This chapter introduces conviction narratives to analyze decision-making under radical uncertainty, enhancing economic policy insights.
Economics has no theory as to how people act when no probabilities are available to judge the successful outcome of their actions, as in radical uncertainty. Yet most significant economic policy decisions fit this context and the lack of a theory puts economics outside other human sciences, which recognise the need for knowledge to be represented in human minds before it can be acted on. In this chapter, which begins by reviewing why neither standard nor behavioural theory have hitherto addressed the issue at any depth, conviction narrative theory is introduced. Conviction narratives are mental representations which allow individual decision-makers faced with radical uncertainty to extract relevant information from their extended social networks so as to decide on the ‘rightness’ of what to do and to feel convinced enough about it to act. Because these narratives are extracted from narratives circulating in social networks, they can be studied to capture change at both individual and aggregate levels of the economy. In this way they open new possibilities for economic analysis and data collection as well as policy advice.
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David Tuckett (2026) studied this question.
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