{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:5HRQYNDUTVTRD6G5JXVFMGGCKD","short_pith_number":"pith:5HRQYNDU","schema_version":"1.0","canonical_sha256":"e9e30c34749d6711f8dd4dea5618c250c1f41249ccc5c2a378fa50f4d66d39c5","source":{"kind":"arxiv","id":"1712.09089","version":10},"attestation_state":"computed","paper":{"title":"An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Kaspar W\\\"uthrich, Victor Chernozhukov, Yinchu Zhu","submitted_at":"2017-12-25T15:29:10Z","abstract_excerpt":"We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. We recast the causal inference problem as a counterfactual prediction and a structural breaks testing problem. This allows us to exploit insights from conformal prediction and structural breaks testing to develop permutation inference procedures that accommodate modern high-dimensional estimators, are valid under weak and easy-to-verify conditions, and are provably robust against misspecification. Our methods work in conjunction with many different approaches for predicting counterfact"},"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":"1712.09089","kind":"arxiv","version":10},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2017-12-25T15:29:10Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"0f0b48289bb56a561981a8bfc04c10e609796e796071f69059e29a0f8ccad0a9","abstract_canon_sha256":"9b68a4fa2ebebae25338f049c8d1d93355c659e084dde1b21d99f469806182e5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:51:02.554037Z","signature_b64":"p+0nyE8yOnFPr+/7UAZpZvNNG/xpShW/GuRPP2Tb4Jki7GDaWEmD3HL71X/Qg3ToVQeadqJ3vIqsLflETbrWDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e9e30c34749d6711f8dd4dea5618c250c1f41249ccc5c2a378fa50f4d66d39c5","last_reissued_at":"2026-07-05T03:51:02.553645Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:51:02.553645Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Kaspar W\\\"uthrich, Victor Chernozhukov, Yinchu Zhu","submitted_at":"2017-12-25T15:29:10Z","abstract_excerpt":"We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. We recast the causal inference problem as a counterfactual prediction and a structural breaks testing problem. This allows us to exploit insights from conformal prediction and structural breaks testing to develop permutation inference procedures that accommodate modern high-dimensional estimators, are valid under weak and easy-to-verify conditions, and are provably robust against misspecification. Our methods work in conjunction with many different approaches for predicting counterfact"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09089","kind":"arxiv","version":10},"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/1712.09089/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":"1712.09089","created_at":"2026-07-05T03:51:02.553700+00:00"},{"alias_kind":"arxiv_version","alias_value":"1712.09089v10","created_at":"2026-07-05T03:51:02.553700+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09089","created_at":"2026-07-05T03:51:02.553700+00:00"},{"alias_kind":"pith_short_12","alias_value":"5HRQYNDUTVTR","created_at":"2026-07-05T03:51:02.553700+00:00"},{"alias_kind":"pith_short_16","alias_value":"5HRQYNDUTVTRD6G5","created_at":"2026-07-05T03:51:02.553700+00:00"},{"alias_kind":"pith_short_8","alias_value":"5HRQYNDU","created_at":"2026-07-05T03:51:02.553700+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2602.04611","citing_title":"Targeted Synthetic Control Method","ref_index":3,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD","json":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD.json","graph_json":"https://pith.science/api/pith-number/5HRQYNDUTVTRD6G5JXVFMGGCKD/graph.json","events_json":"https://pith.science/api/pith-number/5HRQYNDUTVTRD6G5JXVFMGGCKD/events.json","paper":"https://pith.science/paper/5HRQYNDU"},"agent_actions":{"view_html":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD","download_json":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD.json","view_paper":"https://pith.science/paper/5HRQYNDU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1712.09089&json=true","fetch_graph":"https://pith.science/api/pith-number/5HRQYNDUTVTRD6G5JXVFMGGCKD/graph.json","fetch_events":"https://pith.science/api/pith-number/5HRQYNDUTVTRD6G5JXVFMGGCKD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD/action/storage_attestation","attest_author":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD/action/author_attestation","sign_citation":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD/action/citation_signature","submit_replication":"https://pith.science/pith/5HRQYNDUTVTRD6G5JXVFMGGCKD/action/replication_record"}},"created_at":"2026-07-05T03:51:02.553700+00:00","updated_at":"2026-07-05T03:51:02.553700+00:00"}