{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2009:TKU7M3NAKK54MP2QMRNPPESHOF","short_pith_number":"pith:TKU7M3NA","canonical_record":{"source":{"id":"0904.0951","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2009-04-06T15:17:37Z","cross_cats_sorted":["econ.EM","stat.AP"],"title_canon_sha256":"7a04f5257de30c19da7faa2ddc9adfef68064e8006f4184a657864f60a1d6b48","abstract_canon_sha256":"8b501af8d4b580e9b8bbf53034f675da5845112c41dde5acb456ab2ebecba602"},"schema_version":"1.0"},"canonical_sha256":"9aa9f66da052bbc63f50645af792477174155f6beb12f1f3d678872a3102a1a5","source":{"kind":"arxiv","id":"0904.0951","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0904.0951","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"arxiv_version","alias_value":"0904.0951v6","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0904.0951","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"pith_short_12","alias_value":"TKU7M3NAKK54","created_at":"2026-05-18T12:26:01Z"},{"alias_kind":"pith_short_16","alias_value":"TKU7M3NAKK54MP2Q","created_at":"2026-05-18T12:26:01Z"},{"alias_kind":"pith_short_8","alias_value":"TKU7M3NA","created_at":"2026-05-18T12:26:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2009:TKU7M3NAKK54MP2QMRNPPESHOF","target":"record","payload":{"canonical_record":{"source":{"id":"0904.0951","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2009-04-06T15:17:37Z","cross_cats_sorted":["econ.EM","stat.AP"],"title_canon_sha256":"7a04f5257de30c19da7faa2ddc9adfef68064e8006f4184a657864f60a1d6b48","abstract_canon_sha256":"8b501af8d4b580e9b8bbf53034f675da5845112c41dde5acb456ab2ebecba602"},"schema_version":"1.0"},"canonical_sha256":"9aa9f66da052bbc63f50645af792477174155f6beb12f1f3d678872a3102a1a5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:54.193802Z","signature_b64":"GRNzRdt7rho11LNclvVUsFm/BlPuPsC/x6m3Gp7U0N89SNZ2EgcZjZb6RIfDHQFhTUh3DwjJi4QT8AI5nOADCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9aa9f66da052bbc63f50645af792477174155f6beb12f1f3d678872a3102a1a5","last_reissued_at":"2026-05-18T00:29:54.193187Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:54.193187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"0904.0951","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HvM3fbY+x0QqdlIKaD9k13YuMv8FZIeRWALz+D8vGlTuibIdsAiEVCqYpq4MvaqDqAYAKocRLJY3W1UWhcP9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:18:06.089158Z"},"content_sha256":"bb7d01736bc462b1f6a637afc4072a79f238804d6bda540163dfc3a7b9538d43","schema_version":"1.0","event_id":"sha256:bb7d01736bc462b1f6a637afc4072a79f238804d6bda540163dfc3a7b9538d43"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2009:TKU7M3NAKK54MP2QMRNPPESHOF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inference on Counterfactual Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.EM","stat.AP"],"primary_cat":"stat.ME","authors_text":"Blaise Melly, Ivan Fernandez-Val, Victor Chernozhukov","submitted_at":"2009-04-06T15:17:37Z","abstract_excerpt":"Counterfactual distributions are important ingredients for policy analysis and decomposition analysis in empirical economics. In this article we develop modeling and inference tools for counterfactual distributions based on regression methods. The counterfactual scenarios that we consider consist of ceteris paribus changes in either the distribution of covariates related to the outcome of interest or the conditional distribution of the outcome given covariates. For either of these scenarios we derive joint functional central limit theorems and bootstrap validity results for regression-based es"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0904.0951","kind":"arxiv","version":6},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nEfMQwLlUKJvfAEt1KXpZ8IEEsawQICmMu5wwtGjPokk9w4GFbAFm8rqiYzty1c4jPnezXNaQC8IO9NmnwXYDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:18:06.089831Z"},"content_sha256":"9e170ed52be0fc023e75f760fd74af39829b99559da8a24ebeb61430580f9010","schema_version":"1.0","event_id":"sha256:9e170ed52be0fc023e75f760fd74af39829b99559da8a24ebeb61430580f9010"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TKU7M3NAKK54MP2QMRNPPESHOF/bundle.json","state_url":"https://pith.science/pith/TKU7M3NAKK54MP2QMRNPPESHOF