Monetary policy transmission during QE times: role of expectations and premia channels

Iryna Kaminska and Haroon Mumtaz

Since 2009, when policy rates reached their effective lower bound, quantitative easing (QE) has become an important instrument of central bank monetary policy. It is aimed to work via long-term yields. The literature confirms that QE helped lower long-term yields. But the yields have two components – expectations and term premia – and open questions remain: does QE reduce yields via expected rates or term premia? And which channel is more efficient in stimulating the economy? In our research paper, we find evidence that QE often worked through signalling and term-premia effects simultaneously. But the two main QE channels are transmitted to financial markets and the real-economy in different ways, and only signalling is found to have ultimately affected inflation significantly.

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What to expect when they’re expecting

Maren Froemel, Mike Joyce and Iryna Kaminska

Introduction

During 2020 the MPC announced a further £450 billion of QE purchases, slightly more than the total amount of assets purchased over the preceding ten years, taking the target QE stock to £875 billion of gilt holdings and £20 billion of sterling investment-grade corporate bonds. We study the high-frequency reaction of gilt markets to these QE announcements in light of the surprises to market expectations of the future QE path. We find the yield reactions to be broadly consistent with news about the expected medium-term stock of QE. This is in line with recent commentary, which has focused on the ‘pace of purchases’, as a faster/slower pace translated into a larger/lower stock of expected purchases, and could capture the effects of the local supply channel. The reaction to news about purchase pace could also be potentially consistent with an impact on expected liquidity premia or expected policy rates.

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Wir sind die Roboter: can we predict financial crises?

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.

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All bark but no bite? What does the yield curve tell us about growth?

Carlo Favero, Sebastian Vismara and Iryna Kaminska

The slope of the yield curve has decreased in the US and the UK over the last few years (Chart 1). This development is attracting significant attention, because the yield curve slope (i.e. the difference between longer term government bond yields and shorter term government bond yields) is a popular business cycle indicator, and a fall of longer term yields below shorter term yields (i.e. an ‘inversion’ of the yield curve) has historically been considered as a powerful signal of recessions, particularly in the US.

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