Muddled measurements on clarity

Charlie Warburton and James Brookes

Economists have repeatedly shown that readability of central banking communication matters. But they typically measure readability in a crude way – using the simplistic but influential Flesch-Kincaid metric. The Flesch-Kincaid Grade Level is based on word and sentence length and is commonly interpreted as the number of years of education required to understand a text. However, recent advances in computational linguistics toolkits empower us to consider finer-grained markers of language comprehension missed by Flesch-Kincaid. Here, we revisit Jansen (2011) which found that Fed Chair testimonies with lower Flesch-Kincaid Grade Level scores – indicating higher readability – were associated with lower market volatility. Our results show that compared to more sophisticated linguistic metrics, Flesch-Kincaid is a relatively poorer indicator of readability.

Continue reading →

Payments without borders: using ISO 20022 to identify cross-border payments in CHAPS

James Duffy and James Sanders

Understanding a payment’s journey around the globe can be difficult. As the operator of the UK’s high-value payment system (CHAPS), the Bank is all too familiar with this challenge. By leveraging the benefits of the newly introduced ISO 20022 standard for messaging, we have devised a new methodology to identify and classify cross-border CHAPS payments more effectively. This method reveals that international transactions form over half of CHAPS activity, and offers new insights into the global payment corridors for CHAPS payments. Gaining a deeper understanding of payment flows could assist policymakers in prioritising their efforts to reduce global barriers as they implement the G20 roadmap for enhancing cross-border payments.

Continue reading →

Leveraging language models for prudential supervision

Adam Muhtar and Dragos Gorduza

Imagine a world where machines can assist humans in navigating across complex financial rules. What was once far-fetched is rapidly becoming reality, particularly with the emergence of a class of deep learning models based on the Transformer architecture (Vaswani et al (2017)), representing a whole new paradigm to language modelling in recent times. These models form the bedrock of revolutionary technologies like large language models (LLMs), opening up new ways for regulators, such as the Bank of England, to analyse text data for prudential supervision and regulation.

Continue reading →

The transmission of macroprudential policy in the tails

Álvaro Fernández-Gallardo, Simon Lloyd and Ed Manuel

Since the 2007–09 Global Financial Crisis, central banks have developed a range of macroprudential policies (‘macropru’) to address fault lines in the financial system. A key aim of macropru is to reduce ‘left-tail risks‘ – ie, minimise the probability and severity of future economic crises. However, building this resilience could influence other parts of the GDP-growth distribution and so may not always be costless. In our Working Paper, we gauge these potential costs and benefits by estimating the effects of macropru on the entire GDP-growth distribution, and explore its transmission channels. We find that macropru is effective at reducing the variance of GDP growth, and that it does so by reducing the probability and severity of excessive credit booms.

Continue reading →

Fuelling the tail: inflation- and GDP-at-Risk with oil-supply shocks

Marco Garofalo, Simon Lloyd and Edward Manuel

The economic consequences of the Russia-Ukraine war have brought the importance of sharp changes in commodity prices, such as oil, to centre stage. While many have focused on understanding the impact of these developments on the central projection for the macroeconomic outlook, this post investigates the balance of risks arising from oil-supply shocks, asking: could these lead to more severe or persistent changes in output growth and inflation, in rare events? Through the lens of a simple statistical model of Inflation- and GDP-at-Risk, we quantify the macroeconomic risks to inflation and GDP growth associated with (exogenous) changes in oil supply, showing that these shocks have more pronounced effects on the upper tail of the inflation distribution than at the centre.

Continue reading →

Unknown measures: assessing uncertainty around UK inflation using a new Inflation-at-Risk model

Nikoleta Anesti, Marco Garofalo, Simon Lloyd, Edward Manuel and Julian Reynolds

Understanding and quantifying risks to the economic outlook is essential for effective monetary policymaking. In this post, we describe an ‘Inflation-at-Risk’ model, which helps us assess the uncertainty and balance of risks around the outlook for UK inflation, and understand how this uncertainty relates to underlying economic conditions. Using this data-driven approach, we find that higher inflation expectations are particularly important for driving upside risks to inflation, while a widening in economic slack is important for downside risks. Our model highlights that rising tail-risks can become visible before a turning point, making the approach a useful addition to economists’ forecasting toolkit.

Continue reading →

Dissecting UK service inflation via a neural network Phillips curve

Marcus Buckmann, Galina Potjagailo and Philip Schnattinger

Understanding the origins of currently high inflation is a challenge, since the effects from a range of large shocks are layered on top of each other. The rise of UK service price inflation to up to 6.9% in April might potentially reflect external shocks propagating to a wider range of prices and into domestic price pressures. In this blog post we disentangle what might have contributed to the rise in service inflation in the UK using a neural network enhanced with some economic intuition. Our analysis suggests that much of the increase stems from spillovers from goods prices and input costs, a build-up of service inflation inertia and wage effects, and a pick-up in inflation expectations.

Continue reading →

Flash loans, flash attacks, and the future of DeFi

Aidan Saggers, Lukas Alemu and Irina Mnohoghitnei

Decentralised Finance (DeFi) may seem a tempting option for those seeking financial gain, autonomy, and self-governance… But how safe is a world in which ‘code is law’? Closer inspection reveals an ecosystem experiencing several hacks, attacks, and fraud. Estimates show at least US$6.5 billion has been stolen since DeFi’s inception, and one particular DeFi feature is often at the centre of this theft – flash loans. Unlimited, ungoverned, and uncollateralised, flash loans give hackers the toolkit to highly leverage their potential attacks. The only cost is the gas fees required to send the transaction. In this blog post we consider the world of flash loans and their criminal counterpart – flash attacks.

Continue reading →

Booming entrepreneurship during the Covid-19 pandemic

Saleem Bahaj, Sophie Piton and Anthony Savagar

Recessions typically discourage entrepreneurs from starting new businesses. During the Great Recession, a ‘generation’ of start-ups went missing which contributed to a slow recovery in employment. Two years after the pandemic started, evidence for the UK suggests a very different story: the pandemic inspired many entrepreneurs to start new businesses and this supported the recovery in employment.

Continue reading →

What did we learn from working from home during Covid?

Lena Anayi, John Lewis and Misa Tanaka

Since the onset of Covid-19, firms and workers have adopted and adapted to new working arrangements, which involved some workers primarily or exclusively working from home (WFH). What lessons – if any – can be drawn from this experience to inform future of work? A previous blog post examined how WFH might affect productivity. This blog post reviews more recent research on the experience of WFH during Covid, and considers what can be learnt about the impact of WFH on time use, workplace interactions and productivity.

Continue reading →