Analysis reveals how granular data enhances policy responses in central banking, suggesting the need for improved quality and security measures.
Central banks are increasingly leveraging the vast amount of information available in modern societies. Granular datasets offer precision and insight that aggregation often masks, providing flexibility to address a broad spectrum of issues and enabling in-depth understanding of emerging behaviours for more targeted policy responses. Nevertheless, two important challenges persist: these datasets often lack the rigorous production processes and quality assessments of traditional macroeconomic statistics, and their value depends on coherent contextualisation within a policy framework. Fortunately, data science offers effective tools to tackle such issues. This paper describes how, in future, maximising granular data’s potential requires stringent security measures, quality assurance and transparent integration into policy making. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
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Brault et al. (2025) studied this question.
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