Machine learning the news for better macroeconomic forecasting

Arthur Turrell, Eleni Kalamara, Chris Redl, George Kapetanios and Sujit Kapadia

Every day, journalists collate information about the world and, with nimble keystrokes, re-express it succinctly as newspaper copy. Events about the macroeconomy are no exception. So could there be additional valuable information about the economy contained in the news? In a recent research paper, we ask whether newspaper stories could help to predict future macroeconomic developments. We find that news can be used to enhance statistical economic forecasts of growth, inflation and unemployment — but only by using supervised machine learning techniques. We also find that the biggest forecast improvements occur when it matters most — during stressed periods.

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Wir sind die Roboter: can we predict financial crises?

Kristina Bluwstein, Marcus Buckmann, Andreas Joseph, Miao Kang, Sujit Kapadia and Özgür Şimşek

Financial crises are recurrent events in economic history. But they are as rare as a Kraftwerk album, making their prediction challenging. In a recent study, we apply robots — in the form of machine learning — to a long-run dataset spanning 140 years, 17 countries and almost 50 crises, successfully predicting almost all crises up to two years ahead. We identify the key economic drivers of our models using Shapley values. The most important predictors are credit growth and the yield curve slope, both domestically and globally. A flat or inverted yield curve is of most concern when interest rates are low and credit growth is high. In such zones of heightened crisis vulnerability, it may be valuable to deploy macroprudential policies.

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The language of rules: textual complexity in banking reforms

Zahid Amadxarif, James Brookes, Nicola Garbarino, Rajan Patel and Eryk Walczak

The banking reforms that followed the financial crisis of 2007-08 led to an increase in UK banking regulation from almost 400,000 to over 720,000 words. Did the increase in the length of regulation lead to an increase in complexity?

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Covid-19 briefing: epi-macro 101

Cristiano Cantore, Federico Di Pace, Riccardo M Masolo, Silvia Miranda-Agrippino and Arthur Turrell

The Covid-19 crisis has led to a swift shift in the emphasis of macroeconomic research. At the centre of this is a new field of inquiry called ‘epi-macro’ that combines epidemiological models with macroeconomic models. In this post, we give a brief introduction to some of the earliest papers in this fast-growing literature.

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Setting boundaries: finding thresholds in bank regulation

Zahid Amadxarif, Paula Gallego Marquez and Nic Garbarino

“We’ve done a lot to lower prudential barriers to entry into the banking sector […] but have we done enough to lower the equivalent barriers to growth?” asked PRA CEO Sam Woods in a recent speech. To make regulation proportionate, policymakers adapt regulatory requirements to the risks posed by each firm. But regulators face a trade-off between addressing systemic risks in a proportionate way and limiting regulatory complexity. New thresholds can create complexity and cliff-edge effects that can discourage healthy firms from growing. We identify regulatory thresholds for UK banks and building societies using textual analysis on a new dataset that contains the universe of prudential rules.

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Thinking historically

Austen Saunders

Central banks want to learn from history. They can do so by drawing on decades of work by economic historians, as well as their own archives which manifest layers of institutional memory. But the path from page to policy can be difficult to find. Central banks need therefore to invest in the capacity of their own staff to think historically. This will help them use evidence from the past to make better decisions in the future. In practice, this means producing historical research as well as consuming it. Institutions like central banks need to be fluent participants in the conversations which bridge the distance between past and present.

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Covid-19 briefing: post-lockdown macro

Michael Kumhof

In the wake of Covid-19 lockdown, macroeconomic policymakers have to deal not only with the immediate contraction in the economy, but also with the medium and longer term macro-consequences. Over the past four months, the macroeconomic literature on these topics has expanded rapidly. This post reviews the literature that considers the channels via which the shock affects the economy, and the macroeconomic policy options for dealing with the aftermath, taking as given the shock caused by the virus and the lockdown.

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Loss aversion: the concept every supplier should be utilising to tackle climate change

India Loader, South Wilts Grammar School

India Loader, from South Wilts Grammar School, is the winner of the third Bank of England/Financial Times schools blog competition. The competition invited students across the UK to write a post on the theme: the economy and climate change.

To help save the planet and gain a competitive edge, cafes should obey a basic rule of behavioural economics by switching from offering discounts for customers who bring their own cups in favour of charging more for disposable ones.

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Thrive or dive: can our economy weather the climate crisis?

Marco Minasi-Smith, Fortismere School, London

Marco Minasi-Smith, from Fortismere School, London, is the runner-up of the third Bank of England/Financial Times schools blog competition. The competition invited students across the UK to write a post on the theme: the economy and climate change.

While Australia mourns the human and ecological cost of its ‘black summer’ of fires, the tragedy poses a question for economic policy-makers everywhere: how do we prevent climate crises becoming economic ones?

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