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In Bank of England Staff Working Paper No. 674 of September 2017, Chiranjit Chakraborty and Andreas Joseph introduce machine learning for central banking and policy analysis, present a case study projecting UK CPI inflation, and write that machine-learning models generally outperform traditional approaches in prediction tasks. Copy claim link
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Date 2017-09 · publication Records dated 2017 → Role Articulation Register (kind of text) Nonfiction Scope and limits A staff working paper with the authors’ disclaimer; the authors also state that open questions remain about causal inference. Their result is from their own case studies, not an adopted forecasting practice.
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Machine learning at central banks (Staff Working Paper No. 674) ↗ Bank of England · 2017-09
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Source excerpt “We introduce machine learning in the context of central banking and policy analyses.” Location in source PDF p. 2, Abstract
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Chiranjit Chakraborty; Andreas Joseph Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 51eb4af7fa56e58d9a2d057dc51dda146ebb4842c98c8c1e87e1b667c14b425f). Retrieved again at admission on 2026-11-06 (same file). PDF of Staff Working Paper No. 674, September 2017, as served on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Chiranjit Chakraborty, Andreas Joseph, “Machine learning at central banks (Staff Working Paper No. 674)”, 2017-09. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The quotation (13 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. primary source Supports the claim
Machine learning at central banks (Staff Working Paper No. 674) ↗ Bank of England · 2017-09
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Source excerpt “Machine learning models generally outperform traditional modelling approaches in prediction tasks, while open research questions remain with regard to their causal inference properties.” Location in source PDF p. 2, Abstract
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Chiranjit Chakraborty; Andreas Joseph Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 51eb4af7fa56e58d9a2d057dc51dda146ebb4842c98c8c1e87e1b667c14b425f). Retrieved again at admission on 2026-11-06 (same file). PDF of Staff Working Paper No. 674, September 2017, as served on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Chiranjit Chakraborty, Andreas Joseph, “Machine learning at central banks (Staff Working Paper No. 674)”, 2017-09. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The quotation (23 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. primary source Context only
Machine learning at central banks (Staff Working Paper No. 674) ↗ Bank of England · 2017-09
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Source excerpt “The views expressed in this paper are those of the authors, and not necessarily those of the Bank of England or any of its committees.” Location in source PDF p. 2 (abstract page), first footnote block
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Chiranjit Chakraborty; Andreas Joseph Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 51eb4af7fa56e58d9a2d057dc51dda146ebb4842c98c8c1e87e1b667c14b425f). Retrieved again at admission on 2026-11-06 (same file). PDF of Staff Working Paper No. 674, September 2017, as served on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Chiranjit Chakraborty, Andreas Joseph, “Machine learning at central banks (Staff Working Paper No. 674)”, 2017-09. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The text’s own statement of whose views it gives, shown beside the record; it is context, not support. The quotation matched a fresh retrieval of 2026-11-06. No human editorial review. Status and meaning Editorial status. Machine-checked . Machines found this record and checked it against its sources; no person accepted it individually. Each evidence record above shows how it was checked.
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Record ID am-u05-boe-2017-swp674-ml-central-banks