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Claim LD03-SL-C21 (v1.0)

Across 56 economies and 16 industries, industries more exposed to generative AI grew faster in 2022–23 where countries were better prepared for AI, which the authors read as generative AI likely benefiting advanced economies more than emerging ones and widening global income disparities in the near term.

Provenance and status

Claim type
ESTIMATE (as printed: “ESTIMATE”)
Publication status
ELIGIBLE (WORKING_PAPER) (as printed: “ELIGIBLE WITH WORKING-PAPER QUALIFIER”)
Verification state
CONTENT_VERIFIED_PRIMARY (as printed: “CONTENT VERIFIED”; verified by: UNKNOWN)
Does not license
Total factor productivity; observed adoption; long-run effects
Source (field 6, as printed)
Gambacorta, Kharroubi, Mehrotra & Oliviero, “Artificial intelligence and growth in advanced and emerging economies: short-run impact,” BIS Working Papers No 1321, December 2025
Source type (field 7)
WORKING_PAPER (as printed: “Academic working paper”)
Institutional position
Mixed
Maturity (claim evidence / publication maturity)
EMERGING (as printed: “EMERGING”)
Recorded date
2026-10-15
Currentness / correction
This is the current version. No correction or concern relation is recorded on its Sources.

Version

Current version v1.0, resolved through the explicit current pointer CLAIM--LD03-SL-C21.

Versions:v1.0 · current

Pinned Sources (field 6, version-specific)

All 25 canonical Claim fields (raw values and normalized values)
#Canonical fieldCanonical value (verbatim)Normalized (Claim Value Vocabulary v1.0.2)
1CLAIM IDLD03-SL-C21—
2PUBLIC-FACING CLAIMAcross 56 economies and 16 industries, industries more exposed to generative AI grew faster in 2022–23 where countries were better prepared for AI, which the authors read as generative AI likely benefiting advanced economies more than emerging ones and widening global income disparities in the near term.—
3CLAIM TYPEESTIMATEbase_types: ESTIMATE
4RESEARCH STRANDD — Aggregate estimates and theory—
5MATURITYEMERGINGstates: EMERGING
6SOURCEGambacorta, Kharroubi, Mehrotra & Oliviero, “Artificial intelligence and growth in advanced and emerging economies: short-run impact,” BIS Working Papers No 1321, December 2025source_ids: SRC-SL-GAMBACORTA-KHARROUBI-MEHROTRA-OLIVIERO-BIS-1321
7SOURCE TYPEAcademic working paperclasses: WORKING_PAPER
8INSTITUTIONAL POSITIONMixed—
9SCOPE56 economies, 16 industries; value-added growth in 2022–23—
10DESIGNCross-country, cross-industry interaction design (Rajan–Zingales style) with country and industry fixed effects—
11SAMPLE / DATASETIndustry-country value-added data—
12MODEL / TOOL / VERSIONGenerative AI (predicted exposure, not observed use)—
13COMPARATORLess exposed industries; less prepared countries—
14MAIN RESULTGrowth differential of about two percentage points between high- and low-exposure sectors for a one-standard-deviation increase in AI preparedness; benefits likely larger in advanced economies—
15INFERENTIAL TARGETWhether early growth effects of generative AI differ by country readiness—
16DOES NOT LICENSETotal factor productivity; observed adoption; long-run effects—
17VERIFICATION STATECONTENT VERIFIEDstate: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18LIMITATIONSAssociational, over one year, using predicted exposure benchmarked on the US; results in value added, and the authors leave conversion to productivity to future work; BIS is an international organization of central banks—
19CONTRADICTORY / SUPPORTING SOURCESConsistent with distributional readings of AI gains—
20GEOGRAPHY / LANGUAGEMulti-country—
21DISTRIBUTIONAL LEDGERAdvanced economies gain more than emerging economies—
22R01 / FIELD-MAP LINKSLD-03, D2—
23WHAT WOULD CHANGE THIS CLAIM?Later years or observed adoption data reversing the pattern—
24PUBLICATION STATUSELIGIBLE WITH WORKING-PAPER QUALIFIERstate: ELIGIBLE · qualifiers: WORKING_PAPER
25RECORDED DATE2026-10-15—

Field 22 references resolved against Field Map v0.2: LD-03 (LIVING_DEBATE); D2 (DOMAIN)

Cited by Living Debate versions

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 9cdc729324371d4d5e6fb26ad6e6e2a1a3a05e3d9f50489e918305f3c5e4e8a6.

Repository-authored inputs (not Drive exports)

  • SocioLens claim — LD03-SL-C21 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts. Block “ENTRY 21 — LD03-SL-C21” SHA-256 f7fb59bbf219d16e7e15dcc35b25e5dab743ff284c707cab29cf36a597bcefb0; fixture fixtures/authored/claims/LD03-SL-C21--v1.0.

Builder decisions (not Drive data)

  • VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD03-SL-C21 v1.0); the first version of a new Claim of the LD-03 debate
  • CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD03-SL-C21 v1.0" (Project Lead (Claude, AI), 2026-10-15); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts
  • FIELD_6_SOURCE_REFERENCE = SRC-SL-GAMBACORTA-KHARROUBI-MEHROTRA-OLIVIERO-BIS-1321--v1.0 — basis: field 6 of ENTRY 21 — LD03-SL-C21 cites "Gambacorta, Kharroubi, Mehrotra & Oliviero, “Artificial intelligence and growth in advanced and emerging economies: short-run impact,” BIS Working Papers No 1321, December 2025"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
  • SOURCE_PROVENANCE_PIN = SRC-SL-GAMBACORTA-KHARROUBI-MEHROTRA-OLIVIERO-BIS-1321--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Gambacorta, Kharroubi, Mehrotra & Oliviero, “Artificial intelligence and growth in advanced and emerging economies: short-run impact,” BIS Working Papers No 1321, December 2025".