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Applied Economics Letters Volume 28, 2021 - Issue 16
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Research Article

Improving econometric prediction by machine learning

Giovanni CerulliCNR-IRCRES, Research Institute on Sustainable Economic Growth, National Research Council of Italy, Rome, ItalyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-5892-3372
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Pages 1419-1425 | Published online: 14 Sep 2020

Citations (4)

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Mark E. Lokanan. (2023) Predicting money laundering sanctions using machine learning algorithms and artificial neural networks. Applied Economics Letters 0:0, pages 1-7.
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Articles from other publishers (3)

Giovanni Cerulli. (2023) Machine learning using Stata/Python. The Stata Journal: Promoting communications on statistics and Stata 22:4, pages 772-810.
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Roni Barak-Ventura, Manuel Ruiz Marín & Maurizio Porfiri. (2022) A spatiotemporal model of firearm ownership in the United States. Patterns 3:8, pages 100546.
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Hoon Jang. (2022) Predicting funded research project performance based on machine learning. Research Evaluation 31:2, pages 257-270.
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