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TKU7M3NAKK54MP2QMRNPPESHOF/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-31T08:18:06Z","links":{"resolver":"https://pith.science/pith/TKU7M3NAKK54MP2QMRNPPESHOF","bundle":"https://pith.science/pith/TKU7M3NAKK54MP2QMRNPPESHOF/bundle.json","state":"https://pith.science/pith/TKU7M3NAKK54MP2QMRNPPESHOF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TKU7M3NAKK54MP2QMRNPPESHOF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2009:TKU7M3NAKK54MP2QMRNPPESHOF","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8b501af8d4b580e9b8bbf53034f675da5845112c41dde5acb456ab2ebecba602","cross_cats_sorted":["econ.EM","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2009-04-06T15:17:37Z","title_canon_sha256":"7a04f5257de30c19da7faa2ddc9adfef68064e8006f4184a657864f60a1d6b48"},"schema_version":"1.0","source":{"id":"0904.0951","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0904.0951","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"arxiv_version","alias_value":"0904.0951v6","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0904.0951","created_at":"2026-05-18T00:29:54Z"},{"alias_kind":"pith_short_12","alias_value":"TKU7M3NAKK54","created_at":"2026-05-18T12:26:01Z"},{"alias_kind":"pith_short_16","alias_value":"TKU7M3NAKK54MP2Q","created_at":"2026-05-18T12:26:01Z"},{"alias_kind":"pith_short_8","alias_value":"TKU7M3NA","created_at":"2026-05-18T12:26:01Z"}],"graph_snapshots":[{"event_id":"sha256:9e170ed52be0fc023e75f760fd74af39829b99559da8a24ebeb61430580f9010","target":"graph","created_at":"2026-05-18T00:29:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Counterfactual distributions are important ingredients for policy analysis and decomposition analysis in empirical economics. In this article we develop modeling and inference tools for counterfactual distributions based on regression methods. The counterfactual scenarios that we consider consist of ceteris paribus changes in either the distribution of covariates related to the outcome of interest or the conditional distribution of the outcome given covariates. For either of these scenarios we derive joint functional central limit theorems and bootstrap validity results for regression-based es","authors_text":"Blaise Melly, Ivan Fernandez-Val, Victor Chernozhukov","cross_cats":["econ.EM","stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2009-04-06T15:17:37Z","title":"Inference on Counterfactual Distributions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0904.0951","kind":"arxiv","version":6},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:bb7d01736bc462b1f6a637afc4072a79f238804d6bda540163dfc3a7b9538d43","target":"record","created_at":"2026-05-18T00:29:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8b501af8d4b580e9b8bbf53034f675da5845112c41dde5acb456ab2ebecba602","cross_cats_sorted":["econ.EM","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2009-04-06T15:17:37Z","title_canon_sha256":"7a04f5257de30c19da7faa2ddc9adfef68064e8006f4184a657864f60a1d6b48"},"schema_version":"1.0","source":{"id":"0904.0951","kind":"arxiv","version":6}},"canonical_sha256":"9aa9f66da052bbc63f50645af792477174155f6beb12f1f3d678872a3102a1a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9aa9f66da052bbc63f50645af792477174155f6beb12f1f3d678872a3102a1a5","first_computed_at":"2026-05-18T00:29:54.193187Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:54.193187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GRNzRdt7rho11LNclvVUsFm/BlPuPsC/x6m3Gp7U0N89SNZ2EgcZjZb6RIfDHQFhTUh3DwjJi4QT8AI5nOADCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:54.193802Z","signed_message":"canonical_sha256_bytes"},"source_id":"0904.0951","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb7d01736bc462b1f6a637afc4072a79f238804d6bda540163dfc3a7b9538d43","sha256:9e170ed52be0fc023e75f760fd74af39829b99559da8a24ebeb61430580f9010"],"state_sha256":"7530d713034b4de5fab9e84342fad261a803f0a1188d1272ba7d2c41c3c09b34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2QUbawBx/w4xR1Ppm2eN8mflQL7npPqN3I1/+uE0y79NIj2XcqcVehSYD4Io+J/3D0TPSA+rTmUCQUKv2duIAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T08:18:06.093269Z","bundle_sha256":"3c0d7e9ccec4fc3b885b9f3797fda217de6355d07c4229bd6abbe3dfd22dc3bb"}}