The Covid shock has created substantial and unprecedented challenges for monetary policymakers. This post summarises the key literature on the immediate monetary policy response to the shock, including both tools and short to medium-term strategy issues (but leaving aside the longer-term question of fiscal-monetary interactions).
This post contributes to our occasional series of guest posts by external researchers who have used the Bank of England’s archives for their work on subjects outside traditional central banking topics.
In 1944, the Bank of England’s historian, John Clapham, looked back at the ways in which the Bank had changed since 1914 and remarked:
‘ . . . it would not be fantastic to argue that the Bank in 1944 was further . . . from 1914 than 1914 was from 1714.’
The Coronavirus pandemic and measures to contain contagion had far reaching consequences on economic activities, which also led to a sharp fall in CO2 emissions. This has sparked new debate about how the recovery from the crisis could be made compatible with the Paris climate goals. In this post, I survey the emerging literature on the link between the economic recovery from the aftermath of the pandemic and climate change.
Can Gao, Ian Martin, Arjun Mahalingam and Nicholas Vause
Since Covid-19-related crashes in March, major stock indices around the world have bounced back. This is despite little or no recovery in corporate earnings expectations. As a result, forward-looking price-to-earnings ratios have increased, rising above long-run average values in most large advanced economies and approaching record highs in the United States. Commenting on such valuations, some market participants have suggested there is ‘a great deal of optimism priced into the market’ and that stock prices ‘cannot defy economic gravity indefinitely’. This post takes a closer look at stock valuations, focusing on the UK, and drawing both on a textbook model and new research from academia.
Since the tumultuous events of 2007, much work has suggested that financial shocks are the main driver of economic fluctuations. In a recent paper, I propose a novel strategy to identify financial disturbances. I use the evolution of loan finance relative to bond finance to proxy for firms’ credit conditions and single out the shocks born in the financial sector. I apply and test the method for the US economy. I obtain three key results. First, financial shocks account for around a third of the US business cycle. Second, these shocks occur around precise events such as the Japanese crisis and the Great Recession. Third, the financial shocks I obtain are predictive of the corporate bond spread.
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.
Imagine you’ve booked tickets for a flight, and go to pick them up and pay for them on the day. You arrive at the airport but find out the airline has overbooked, and already given your ticket away. Worse yet, because you’ve missed this flight you’re going to miss an onward connection. But, you’ll likely get a replacement ticket in a day or two as compensation.
What was the root cause of the financial crisis? Ask any economist or banker and undoubtedly they will at some point mention leverage (see e.g. here, here and here). Yet when a capital requirement based on leverage — the leverage ratio requirement — was introduced, fierce criticism followed (see e.g. here and here). Drawing on the insights from a working paper, and thinking about the main criticism — that a leverage ratio requirement could cause excessive risk-taking — this seems not to have been the case.
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.