Choose an institution to see its records and dossier, or choose a topic.
Through year 2027 · all records, including scheduled dates 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2008 2005 1965 Show Organisations and infrastructure All types Organisation Person Document Concept Infrastructure Public body Reset filters
94 people, organisations and other records · 122 relationships · 34 claims about a valueEverything recorded up to the chosen year, whether or not still in effect · Undated records included
Claim and evidence Close ×
Aghion, Jones, Jones, “Artificial Intelligence and Economic Growth” (2017-10) bears on M06a. Argues that Baumol's cost disease can keep the labour share substantial even as automation advances. Copy claim link
Copy claim reference
Machine-checked, not reviewed by an editor Stated in source Supported
Supporting evidence: primary · 1 source
Date 2017-10 · publication Role Context Register (kind of text) Nonfiction Missing element A model in which the labour share stays substantial despite nearly complete automation; it does not state a fall for some workers, though the paper also notes a possible prolonged high-capital-share period. Tier Tier 1. NBER working paper (core venue). Conditions Elasticity of substitution across tasks below one; automation exogenous; sufficient conditions for balanced growth with a constant capital share well below 100%. Scope and limits NBER Working Paper 23928, October 2017 (NBER Conference on AI paper; later a chapter in The Economics of Artificial Intelligence). Model result under stated conditions.
The evidence 01 primary source Supports the claim
Artificial Intelligence and Economic Growth ↗ NBER Working Paper 23928 · 2017-10
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “The labor share remains substantial because of Baumol's insight: growth is determined not by what we are good at but rather by what is essential and yet hard to improve.” Location in source pdf page 47; section 7 Conclusion (printed p. 46)
Machine-checked · 2026-10-14
Source details and check notes Authors Philippe Aghion; Benjamin F. Jones; Charles I. Jones Version Full text. Current copy retrieved directly on 2026-10-09; no archive capture (Wayback unreachable), so earlier bytes are not authenticated. SHA-256 a8e68273c738c80fe565afa60bc27ec5e8aaf3135011a0f760233896f1f2100c. Canonical address Open the canonical source ↗ Accessed 2026-10-09 Language English (en) Attribution Philippe Aghion, Benjamin F. Jones, Charles I. Jones, “Artificial Intelligence and Economic Growth”, NBER Working Paper 23928, 2017-10. 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 M06a-11 (research/economics-mainstream). The quotation (30 words) matched the retrieved current copy (SHA-256 a8e68273c738c80fe565afa60bc27ec5e8aaf3135011a0f760233896f1f2100c) in the pack's verification. Re-checked at admission on 2026-10-14 against a copy retrieved that day. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document bears on the proposition without meeting its criterion; the record names the missing element. It is not an articulation and implies no influence.
Date. Cover "October 2017". Chapter in the NBER Economics of AI volume (2019). Checked in a current copy; an archive capture was not available, so earlier bytes are not authenticated.
Record ID ec-m06a-aghion-jones-jones-2017-ai-and-economic-growth-b