Product progression: a machine learning approach to forecasting industrial upgrading.
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ABSTRACT:
SUBMITTER: Albora G
PROVIDER: S-EPMC9880377 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
Publications
Product progression: a machine learning approach to forecasting industrial upgrading.
Albora Giambattista G Pietronero Luciano L Tacchella Andrea A Zaccaria Andrea A
Scientific reports 20230127 1
Economic complexity methods, and in particular relatedness measures, lack a systematic evaluation and comparison framework. We argue that out-of-sample forecast exercises should play this role, and we compare various machine learning models to set the prediction benchmark. We find that the key object to forecast is the activation of new products, and that tree-based algorithms clearly outperform both the quite strong auto-correlation benchmark and the other supervised algorithms. Interestingly, ...[more]
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