Machine Learning for Economic Policy

Maryam Haghighi, Andreas Joseph, George Kapetanios, Christopher Kurz, Michele Lenza and Juri Marcucci

Journal of Econometrics, 2025, vol. 249, issue PC

Abstract: The Themed Issue Machine Learning for Economic Policy consists of 12 papers at the intersection of machine learning, nontraditional data sources and economic policymaking. We will introduce the Themed Issue and review its contributions.

Keywords: Machine learning; Nontraditional data; Big data; Text mining; Text-as-data; Text analysis; Natural language processing; Artificial intelligence; Data science; High-dimensional time series; Networks (search for similar items in EconPapers)
JEL-codes: C45 C53 C54 C55 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:249:y:2025:i:pc:s0304407625000247

DOI: 10.1016/j.jeconom.2025.105970

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