Theoretical paper critiques current behavioural economics, proposing new methods from complexity theory to enhance predictive power and realism in economic models.
The aim of this theoretical paper is to discuss the contemporary lines of criticism towards behavioural economics (BE) and propose ways in which BE can improve the predictive power and descriptive realism of economic models of human behaviour and financial markets at the aggregated level. BE was initially aimed to transform the paradigm of neoclassical economics, based predominantly on normative as if assumptions to a more realistic psychological background. However, at present BE is neither a real combination of economics and psychology nor a new distinctive economic paradigm. Moving beyond 'as if' BE requires adopting new data analysis methods from complexity theory and narrative economics. This shift would provide a more accurate, data-driven understanding of human economic decision-making in an increasingly complex world and how it may shape the economy at the aggregated level.
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Rzeszutek et al. (2025) studied this question.
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