{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:J627P6EJQ42DLSYOY4DG745KCW","short_pith_number":"pith:J627P6EJ","schema_version":"1.0","canonical_sha256":"4fb5f7f889873435cb0ec7066ff3aa1589dfe502db617a23e13c02c7a17b193f","source":{"kind":"arxiv","id":"1804.03349","version":1},"attestation_state":"computed","paper":{"title":"Inference on Local Average Treatment Effects for Misclassified Treatment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"econ.EM","authors_text":"Takahide Yanagi","submitted_at":"2018-04-10T05:57:30Z","abstract_excerpt":"We develop point-identification for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is non-classical by construction. We correct the problem by identifying the distribution of the measurement error based on the use of an exogenous variable that can even be a binary covariate. The moment conditions derived from the identification lead to generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations and an e"},"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":"1804.03349","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2018-04-10T05:57:30Z","cross_cats_sorted":[],"title_canon_sha256":"b34fd650134a46b86440c994ac2cd3943609adecb51b6e1fbb1a1ec511477e07","abstract_canon_sha256":"2f04a8343dd57036413be94fe2a778f8d2754f23973c5ad900bd1cac6f87dc5d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:56.330044Z","signature_b64":"N0FR/4eDWVViJ43ZJ+cguthNCVTHZ3mmcD8WiGAVrBeAL/zlkVKTNDt2Ep7Fj7S33xVh1tUQU9N1WHMYCi3KBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4fb5f7f889873435cb0ec7066ff3aa1589dfe502db617a23e13c02c7a17b193f","last_reissued_at":"2026-05-18T00:18:56.329646Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:56.329646Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Inference on Local Average Treatment Effects for Misclassified Treatment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"econ.EM","authors_text":"Takahide Yanagi","submitted_at":"2018-04-10T05:57:30Z","abstract_excerpt":"We develop point-identification for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is non-classical by construction. We correct the problem by identifying the distribution of the measurement error based on the use of an exogenous variable that can even be a binary covariate. The moment conditions derived from the identification lead to generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations and an e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.03349","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":"1804.03349","created_at":"2026-05-18T00:18:56.329711+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.03349v1","created_at":"2026-05-18T00:18:56.329711+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.03349","created_at":"2026-05-18T00:18:56.329711+00:00"},{"alias_kind":"pith_short_12","alias_value":"J627P6EJQ42D","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_16","alias_value":"J627P6EJQ42DLSYO","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_8","alias_value":"J627P6EJ","created_at":"2026-05-18T12:32:31.084164+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/J627P6EJQ42DLSYOY4DG745KCW","json":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW.json","graph_json":"https://pith.science/api/pith-number/J627P6EJQ42DLSYOY4DG745KCW/graph.json","events_json":"https://pith.science/api/pith-number/J627P6EJQ42DLSYOY4DG745KCW/events.json","paper":"https://pith.science/paper/J627P6EJ"},"agent_actions":{"view_html":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW","download_json":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW.json","view_paper":"https://pith.science/paper/J627P6EJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.03349&json=true","fetch_graph":"https://pith.science/api/pith-number/J627P6EJQ42DLSYOY4DG745KCW/graph.json","fetch_events":"https://pith.science/api/pith-number/J627P6EJQ42DLSYOY4DG745KCW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW/action/storage_attestation","attest_author":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW/action/author_attestation","sign_citation":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW/action/citation_signature","submit_replication":"https://pith.science/pith/J627P6EJQ42DLSYOY4DG745KCW/action/replication_record"}},"created_at":"2026-05-18T00:18:56.329711+00:00","updated_at":"2026-05-18T00:18:56.329711+00:00"}