经济学家

The paper's central contribution is showing that AI-driven automation creates what economists call a demand externality — a situation where one company's decision imposes costs on other companies that the first company doesn't have to pay.

This page is part of a larger set of rankings for research items, serials, authors and institutions made available on this site. A FAQ is available · The data presented here are experimental. They are based on a sample of the research output in Economics and Finance.

Artificial intelligence (AI) isn’t just a risk to jobs—Goldman Sachs Research estimates that it also increases the number of jobs in some sectors. Our economists find that, in occupations where workers face a high risk of being substituted by AI, jobs are being lost.

In a working paper published this week, a team of researchers surveyed economists about their outlook over the next five and 25 years. Most expect the economy to grow a bit more quickly as A.I. improves, but not to diverge substantially from historical patterns.

how economists conduct research. This overview provides a methodological introduction and practical · guide to AI agents in economic research. We first discuss the conceptual and theoretical frameworks · underpinning AI agents – defining what constitutes an “AI agent,” exploring how multi-agent systems · and cognitive automation can augment research workflows, and addressing key considerations like

These models help to explain economic relationships and are used to develop forecasts related to the nature and length of business cycles, the effects of a specific rate of inflation on the economy, the effects of tax legislation on unemployment levels, and other economic phenomena. Many economists have applied these fundamental areas of economics to more narrow areas with specific applications such as health, education, agriculture, urban and regional economics, law, history, energy, and the environment.

In 2023, MIT researchers claimed AI implementation could increase a worker’s performance by nearly 40% compared to workers who didn’t use the technology. But emerging data failing to show these promised productivity gains has led economists to wonder when—or if—AI will offer a return on corporate investments, which swelled to more than $250 billion in 2024.

A curated list of AI tools, libraries, and resources transforming how economists conduct research, teach, and analyze policy — from natural language data access to causal machine learning.

We completed the most comprehensive study of how economists and AI experts think AI will affect the U.S. economy. They predict major AI progress—but no dramatic break from economic trends: GDP growth rates similar to today’s and a moderate decline in labor force participation.

On average, economists assigned a 47 percent probability of “moderate“ AI progress by 2030, defined as systems that can operate semi-autonomous research labs, put out high-quality novels, and complete complex projects with oversight.