Machine learning at central banks

Chiranjit Chakraborty and Andreas Joseph

No 674, Bank of England working papers from Bank of England

Abstract: We introduce machine learning in the context of central banking and policy analyses. Our aim is to give an overview broad enough to allow the reader to place machine learning within the wider range of statistical modelling and computational analyses, and provide an idea of its scope and limitations. We review the underlying technical sources and the nascent literature applying machine learning to economic and policy problems. We present popular modelling approaches, such as artificial neural networks, tree-based models, support vector machines, recommender systems and different clustering techniques. Important concepts like the bias-variance trade-off, optimal model complexity, regularisation and cross-validation are discussed to enrich the econometrics toolbox in their own right. We present three case studies relevant to central bank policy, financial regulation and economic modelling more widely. First, we model the detection of alerts on the balance sheets of financial institutions in the context of banking supervision. Second, we perform a projection exercise for UK CPI inflation on a medium-term horizon of two years. Here, we introduce a simple training-testing framework for time series analyses. Third, we investigate the funding patterns of technology start-ups with the aim to detect potentially disruptive innovators in financial technology. Machine learning models generally outperform traditional modelling approaches in prediction tasks, while open research questions remain with regard to their causal inference properties.

Keywords: Machine learning; artificial intelligence; big data; econometrics; forecasting; inflation; financial markets; banking supervision; financial technology (search for similar items in EconPapers)
JEL-codes: A12 A33 C14 C38 C44 C45 C51 C52 C53 C54 C55 C61 C63 C87 E37 E58 G17 Y20 (search for similar items in EconPapers)
Pages: 89 pages
Date: 2017-09-04
New Economics Papers: this item is included in nep-big, nep-cba, nep-cmp, nep-ecm, nep-mac and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (80)

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