Discussion paper

DP17410 Measuring Brexit Uncertainty: A Machine Learning and Textual Analysis Approach

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.

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Citation

Chung, W, D Dai and R Elliott (eds) (2022), “DP17410 Measuring Brexit Uncertainty: A Machine Learning and Textual Analysis Approach”, CEPR Press Discussion Paper No. 17410. https://cepr.org/publications/dp17410