Measuring Brexit Uncertainty: A Machine Learning and Textual Analysis Approach

Wanyu Chung, Duiyi Dai and Robert Elliott ()

No 17410, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: In this paper we develop a series of Brexit uncertainty indices (BUI) based on UK newspaper coverage. Using unsupervised machine learning (ML) methods to automatically select topics, our main contribution is to generate timely and cost-effective indicators of uncertainty. In further analysis we are able to distinguish Brexit related uncertainty from the uncertainly due to COVID-19. Our indices can be used to investigate Brexit-related uncertainties across different policy areas.

Keywords: Brexit; Uncertainty; Machine learning (search for similar items in EconPapers)
JEL-codes: D80 E66 F50 (search for similar items in EconPapers)
Date: 2022-06
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