Predictive economics: Rethinking economic methodology with machine learning

Miguel Alves Pereira

Papers from arXiv.org

Abstract: This article proposes predictive economics as a distinct analytical perspective within economics, grounded in machine learning and centred on predictive accuracy rather than causal identification. Drawing on the instrumentalist tradition (Friedman), the explanation-prediction divide (Shmueli), and the contrast between modelling cultures (Breiman), we formalise prediction as a valid epistemological and methodological objective. Reviewing recent applications across economic subfields, we show how predictive models contribute to empirical analysis, particularly in complex or data-rich contexts. This perspective complements existing approaches and supports a more pluralistic methodology - one that values out-of-sample performance alongside interpretability and theoretical structure.

Date: 2025-10
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2510.04726

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