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NBER opens applications for March 31 PhD workshop on growth policy, including AI

According to a post on X by @nberpubs, NBER is inviting PhD students to its PhD Student Workshop on Microeconomic Policies and Economic Growth, set for March 31, 2027 in Washington, D.C. The workshop will bring together about 30 dissertation-stage economists working on nine policy areas, including AI policy and high-skilled immigration. Travel is reimbursed, and applications are due at 11:59 PM ET on December 16. The post also describes the workshop as a funded opportunity for young economists studying AI's growth effects.

Source: Scobleizer News Pulse (X) · x.com Found via Robert Scoble’s Scobleizer News Pulse · a post on X, not independently verified Published 2026-11-10T20:45:00+00:00 Detected 2026-11-11T02:18:53+00:00
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According to a post on X by @nberpubs, NBER is inviting PhD students to its PhD Student Workshop on Microeconomic Policies and Economic Growth, set for March 31, 2027 in Washington, D.C. The workshop will bring together about 30 dissertation-stage economists working on nine policy areas, including AI policy and high-skilled immigration. Travel is reimbursed, and applications are due at 11:59 PM ET on December 16. The post also describes the workshop as a funded opportunity for young economists studying AI's growth effects.

AI-assisted summary based on the listed source.

NBER's PhD Student Workshop on Microeconomic Policies & Economic Growth, on Mar 31, 2027 in Washington, D.C., will take about 30 dissertation-stage economists working on nine policy areas, including AI policy and high-skilled immigration. Travel is reimbursed, and applications are due 11:59 PM ET on Dec 16. Why it...

Economists at the dissertation stage who study AI's economic impact could gain a funded chance to present and network in the policy field. Research groups and policy teams may also watch which AI-related growth questions attract attention from the profession. Applicants should check the December 16 deadline and the workshop's scope before applying.

Signal Strength 82% Technical label WATCH Public Interest 22 Category DEVELOPING Reader Depth GENERAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 0 Novelty Interest Score 70 Consequence Score 26 Curiosity Score 0 Shareability Score 41

VQV surfaced this signal because it is recent, relevant to AI Policy & Society, connected to Scobleizer News Pulse (X).