Global Investment – The Role of Emerging Markets

Alexander Naumov.

Capital investment is one of the fundamental building blocks of future productivity growth and anticipating future developments in global investment is a major concern for policymakers. This note makes two observations: 1) Despite weak investment in advanced economies, investment is not weak globally – as a share of world GDP, capital investment is currently at the highest level since 1990; 2) Emerging market economies, particularly China and commodity exporters, disproportionally contributed to the recent strength in global investment, but that contribution is now at risk.

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Filed under International Economics

Unintended consequences of higher capital requirements

Arzu Uluc and Tomasz Wieladek.

Following the global financial crisis of 2007-08, financial reform introduced time-varying capital requirements to raise the resilience of the financial system. But do we really understand how this policy works and the impact it is likely to have on UK banks’ largest activity, mortgage lending? In a recent paper we investigated the UK experience of time-varying microprudential capital requirements before the financial crisis. We found that an increase in this requirement intended to make a bank more resilient actually induced it to shift into riskier mortgage lending.

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Filed under Banking, Financial Stability, Macroprudential Regulation, Microprudential Regulation

DIY Macroeconomic Modelling on a Raspberry Pi

Andrew Blake.

Enthusiasts use the tiny Raspberry Pi computers for many things.  Fun ones include garage door opening, retro gaming, a voice-activated tea maker, live images from near-space and even a GPS kitten tracker.  These computers are primarily educational but do anything a normal computer does, so users also send email, play Minecraft, program and (it turns out) do macroeconomic modelling.

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Filed under Macroeconomics, New Methodologies

Proprietary trading: evidence from the crisis

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.

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Filed under Banking, Financial Markets, Financial Stability

Collateral and market stress: what are the risks?

Yuliya Baranova, Zijun Liu and Joseph Noss.

Introduction

Collateral – that is, securities pledged to secure loans and other counterparty exposures – plays an important role in supporting the efficient functioning of the financial system. It supports a vast range of collateralised transactions, including repo and derivatives, which are important for both market liquidity and funding liquidity. But can collateral market dynamics play a role in exacerbating financial stability risks?  In this post we explore two risks arising from the behaviour of market participants in stressed conditions:The first risk is that in response to market stress demand for collateral temporarily exceeds supply, until prices adjust. The second is that, during market stress, constraints on dealers’ balance sheets mean they have insufficient capacity to move collateral across the financial system.

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Filed under Financial Markets, Financial Stability

Robot Macroeconomics: What can theory and several centuries of economic history teach us?

John Lewis.

Advances in machine learning and mobile robotics mean that robots could do your job better than you.  That’s led to some radical predictions of mass unemployment, much more leisure or a work free future.   But labour saving innovations and the debates around them aren’t really anything new.  Queen Elizabeth I denied a patent for a knitting machine over fears it would create unemployment, Ricardo thought technology would lower wages and Keynes famously predicted a 15 hour working week by 2030.   Understanding why these beliefs proved to be wrong gives us important insights into why similar claims about robotisation might be incorrect.  But automation could nevertheless have sizeable distributional implications and ramifications well beyond the industries in which it’s deployed.

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Filed under Economic History, Macroeconomics

When asset managers go MAD

Thomas Belsham.

What do the Cold War powers of the United States and the USSR have in common with modern day asset managers?  The capacity for mutually assured destruction.  During the 1950s game theorists described a model of strategic interaction to demonstrate how it might be that two nations would choose to annihilate each other in nuclear conflict.  Simply put, each nation had an incentive to strike first, as there was no incentive to retaliate.  Both would race to push the button.  Asset managers face a similar set of incentives.

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Filed under Financial Markets, Financial Stability, Macroprudential Regulation

How credit risk can incentivise banks to keep making payments at the height of a crisis

Marius Jurgilas, Ben Norman and Tomohiro Ota.

The final, practical determinant of whether a bank is a going concern is: does it have the liquidity to make its payments as they become due?  Thus, the ultimate crucible in which financial crises play out is the payment system.  At the height of recent crises, some banks delayed making payments for fear of paying to a bank that would fail (Norman (2015)).  This post sets out a design feature in a payment system that creates incentives, especially during financial crises, for banks to keep making payments.  This feature could address situations where banks in the system would otherwise be tempted to postpone their payments to a bank that is (rumoured to be) in trouble.

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Filed under Market Infrastructure, New Methodologies

Balancing bias and variance in the design of behavioral studies: The importance of careful measurement in randomized experiments

Andrew Gelman.
bu-guest-post2

The Centre for Central Banking Studies recently hosted their annual Chief Economists Workshop, whose theme was “What can policymakers learn from other disciplines”.  In this guest post, one of the keynote speakers at the event, Andrew Gelman professor of statistics and political science at Columbia University, points out some of the pitfalls of randomly assigned experiments with control groups.

When studying the effects of interventions on individual behavior, the experimental research template is typically:  Gather a bunch of people who are willing to participate in an experiment, randomly divide them into two groups, assign one treatment to group A and the other to group B, then measure the outcomes.  If you want to increase precision, do a pre-test measurement on everyone and use that as a control variable in your regression.  But in this post I argue for an alternative approach- study individual subjects using repeated measures of performance, with each one serving as their own control.

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It’s time to bring more realistic models of human behaviour into economic policy and regulation

David Halpern.

bu-guest-post2The Centre for Central Banking Studies recently hosted their annual Chief Economists Workshop, whose theme was “What can policymakers learn from other disciplines”.  In this guest post, one of the keynote speakers at the event, David Halpern, CEO of the Behavioural Insights Team, argues that insights from behaviour science can improve the design and effectiveness of economic policy interventions.

Behaviour science has had major impacts on policy in recent years. Introducing a more realistic model of human behaviour – to replace the ‘rational’ utility-maximizer – has enabled policymakers to boost savings; increase tax payments; encourage healthier choices; reduce energy consumption; boost educational attendance; reduce crime; and increase charitable giving. But there remain important areas where its potential has yet to be realised, including macroeconomic policy and large areas of regulatory practice. Businesses, consumers, and even regulators are subject to similar systematic biases to other humans. These include overconfidence; being overly influenced by what others are doing; and being influenced by irrelevant information. The good news is that behavioural science offers the prospect of helping regulators address some of their most pressing issues. This includes: anticipating and addressing ‘animal spirits’ that drive bubbles or sentiment-driven slowdowns; reducing corrupt market practices; and encouraging financial products that are comprehensible to humans.

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