Bank Underground is about to take a break for the festive season. In keeping with tradition, we are pleased to present the annual Bank Underground Christmas Quiz! This year, it’s been prepared with the kind assistance of the Bank of England’s Archive team. We hope you enjoy testing your knowledge of the Bank’s history, especially how it has marked Christmas in years past. We wish our readers a very happy festive season!
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.
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 Macroeconomic Environment Theme which focuses on the changing infaton dynamics and unfolding structural change faced by monetary policy makers
The recent inflation surge has sparked concerns about how uncertainty over price dynamics shapes households’ financial behaviour. Often, lower uncertainty about inflation coincides with lower expected inflation – when inflation is low and stable, households feel more confident about future trends. In a new paper, Johannes J. Fischer, Christoph Herler and Philip Schnattinger employ a randomised controlled trial (RCT) to disentangle the effects of households’ uncertainty about inflation from the expected level. This disentangling is important: lower expected inflation can discourage immediate spending, while lower inflation uncertainty may push them towards spending more. We show that reduced inflation uncertainty leads to higher planned spending, lower saving rates, and a shift towards liquid assets with fixed returns.
Ludovica Ambrosino, Jenny Chan and Silvana Tenreyro
Macroeconomic Environment Theme
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 Macroeconomic Environment Theme which focuses on the changing inflation dynamics and unfolding structural change faced by monetary policy makers.
Global economic trends have changed markedly over the past two decades. The global financial crisis represented a turning point, with trade openness plateauing and fragmentation steadily increasing before rising sharply during the pandemic and Russia’s invasion of Ukraine. Trade fragmentation is increasingly driven by national security concerns, the rise of ‘friendshoring‘, and the emergence of competing trade blocs. For policymakers, this raises a central question: how will trade fragmentation shape inflation dynamics, and what are the implications for monetary policy? A recent paper addresses this question by analysing trade fragmentation in a model where the inflationary effects depend on the adjustment of demand alongside supply.
High levels of household indebtedness can amplify negative economic shocks, if highly indebted mortgagors make larger cuts to spending in response to them or are more vulnerable to defaulting on mortgage payments adding to bank losses. These are tail risks which can pose significant financial instability. In this post, we present quantitative evidence on these risks using a local projection model. We find that when the share of highly indebted households increases, aggregate consumption drops more sharply and mortgage arrears increase more in response to interest rate shocks. Our work highlights the importance of managing risky lending through macro and microprudential policy. And it highlights how debt burdens can interact with the monetary transmission mechanism.
Houses account for the largest share of total assets held by the UK household sector. Households’ spending and saving decisions depend in part on the price of these assets. What causes house prices to move can therefore have important consequences for macroeconomic policy and financial stability. Our house price model decomposes movements in house prices into contributions from key economic drivers. Among these, measures of real household income explain much of their variation over time. The rise in mortgage rates during the recent tightening cycle is estimated to have kept house prices nearly 10% lower than had interest rates not moved, with some of this effect offset by real income growth.
Modern language models – think OpenAI’s GPTs, Google’s Gemini or DeepSeek – are powerful tools: but how can we use them in economic policymaking? Economic analysis often relies on decompositions to understand macroeconomic data and inform counterfactuals. But these decompositions are typically obtained from numerical data or macroeconomic models and so may overlook nuanced insights embedded in unstructured text. We propose decomposing the metrics which Large Language Models (LLMs) can derive from text data to offer insights from large collections of documents in a highly interpretable format. This approach aims to bridge the gap between natural language processing (NLP) techniques and economic decision-making, offering a richer, more context-aware understanding of complex economic phenomena.
Digital currencies and stablecoins have increased interest in how new forms of money are adopted. Looking to three episodes from the 1690s to the First World War, this post considers how paper currency replaced coin in Britain, an historical example of adoption of new money. The underlying drivers were not technological changes but wars, leading to actual or feared shortages of coin, and a need to take specie out of internal circulation in order to meet overseas outflows. The public authorities took the initiative and created trust successfully in the new money. This is the first of a series of planned posts by Bank staff on past payment innovations.
AI systems are becoming increasingly capable of pursuing sophisticated goals without human intervention. As these systems begin to be used to make economic transactions, they raise important questions for central banks, given their role overseeing money, payments, and financial stability. Leading AI researchers have highlighted the importance of retaining governance control over such systems. In response, AI safety researchers have proposed developing infrastructure to govern AI agents. This blog explores how financial infrastructure may emerge as a particularly viable governance tool, offering pragmatic, scalable, and reversible chokepoints for monitoring and controlling increasingly autonomous AI systems.
Utkarsh Somaiya, Caspar Siegert and Benjamin Kingsmore
Climate change creates material economic and financial risks which central banks need to understand to ensure monetary and financial stability. Their interest in climate change has therefore skyrocketed, with almost one third of central bank speeches in 2023 referencing climate change. Central banks are typically responsible for ensuring monetary and financial stability; these macroeconomic conditions are essential to support an orderly transition to net zero. But central banks are often urged to play a more active role and provide targeted support for the transition. Rather than discussing whether this is consistent with their legal mandates, we ask a more pragmatic question: do central banks have the right tools for this job? We argue that some commonly discussed tools may not be very effective.