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.
Real interest rates have fallen by around 5 percentage points since the 1980s. Many economists attribute this to “secular” trends such as a structural slowdown in global growth, changing demographics and a fall in the relative price of capital goods which will hold equilibrium rates low for a decade or more (Eggertsson et al., Summers, Rachel and Smith, and IMF). In this blog post, I argue this explanation is wrong because it’s at odds with pre-1980s experience. The 1980s were the anomaly (chart A). The decline in real rates over the 1990s and early 2000s simply reflected a return to historical norms from an unusually high starting point. Further falls since 2008 are far more plausibly related to the financial crisis than secular trends.
Philip Bunn, Jeanne Le Roux, Kate Reinold and Paolo Surico.
If you unexpectedly received £1000 of extra income this year, how much of it would you spend? All? Half? None? Now, by how much would you cut your spending if it had been an unexpected fall in income? Standard economic theory (for example the ‘permanent income hypothesis’) suggests that your answers should be symmetric. But there are good reasons to think that they might not be, for example in the face of limits on borrowing or uncertainty about future income. That is backed up by new survey evidence, which finds that an unanticipated fall in income leads to consumption changes which are significantly larger than the consumption changes associated with an income rise of the same size.
Empirical identification of the effects of monetary policy requires isolating exogenous shifts in the policy instrument that are distinct from the systematic response of the central bank to actual or foreseen changes in the economic outlook. Because the same tools are used to both induce changes in the economy, and to react to them, distinguishing between cause and effect is a far from trivial matter. One popular way is to use surprises in financial markets to proxy for the shock. In a recent paper, we argue that markets are not able to distinguish the shocks from the systematic component of policy if their forecasts do not align with those of the central bank. We thus develop a new measure of monetary shocks, based on market surprises but free of anticipatory effects and unpredictable by past information.
Philippe Bracke and Silvana Tenreyro.
When someone bought a house turns out to be an important factor in predicting whether the house will be sold again soon, and at what price. People who bought during a boom aim at achieving higher prices when they sell and, as a consequence, move less often. We explore whether this pattern is due to psychological anchoring (whereby the previous purchase price becomes an important reference point) or to the way the mortgage market works (for example, with homebuyers often using proceeds from house sales for down-payments on new properties).
Ian Billett and Patrick Schneider.
As time goes to infinity, the probability that a productivity analyst will wonder ‘which sectors are driving these trends?’ goes to one. We present an interactive sectoral productivity tool to help you explore this question without any fuss.
Paul Schmelzing, Harvard University.
Paul Schmelzing is a visiting scholar at the Bank from Harvard University, where he concentrates on 20th century financial history. In this guest post, he looks at the current bond market through the lens of nearly 800 years of economic history.
The economist Eugen von Böhm-Bawerk once opined that “the cultural level of a nation is mirrored by its interest rate: the higher a people’s intelligence and moral strength, the lower the rate of interest”. But as rates reached their lowest level ever in 2016, investors rather worried about the “biggest bond market bubble in history” coming to a violent end. The sharp sell-off in global bonds following the US election seems to confirm their fears. Looking back over eight centuries of data, I find that the 2016 bull market was indeed one of the largest ever recorded. History suggests this reversal will be driven by inflation fundamentals, and leave investors worse off than the 1994 “bond massacre”.
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.
Gene Kindberg-Hanlon and David Young.
The volume of world trade is now 17% below where it would be had it grown at pre-crisis trend after 2011. This post argues that most of this gap can be explained by weakness in world GDP, but stalling expansion in global value chains (GVCs) is playing an increasingly important role. We also argue that this shortfall can’t be explained by shifts in the geographical or the expenditure split of global GDP growth. While world trade grew twice as quickly as world GDP pre-crisis, it is likely to grow at about the same rate as world GDP in the future. This matters: weak trade could explain half of the 1pp fall in annual global productivity growth since the crisis.
Colm Aodh Manning.
For the past three years, the Bank of England (the Bank) has carried out an annual ‘stress test’ of the UK’s largest banks. To do this, it designed a narrative-based stress scenario in 2014 and 2015. The goal was to determine the banking sector’s resilience to pertinent threats, like recessions or a sharp fall in house prices. However, changing scenarios each year makes it difficult to judge how banks’ overall vulnerability to risks changes over time. Since the crisis we learned that risks build in the good times and capital in the banking system should rise to reflect this. This is why – beginning this year – the Bank has also run an Annual Cyclical Scenario (ACS).