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Using agents to build economic datasets

Economy

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开始于 May 12, 2026

Constructing datasets from primary sources is one of the costliest tasks in empirical economics. We propose Deep Research on a Loop (DRIL), a methodology that uses AI agents to assemble datasets from publicly available sources. DRIL applies a fixed research instrument across a mapped unit space (e.g., countries by years), with a two-stage architecture separating […] The post Using agents to build economic datasets appeared first on Marginal REVOLUTION. CommentsDon't get me wrong; I think this...

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Using agents to build economic datasets

Marginal Revolution (United States) | May 12, 2026

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CLAIM 发布者 admin • May 12, 2026

The DRIL methodology can significantly reduce the costs of data collection in economics, enabling more researchers to participate in empirical studies.

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CLAIM 发布者 admin • May 12, 2026

While DRIL offers efficiency, it raises questions about the reliability and accuracy of datasets assembled by AI without human oversight.

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CLAIM 发布者 admin • May 12, 2026

Relying on AI agents for dataset construction may overlook the nuances of human judgment, leading to potential biases in economic analysis.

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CLAIM 发布者 admin • May 12, 2026

Using AI agents like DRIL could democratize access to economic data, allowing smaller institutions to conduct meaningful research.

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CLAIM 发布者 admin • May 12, 2026

The implementation of DRIL could lead to a homogenization of data sources, limiting the diversity of perspectives in economic research.

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