A new framework for monitoring risks in the UK housing market

Tihana Škrinjarić

In my recent paper, I present a new model that helps assess risks in the UK housing market. Unlike traditional approaches that focus on average house price growth, the model estimates a full range of possible outcomes, allowing policymakers to identify potential risk of big house price drops. The analysis also highlights important regional differences: areas with more constrained housing supply tend to be more sensitive to changes in interest rates. Expanding supply can help ease price pressures. These insights can help improve the monitoring of housing market vulnerabilities and support financial stability policy.

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Distributional consequences of borrower-based macroprudential tools

Jagdish Tripathy, Arzu Uluc, José-Luis Peydró and Francesc Rodriguez-Tous

Borrower-based macroprudential measures – such as limits on loan to income (LTI) and loan to value (LTV) ratios – have become a standard feature of the post-crisis regulatory landscape. A growing body of country-specific evidence suggests these measures are effective in moderating the self-reinforcing loop between mortgage credit and house prices, and in reducing default rates and limiting house price volatility during periods of economic stress. Yet their distributional consequences are less well understood. In a new paper, we survey the existing evidence and find that these tools deliver clear financial stability benefits, while also generating distributional effects across borrower groups. Further, we identify areas where future research is needed to provide a comprehensive welfare assessment of these measures.

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Does higher productivity create inflationary or disinflationary pressure?

Ludovica Ambrosino, Jenny Chan and Silvana Tenreyro

Recent technological advances raise an important question for policymakers: will higher productivity lead to disinflationary or inflationary pressure? A coming wave of AI-driven productivity growth is often described as a disinflationary tailwind that would allow central banks to hold interest rates lower without reigniting inflationary pressures. Yet faster productivity growth can just as plausibly call for higher, not lower, interest rates. By raising expected future income and the returns to investment, it stimulates consumption and investment today, pushing up the natural rate of interest. Neither view is entirely wrong and our model reconciles the two by showing that the answer depends on the timing, permanence, and sectoral origin of the productivity shock.

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If AI disappoints? The transmission of US big-tech earnings news

Daniel Ostry, Roger Vicquéry and Emilio Zaratiegui

There is growing concern among policymakers, international organisations, and even big-tech Chief Executive Officers (exhibits I, II and III) that the current artificial intelligence (AI) boom features valuations increasingly detached from fundamentals. The Bank’s February 2026 Monetary Policy Report noted that an asset price correction is a key risk to the global economy, while the Bank’s July 2026 Financial Stability Report presented a scenario for how an AI correction could unfold. In this post, we study how negative big-tech earnings news transmits to global markets, which informed discussions around this scenario. We find that the effects ripple far beyond tech: equity indices decline, credit spreads widen and the US dollar depreciates. This last result, together with the limited response of Treasury yields, suggests muted flight-to-safety dynamics, unlike other financial stress episodes.

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Demographics, deposits and data: using machine learning to segment UK mortgages

Joe Grimshaw

Who are the UK’s mortgage borrowers, and how do their characteristics differ? Despite extensive literature on mortgage profiles, loan-level segmentation remains limited, existing work relies on aggregates or predefined categories. I address this gap by applying unsupervised machine learning to 20 years of data, allowing the model determine segments without prior assumptions. Three clusters emerge: one with low leverage, and two with high leverage but notably different income profiles. Lending composition has shifted gradually. High leverage, high-income borrowers now account for a larger market share, and first-time buyers increasingly fall into more leveraged segments. Machine learning is crucial for financial stability, revealing concentrations of characteristics, and trends, that aggregates and simple splits cannot, offering richer and earlier indications of potential vulnerabilities.

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Retail investors’ participation in the gilt market

Sarah Munson and Callum Ashworth

In recent years, retail investors’ demand for UK government bonds (gilts) has increased, marking a change in the composition of market participants. The growth of retail investors, comprised of individuals managing their own portfolios, has been a global phenomenon (Foxall et al (2025)). But what’s driving this change, and what does it mean for the gilt market’s role in monetary policy and financial stability? In this post we explore how UK-based retail participants’ presence in the gilt market is changing and what that might signal for the future. We find that retail holdings of gilts remain modest, with positions concentrated in a handful of bonds. This has limited impact on aggregate liquidity indicators but can impact liquidity in these specific bonds.

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Who owns the buildings where Britain shops, works – and stores its data?

Katherine Blood

We have developed a new measure tracking UK commercial real estate (CRE) ownership at property level, mapping the latest investor landscape at end-2025 Q3 and its shift since the pandemic. Our estimates show a diversified, international base: overseas investors hold around one third of UK CRE, while private equity funds own 8% after post-pandemic growth. Investor-owned CRE has tilted towards warehouses, logistics, rental housing and properties serving innovation-led sectors – like data centres and life-sciences. Why does this matter? CRE ownership shapes how shocks play out – affecting refinancing waves, upgrade costs and valuation swings. History shows the sector has seen boom-bust cycles before and contributed to financial stability challenges in the UK and abroad.

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Regulatory independence and financial stability

Rhiannon Sowerbutts

The Bank of England Agenda for Research (BEAR) sets the key areas for new research at the Bank over the coming years. This post is an example of issues considered under the Financial System Theme which focuses on the shifting landscape and new risks confronting financial policymakers.

Institutions matter. And in the world of economics, few institutions are as prized as independent central banks. Monetary policy independence, many argue, allows central banks to look through electoral cycles to prioritise long-run price stability. But what about price stability’s younger, less glamorous cousin – financial stability? In a recent paper, we develop a measure of regulatory and supervisory independence (or the lack of it) and examine what are the implications for financial stability. Our findings underline the critical importance of robust, independent regulatory frameworks to safeguard financial systems and show that just as with monetary policy – independence matters for regulation and supervision too.

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Once upon a time in the future: strategic foresight in central banks

Julia Giese and Jacqueline Koay

We live in an era of rapid change, complexity and uncertainty. Over recent years, severe global shocks have been frequent, with profound implications for our economy and financial system. Yet such shocks are impossible to forecast with any precision as they are not extrapolations of past relationships. Our economy and financial system are subject to longer-running trends such as technological advances, demographics, geopolitical shifts and climate change which can be blown off course or altered in unexpected ways. Where forecasts are bound to fail, strategic foresight tools can help as they are a means for practitioners to understand the dynamics of change (and how this could impact the economy and financial stability) by imagining different futures and telling stories around how trends might interact to give rise to unforeseen shocks.

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GIV us some credit: estimating the macroeconomic effects of credit supply shocks

Sam Christie and Aniruddha Rajan

Sudden contractions in credit supply can trigger and amplify recessions – a reality made painfully clear by the 2008 global financial crisis (GFC). However, quantifying these real economic effects is challenging. In this post, we demonstrate a novel way to do so using Granular Instrumental Variables (GIV), focusing on the UK mortgage market. The core idea is that we can exploit the market’s concentration to build up exogenous fluctuations in aggregate credit supply from idiosyncratic lender-specific shocks. Using our GIV, we find evidence that contractionary mortgage supply shocks can have quantitatively significant effects on the macroeconomy, causing persistent decreases in output, consumption, and investment, alongside increases in unemployment.

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