{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:YGEIWP3IM6SS2HBT3IFKP25GG4","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":"aed1d6d29c93c79bcedf2eb39ac922fb5e8cf512823c5966de80dc502b09db40","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2020-12-15T08:55:18Z","title_canon_sha256":"84acca360a71f9dce97c695b81609a12c7109d8b19c4e04c6647434247675def"},"schema_version":"1.0","source":{"id":"2012.08155","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.08155","created_at":"2026-07-05T03:36:52Z"},{"alias_kind":"arxiv_version","alias_value":"2012.08155v3","created_at":"2026-07-05T03:36:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.08155","created_at":"2026-07-05T03:36:52Z"},{"alias_kind":"pith_short_12","alias_value":"YGEIWP3IM6SS","created_at":"2026-07-05T03:36:52Z"},{"alias_kind":"pith_short_16","alias_value":"YGEIWP3IM6SS2HBT","created_at":"2026-07-05T03:36:52Z"},{"alias_kind":"pith_short_8","alias_value":"YGEIWP3I","created_at":"2026-07-05T03:36:52Z"}],"graph_snapshots":[{"event_id":"sha256:14b9e7a5f7f385e6f7d34f27eabbaa716c40064c712b74d33345e23b63aac2a9","target":"graph","created_at":"2026-07-05T03:36:52Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2012.08155/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we assess whether using non-linear dimension reduction techniques pays off for forecasting inflation in real-time. Several recent methods from the machine learning literature are adopted to map a large dimensional dataset into a lower dimensional set of latent factors. We model the relationship between inflation and the latent factors using constant and time-varying parameter (TVP) regressions with shrinkage priors. Our models are then used to forecast monthly US inflation in real-time. The results suggest that sophisticated dimension reduction methods yield inflation forecasts ","authors_text":"Florian Huber, Karin Klieber, Niko Hauzenberger","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2020-12-15T08:55:18Z","title":"Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.08155","kind":"arxiv","version":3},"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":"sha256:92b43cd9a033d5f305b2e55f4a1b4e1546345d929caeabcb64f3b2d1f974e899","target":"record","created_at":"2026-07-05T03:36:52Z","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":"aed1d6d29c93c79bcedf2eb39ac922fb5e8cf512823c5966de80dc502b09db40","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2020-12-15T08:55:18Z","title_canon_sha256":"84acca360a71f9dce97c695b81609a12c7109d8b19c4e04c6647434247675def"},"schema_version":"1.0","source":{"id":"2012.08155","kind":"arxiv","version":3}},"canonical_sha256":"c1888b3f6867a52d1c33da0aa7eba63721550a8ada9d252854151e6df0af9147","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1888b3f6867a52d1c33da0aa7eba63721550a8ada9d252854151e6df0af9147","first_computed_at":"2026-07-05T03:36:52.499879Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:36:52.499879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Neu0r08dBKid3JX9cgyOxRsaBGWOitvzTw35mQhxz2AzRBkl5UGJh5OwqwOa1L0FfQybXZjtl18B/EzbFbApAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:36:52.500389Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.08155","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:92b43cd9a033d5f305b2e55f4a1b4e1546345d929caeabcb64f3b2d1f974e899","sha256:14b9e7a5f7f385e6f7d34f27eabbaa716c40064c712b74d33345e23b63aac2a9"],"state_sha256":"9f641b0a62052717551e96bc986604b12c0503841e342565e8a4ed1255aa4710"}