054+00:00"},{"alias_kind":"arxiv_version","alias_value":"2011.03593v3","created_at":"2026-07-05T03:29:46.517054+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.03593","created_at":"2026-07-05T03:29:46.517054+00:00"},{"alias_kind":"pith_short_12","alias_value":"P5QQS6B7M25V","created_at":"2026-07-05T03:29:46.517054+00:00"},{"alias_kind":"pith_short_16","alias_value":"P5QQS6B7M25VDT3H","created_at":"2026-07-05T03:29:46.517054+00:00"},{"alias_kind":"pith_short_8","alias_value":"P5QQS6B7","created_at":"2026-07-05T03:29:46.517054+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/P5QQS6B7M25VDT3HEWMAF43DDC","json":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC.json","graph_json":"https://pith.science/api/pith-number/P5QQS6B7M25VDT3HEWMAF43DDC/graph.json","events_json":"https://pith.science/api/pith-number/P5QQS6B7M25VDT3HEWMAF43DDC/events.json","paper":"https://pith.science/paper/P5QQS6B7"},"agent_actions":{"view_html":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC","download_json":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC.json","view_paper":"https://pith.science/paper/P5QQS6B7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2011.03593&json=true","fetch_graph":"https://pith.science/api/pith-number/P5QQS6B7M25VDT3HEWMAF43DDC/graph.json","fetch_events":"https://pith.science/api/pith-number/P5QQS6B7M25VDT3HEWMAF43DDC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC/action/storage_attestation","attest_author":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC/action/author_attestation","sign_citation":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC/action/citation_signature","submit_replication":"https://pith.science/pith/P5QQS6B7M25VDT3HEWMAF43DDC/action/replication_record"}},"created_at":"2026-07-05T03:29:46.517054+00:00","updated_at":"2026-07-05T03:29:46.517054+00:00"}