TITLE:
What Future for Economics? Rethinking Rationality, Models and Academic Incentives
AUTHORS:
Tommaso De Portu
KEYWORDS:
Bounded Rationality, Economics, Causal Inference, Machine Learning, Reproducibility, Transparency, Academic Incentives
JOURNAL NAME:
Theoretical Economics Letters,
Vol.15 No.6,
November
26,
2025
ABSTRACT: The standard assumption of rationality in economics has been a theoretical convenience rather than an adequate description of human decision processes for decades. The future of economics, however, requires reframing rationality: behavioural economics has long proven that the set of elements informing choices is numerous, often unobserved, and context dependent. This reframing exacerbates the well-known statistical trade-off between overfitting vs. omitted variable bias, that is, an interpretability cost. Whilst on one hand newly available and extremely granular data sources enable new analysis and novel results, these are often limited to the assumptions of limited applicability, hindering scientific value. This paradigm shift calls for a reassessment of models, data practices and academic incentives.