Guidance for the use of AI in the meta‐analysis of economics research

  • Meta-analysis is widely accepted to be the most rigorous and objective approach to the synthesis, interpretation, and understanding of findings from specific areas of empirical economics research. With the advent of increasingly capable generative artificial intelligence and AI's potential to transform the practice of meta-analysis, the Meta-Analysis of Economics Research Network (MAER-Net) has adopted this set of principles. These principles are meant to provide guidance to meta-researchers, as well as editors and reviewers, in the use of AI in meta-analysis of economics research. Future meta-analyses that employ AI are expected to embody these guiding principles and to follow the associated Reporting Guidelines for Meta-Analysis in Economics - Updated for AI (Cook et al. 2026).

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Metadaten
Author:Nikolai Cook, František Bartoš, Pedro R. D. Bom, Sebastian Gechert, Klára Kantová, Jerome Geyer‐KlingebergORCiDGND, Tomáš Havránek, Zuzana Irsova, Martina Luskova, Matěj Opatrný, Franz Prante, Heiko J. Rachinger, T. D. Stanley
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/129880
ISSN:0950-0804OPAC
ISSN:1467-6419OPAC
Parent Title (English):Journal of Economic Surveys
Publisher:Wiley
Place of publication:Weinheim
Type:Article
Language:English
Year of first Publication:2026
Publishing Institution:Universität Augsburg
Release Date:2026/04/22
DOI:https://doi.org/10.1111/joes.70105
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Professur für Applied Data Analysis
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Latest Publications (not yet published in print):Aktuelle Publikationen (noch nicht gedruckt erschienen)
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung