How easy is it to understand this sentence you are currently reading? How easy it is to understand this sentence that has dependency arcs that are longer that make it more difficult to read? How about if my writing is magniloquent? Or what if I use normal words? Writing style matters for how easy it is to read text. This post asks if writing style can influence how long markets take to digest Bank of England monetary policy information. I find that Bank of England publications that summarise their content in the first sentence, and use less unexpected vocabulary, are associated with a faster time for swap markets to reach a new equilibrium price following the publication release.
The Citizens’ Panels (now the Citizens’ Forum) is a Bank of England discussion forum to engage with the UK public on important topics such as the labour and housing markets, or climate change. It included a forecasting competition, and Bank Underground invited the winners to contribute short pieces about how they evaluate the UK economy, discuss issues of their concern, and to propose solutions.
Part of Bank Underground’s purpose is to give a platform for views from Bank of England (‘Bank’) analysts that may differ from those of the Bank or its policy committees. Alternative views are encouraged within the Bank, but the range of opinions and ways of thinking by analysts is likely to be limited to some extent: by education, experience and less tangible factors such as the language analysts use to explain their thoughts. The Citizens’ Panels therefore offer a rich source of information. By now, they include some 3,200+ participants with a wide range of backgrounds: some are familiar with economics and central banking but many may know little about either. This blog represents the voices of some of those panel members about the UK economy, and how they addressed the forecasting challenge, which we put in front of participants as part of the Citizens’ Forum online community – which by-the-way is open to all.
Reforms following the 2008 financial crisis have led to significant increases in banks’ capital requirements. A large literature since then has focused on understanding how banks respond to these changes. Our new paper shows that pre-reform profitability is a vital, but often overlooked, driver of banks’ responses. Profitability determines the opportunity cost of shrinking assets, and underpins the ability to generate capital. We develop a stylised model which predicts that a more profitable bank would choose to shrink by less (or grow by more) compared to a less profitable bank in response to higher capital requirements. Combining textual analysis of banks’ annual reports with the assessment of a key too big to fail (TBTF) reform, we show that this prediction holds in practice.
What can the history and philosophy of science teach us about regulatory reform? In this post, we borrow Thomas Kuhn’s idea of ‘scientific revolutions’ to argue that radical overhauls of regulation often occur after crises but that, once major reforms have been completed, it’s normal to have periods when rules do not change so much. For instance, major reforms made to banking regulations after the Global Financial Crisis of 2007–08 are now coming to an end with future change likely to be more incremental. This post is about why different circumstances call for these different approaches to regulatory change.
Joel Suss, David Bholat, Alex Gillespie and Tom Reader
‘Bad cultures’ at banks are often blamed for scandals and crises, from the global financial crisis to the mis-selling of payment protection insurance (PPI) in the UK. Yet surprisingly little research has tested this claim. This is because quantifying culture is difficult to do. Our working paper gives it a go. Leveraging unique access to data available to regulators, we diagnose the cultural health of the UK banking sector. We find that banks with organisational cultures two standard deviations below the sector average are associated with a 50% increased risk of failure.
Ivan Yotzov, Nick Bloom, Philip Bunn, Paul Mizen, Pawel Smietanka and Greg Thwaites
Text data is often raw and unstructured, and yet it is the key means of human communication. Textual analysis techniques are increasingly being used in economic and financial research in a variety of different ways. In this post we apply these techniques to a new setting: the text comments left by respondents to the Decision Maker Panel (DMP) Survey, a UK-wide monthly business survey. Using over 20,000 comments, we show that: (i) these comments are a rich and unexplored data source, (ii) Brexit has been the dominant topic of comments since 2016, (iii) text-based indices match existing uncertainty measures from the DMP at both the aggregate and firm level, and (iii) sentiment among UK firms has been declining since 2016.
Giorgis Hadzilacos, Ryan Li, Paul Harrington, Shane Latchman, John Hillier, Richard Dixon, Charlie New, Alex Alabaster and Tanya Tsapko
The 2015/16 storms caused the most extreme flooding on record, with parts of the UK impacted by heavy precipitation and extreme wind over a four-month period. These extreme weather events occurred in quick succession, hindering relief efforts and accruing £1.3 billion in insured losses. Without adequate mitigation, such events may result in claims handling strain and capital risk for insurers. Recent research finds that above-average windstorm seasons are typically accompanied by above-average inland flooding. That raises a challenge for insurers: should they have adequate risk mitigation measures in place for periods that are both windy and wet? We argue that insurers need to reassess their model assumptions, especially as climate change might make wet years more frequent than in the past.
The right stance for monetary policy is highly uncertain, and so it is no surprise that members of monetary policy committees – like the Bank of England’s Monetary Policy Committee (MPC) – regularly disagree about the best course of action. Asking a committee to decide allows different opinions to be aired and challenged, with a majority vote needed to determine policy. But how should we expect those disagreements and votes to change in periods of higher uncertainty? Should we expect more 9–0 unanimous votes? Or more 5–4 close contests? We address these questions in this post and find that the degree of disagreement is little changed in periods of high uncertainty, and nor are dissenting votes. There is, however, some difference in how voting decisions are formed when uncertain, with both individual and committee-wide views having less explanatory power for votes.
Marcus Buckmann, Paula Gallego Marquez, Mariana Gimpelewicz and Sujit Kapadia
Bank failures are very costly for society. Following the 2007/2008 global financial crisis, international regulators introduced a package of new banking regulations, known as Basel III. This includes a wider range of capital and liquidity requirements to protect banks from different risks. But could the additional complexity be unnecessary or even increase risks, as some have argued? In a recent staff working paper, we assess the value of multiple regulatory requirements by examining how different combinations of metrics might have helped prior to the 2007/2008 crisis in gauging banks that subsequently failed. Our results generally support the case for a small portfolio of different regulatory metrics: having belts and braces (or suspenders) can strengthen the resilience of the banking system.
Data plays a central role in all technical aspects of insurance and actuarial work. However, utilisation is often still confined to aggregate premium and claims data. Not so in the case of telematics. Say the phrase ‘black box’ and most people will think of flight recorders fitted to aircraft. But Motor insurers also use the millions of data points generated by black boxes, fitted to more than a million cars in the UK, to price risks. What’s more Marine insurers are getting in on the act. In this post we take an actuarial vantage to explore the use of telematics data and consider whether insurers could be using this ‘gold mine’ of information even more widely.