This blog discusses the impact of economic uncertainty on euro-area activity. To do that, we built on the methodology developed for the UK by Haddow et al. (2013). Our analysis suggests that elevated economic uncertainty has been an important driver of euro-area GDP during the financial and sovereign crisis, detracting (on average) around 0.5 pp from annual euro-area growth in the period between 2008Q3 and 2011Q3. As the shock unwound, GDP was boosted during the subsequent recovery. This analysis suggests that any further increase in uncertainty could have a materially negative impact on euro-area activity. Therefore, it needs to be carefully monitored by policy makers, particularly in the context of the upcoming political elections in a number of countries.
A railway boom in America’s Midwest goes spectacularly bust. Sixty-two of New York’s commercial banks close – out of sixty-three. Meanwhile in Britain, a decade gilt-edged by gold discoveries in Australia and fuelled by the Crimean War was beginning to lose its lustre. Thus the scene was set for the first global financial crisis shaking markets in New York, London, Paris and across the world. A crisis so severe it forced the Bank of England to “break the law” to survive.
Francesc R. Tous, Puriya Abbassi, Rajkamal Iyer, José-Luis Peydró.
What are the consequences of proprietary trading? Banks typically hold and trade a significant amount of securities, and during the financial crisis, many of these securities suffered strong price declines. How did banks react? This is precisely what we investigate for the case of Germany in a recently published paper. We find that some banks increased their investments in securities, especially for those securities that suffered price drops. This strategy delivered high returns; but at the same time, these banks pulled back on lending to the real economy, since during the financial crisis they could not easily raise new (long-term) funding. Our findings suggest that proprietary trading during a crisis can lead to less lending to the real sector.
Nicholas Fawcett, Riccardo Masolo, Lena Koerber, Matt Waldron.
Introduction: forecasting and policy-making
Forecasting is difficult, especially when it concerns the future. If we needed a reminder, the 2008-09 financial crisis demonstrated that macroeconomic forecasts can be highly inaccurate when the economy is buffeted by large shocks (see, for example, Figure 1). But that is not a good reason to avoid forecasting: monetary policy takes time to work, so forecasts are indispensable in monetary policymaking. Instead, we need to understand how different models behave in the eye of the storm: do some cope better during breaks and crises than others? And can we make better forecasts by using information that is not normally included in economic models?