{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:KZXZBRSOMQYN5U7TBUJ3KK7GHN","short_pith_number":"pith:KZXZBRSO","schema_version":"1.0","canonical_sha256":"566f90c64e6430ded3f30d13b52be63b4bf95648f8bd8702cec16ae31c93c601","source":{"kind":"arxiv","id":"1010.4345","version":5},"attestation_state":"computed","paper":{"title":"Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.EM","math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Alexandre Belloni, Christian Hansen, Daniel Chen, Victor Chernozhukov","submitted_at":"2010-10-21T00:49:43Z","abstract_excerpt":"We develop results for the use of Lasso and Post-Lasso methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, $p$. Our results apply even when $p$ is much larger than the sample size, $n$. We show that the IV estimator based on using Lasso or Post-Lasso in the first stage is root-n consistent and asymptotically normal when the first-stage is approximately sparse; i.e. when the conditional expectation of the endogenous variables given the instruments can be well-approximated by a relatively small set of variab"},"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":"1010.4345","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2010-10-21T00:49:43Z","cross_cats_sorted":["econ.EM","math.ST","stat.TH"],"title_canon_sha256":"8c06a40b2c92e4e08d28b0492c4037de5a7a7ebdcfc73c77f5a7b3e3d3ef2649","abstract_canon_sha256":"96056c0a7fc54112c84510221112999a938cd27fa09ada6df15fbdbd23be2d43"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:44.552056Z","signature_b64":"NDmYmJSw7iMfc3kpUxt2CDVZJjQvPJStoYtAX/p67E4mtfLkIkXOkyvSKcCjk6vu4oE40iCZvyGQj5UzEtFiDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"566f90c64e6430ded3f30d13b52be63b4bf95648f8bd8702cec16ae31c93c601","last_reissued_at":"2026-05-18T00:33:44.551419Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:44.551419Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.EM","math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Alexandre Belloni, Christian Hansen, Daniel Chen, Victor Chernozhukov","submitted_at":"2010-10-21T00:49:43Z","abstract_excerpt":"We develop results for the use of Lasso and Post-Lasso methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, $p$. Our results apply even when $p$ is much larger than the sample size, $n$. We show that the IV estimator based on using Lasso or Post-Lasso in the first stage is root-n consistent and asymptotically normal when the first-stage is approximately sparse; i.e. when the conditional expectation of the endogenous variables given the instruments can be well-approximated by a relatively small set of variab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1010.4345","kind":"arxiv","version":5},"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":"1010.4345","created_at":"2026-05-18T00:33:44.551523+00:00"},{"alias_kind":"arxiv_version","alias_value":"1010.4345v5","created_at":"2026-05-18T00:33:44.551523+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1010.4345","created_at":"2026-05-18T00:33:44.551523+00:00"},{"alias_kind":"pith_short_12","alias_value":"KZXZBRSOMQYN","created_at":"2026-05-18T12:26:09.077623+00:00"},{"alias_kind":"pith_short_16","alias_value":"KZXZBRSOMQYN5U7T","created_at":"2026-05-18T12:26:09.077623+00:00"},{"alias_kind":"pith_short_8","alias_value":"KZXZBRSO","created_at":"2026-05-18T12:26:09.077623+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/KZXZBRSOMQYN5U7TBUJ3KK7GHN","json":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN.json","graph_json":"https://pith.science/api/pith-number/KZXZBRSOMQYN5U7TBUJ3KK7GHN/graph.json","events_json":"https://pith.science/api/pith-number/KZXZBRSOMQYN5U7TBUJ3KK7GHN/events.json","paper":"https://pith.science/paper/KZXZBRSO"},"agent_actions":{"view_html":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN","download_json":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN.json","view_paper":"https://pith.science/paper/KZXZBRSO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1010.4345&json=true","fetch_graph":"https://pith.science/api/pith-number/KZXZBRSOMQYN5U7TBUJ3KK7GHN/graph.json","fetch_events":"https://pith.science/api/pith-number/KZXZBRSOMQYN5U7TBUJ3KK7GHN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN/action/storage_attestation","attest_author":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN/action/author_attestation","sign_citation":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN/action/citation_signature","submit_replication":"https://pith.science/pith/KZXZBRSOMQYN5U7TBUJ3KK7GHN/action/replication_record"}},"created_at":"2026-05-18T00:33:44.551523+00:00","updated_at":"2026-05-18T00:33:44.551523+00:00"}