How Might Fiscal Policy Respond to the Rise of Artificial Intelligence? -- by Karen Dynan, Douglas Elmendorf, Louise Sheiner

2026-07-09 · Source: National Bureau of Economic Research Working Papers · Field: Finance & Economics — Economic Analysis & Policy, Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

The National Bureau of Economic Research (NBER) highlights a paper titled "How Might Fiscal Policy Respond to the Rise of Artificial Intelligence?" authored by Karen Dynan, Douglas Elmendorf, and Louise Sheiner. This research, featured within NBER's extensive collection of economic studies, likely examines the complex interplay between emerging AI technologies and governmental fiscal strategies. NBER's programs, such as Public Economics and Economics of AI and Digitization, provide a relevant context for this work, suggesting an analysis of taxation, public spending, and economic growth implications in an AI-driven future. The paper contributes to NBER's mission of promoting economic research and disseminating findings to policymakers and the public.

Key takeaway

For policymakers and economists considering the long-term economic impacts of AI, this NBER paper signals a critical area of emerging research. You should monitor NBER's publications for insights into how fiscal tools like taxation and public investment might need adaptation to address AI's effects on labor markets, productivity, and wealth distribution. This work underscores the necessity of proactive policy development.

Topics

• Fiscal Policy
• Artificial Intelligence
• Economic Research
• Taxation
• Public Economics
• Economic Fluctuations

Best for: Policy Maker, Research Scientist, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by National Bureau of Economic Research Working Papers.