Bank of England: A framework for monitoring UK housing market risks

Bank of England: A framework for monitoring UK housing market risks

Bank Underground published Tihana Škrinjarić’s account on 24 September 2026. She describes a model that estimates a range of possible UK house price growth outcomes, rather than focusing only on average growth, to help monitor the risk of sharp declines. The model uses quantile regression to estimate house-price-at-risk (HPaR), a measure of possible declines under adverse conditions, at national and regional levels. Škrinjarić says regional results differ: supply-constrained areas show a stronger association between mortgage rate changes and downside risk. Greater housing supply is generally associated with lower future price pressures in most regions, with London, the South East and Scotland exceptions. She reports that the model’s estimated probability of negative growth rose ahead of periods when house prices fell. This is a predictive relationship, not evidence that the model establishes causes or will reliably forecast future declines. The author says regional data are limited, and that the model is designed to identify predictive relationships rather than causal effects. How would richer regional data change the model’s assessment of where housing market risks are building?

Publication: d27cf80b-9a28-6789-df8b-99589009d434

attribution — pass: The reading attributes the model and findings to Tihana Škrinjarić, writing on Bank Underground, a Bank of England staff blog. The title's 'Bank of England:' prefix reflects the publisher. The body attributes the views to the author, consistent with the blog's disclaimer that the views are not necessarily the Bank's.

Tihana Škrinjarić works in the Bank’s Stress Testing and Resilience Division.

summary — pass: The reading leads with the actor and the development: a model estimating a range of house price outcomes rather than the average. It explains HPaR in plain terms, accurately reports the regional differences and the supply exceptions, and keeps the author's stated limitations. The question follows from the source's own suggestion of richer regional data. Quantile regression is named but explained in context as estimating a range of outcomes, so a non-specialist can follow.

Unlike traditional approaches that focus on average house price growth, the model estimates a full range of possible outcomes

date — pass: originalPublished is 2026-09-24T08:00Z, and the reading states 24 September 2026, matching the UTC day. The page dateline also shows 23/09/2026 alongside 24/09/2026; this is the source's own inconsistency, and the reading does not repeat it. Nothing in the reading is presented as occurring after publication. The kind is publisher-page, so no archive disclosure is needed. The page was edited after publication, and the limitations note this; the passages the reading relies on are core article text.

24/09/202623/09/2026

support — pass: Each claim matches the source text: HPaR at the 5th percentile, national and regional estimates, the stronger mortgage rate effect in supply-constrained regions, and the supply exceptions (London, South East, Scotland). It also matches on probability spikes preceding price drops and on the predictive-not-causal limitation. The reading explicitly declines to turn past predictive performance into future reliability. The edit after publication is disclosed, and the cited passages are plainly part of the article body.

However, London, the South East and Scotland are exceptions.

media — pass: No media was selected, and no verified media candidates were supplied, so leaving media empty is appropriate.