There’s more to house prices than interest rates

Lisa Panigrahi and Danny Walker

The average house in the UK is worth ten times what it was in 1980. Consumer prices are only three times higher. So house prices have more than trebled in real terms in just over a generation. In the 100 years leading up to 1980 they only doubled. Recent commentary on this blog and elsewhere argues that this unprecedented rise in house prices can be explained by one factor: lower interest rates. But this simple explanation might be too simple. In this blog post – which analyses the data available before Covid-19 hit the UK – we show that the interest rates story doesn’t seem to fit all of the facts. Other factors such as credit conditions or supply constraints could be important too.

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How important are large firms for aggregate productivity growth in the UK?

Marko Melolinna

Aggregate labour productivity growth has been low in the UK following the global financial crisis in 2008 (Chart 1). The average annual growth rate has been only 0.7% over the period 2008 to 2019, which is around a third of the growth rate seen during the decade preceding the crisis. There are many ways of analysing the reasons for this weakness, but in this blog post, I concentrate on examining the role that the largest firms in the UK have played in the story. Our analysis covering the past three decades from 1990 to 2017 suggests that firm-specific, or idiosyncratic, shocks to the 100 largest firms had a significant effect on aggregate productivity dynamics in the UK.

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Monetary Policy Transmission: Borrowing Constraints Matter!

Fergus Cumming and Paul Hubert

How does the transmission of monetary policy depend on the distribution of debt in the economy? In this blog post we argue that interest rate changes are most powerful when a large share of households are financially constrained. That is, when a higher proportion of all borrowers are close to their borrowing limits. Our findings also suggest that the overall impact of monetary policy partly depends on the behaviour of house prices, and might not be symmetric for interest rate rises and falls.

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Housing consumption and investment: evidence from the Help to Buy scheme

Matteo Benetton, Philippe Bracke, João F Cocco and Nicola Garbarino

Academics have made the case for mortgage products with equity features, so that gains and losses due to fluctuations in house values are shared between the household and an outside investor. In theory, the equity component expands the set of affordable properties, without increasing household debt, and default risk. These products have not become mainstream, but in a recent paper, we study a large UK experiment with equity-based housing finance — the Help To Buy Equity Loan scheme. We find that equity loans are mainly used to overcome credit constraints, rather than to reduce investment risk. Unconstrained household prefer mortgage debt over equity loans, suggesting optimism about house price risk. Equity loans could still contribute to house price inflation: we don’t find evidence that houses purchased with equity loans are overpriced, but an assessment of the aggregate effects is beyond the scope of the paper.

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Thrive or dive: can our economy weather the climate crisis?

Marco Minasi-Smith, Fortismere School, London

Marco Minasi-Smith, from Fortismere School, London, is the runner-up of the third Bank of England/Financial Times schools blog competition. The competition invited students across the UK to write a post on the theme: the economy and climate change.

While Australia mourns the human and ecological cost of its ‘black summer’ of fires, the tragedy poses a question for economic policy-makers everywhere: how do we prevent climate crises becoming economic ones?

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Loss aversion: the concept every supplier should be utilising to tackle climate change

India Loader, South Wilts Grammar School

India Loader, from South Wilts Grammar School, is the winner of the third Bank of England/Financial Times schools blog competition. The competition invited students across the UK to write a post on the theme: the economy and climate change.

To help save the planet and gain a competitive edge, cafes should obey a basic rule of behavioural economics by switching from offering discounts for customers who bring their own cups in favour of charging more for disposable ones.

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Temporary pause to Bank Underground

Given our need to reprioritise staff resources towards responding to the Covid-19 pandemic, we’ll be temporarily pausing publishing posts on Bank Underground. We will review this periodically and hope to resume soon.

Belinda Tracey, Managing Editor

If you want to get in touch, please email us at bankunderground@bankofengland.co.uk or leave a comment below.

Comments will only appear once approved by a moderator, and are only published where a full name is supplied. Bank Underground is a blog for Bank of England staff to share views that challenge – or support – prevailing policy orthodoxies. The views expressed here are those of the authors, and are not necessarily those of the Bank of England, or its policy committees.

How does monetary policy affect firms?

Saleem Bahaj, Angus Foulis, Gabor Pinter and Paolo Surico

Changes in interest rates affect different parts of the economy differently. In this post, building on a recent working paper, we consider how different types of firms respond to interest rate changes. We focus on firm level employment and ask which firms do the most hiring and firing when monetary policy adjusts. For instance, how important is the age of the firm, its balance sheet position or its size in determining the firm level response to interest rates? Furthermore, do these patterns of responses tell us something about how monetary policy affects the economy?

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How to see it coming: predicting bank distress with machine learning

Joel Suss and Henry Treitel

The need to see it coming

The great American baseball sage, Yogi Berra, is thought to have once remarked: ‘It’s tough to make predictions, especially about the future’. That is certainly true, but thankfully the accelerating development and deployment of machine learning methodologies in recent years is making prediction easier and easier. That is good news for many sectors and activities, including microprudential regulation. In this post, we show how machine learning can be applied to help regulators. In particular, we outline our recent research that develops an early warning system of bank distress, demonstrating the improved performance of machine learning techniques relative to traditional approaches.

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