The keys to house price growth – Bank Underground

Arno Hantzsche and Harriet Jeanes

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.

The house price model

Understanding developments in house prices is important for assessing how changes in the housing market may influence broader economic activity. For example, movements in interest rates can weigh on house prices, which can dampen economic activity by reducing the collateral households have available against which they borrow. This can then have implications for consumption and investment across the economy. Our aim is to provide an up-to-date tool that can both explain house price dynamics over the medium term and deliver robust forecasting performance over a three-year horizon, using a simple framework that captures the main drivers identified in the literature. We build on a large stock of academic and applied literature that analyses the drivers of house price growth over time and across different countries and regions. Duca et al (2021) provide a comprehensive review of this literature.

In theory, house prices should be determined by rates of return, similar to prices of financial assets: over time, one would expect the return to owning a property to align with the cost of financing the purchase of a house (Auterson (2014)). Unlike the price of other assets, or commercial real estate, the relationship between housing costs and expected returns may be imperfect because of the intrinsic value housing provides in the form of shelter. And unlike in financial markets, transactions in the housing market are less frequent and face more frictions such that adjustments can be slower.

Our empirical representation builds on Auterson (2014) and follows an error correction set-up to capture the dynamic adjustments in the housing market over time. It links short-term house price growth in real terms to changes in average interest rates on new mortgages and growth in measures of real household disposable income. We assume that over time, house prices converge to a long-run equilibrium pinned down by measures of household resources (income, wage share of income), the level of mortgage rates and housing supply (total housing stock divided by population).

To estimate our model, we use an economically relevant sample (1991 to 2023). We thereby avoid the structurally very different housing market prior to the 1990s with lower ownership rates and a different regulatory and tax regime. We do capture the change in monetary policy regime from 1997 and include the Covid period to cover recent developments. The model performs well at forecasting house prices, particularly during the aftermath of the global financial crisis (GFC) and in recent years. The model focuses on statistically and economically relevant determinants of house growth, which allows us to break down changes in house prices into the contributions from different economic drivers.

The drivers of house price growth

Through a decomposition of house price growth, we gain useful insights. We find that real income growth explains much of its variation over time. This is consistent with previous analysis of the UK housing market which also finds that household income is an important driver of house price growth (eg, Meen (2013) and Auterson (2014)). Chart 1 shows a historical decomposition using the model’s estimated parameters and historical realisations of house price determinants. Measures of real income growth (orange bars in Chart 1) explain most of the house price boom pre-GFC as well as some of the weakness in house prices in the years that followed.

Identifying the role of housing supply effect is more difficult in a UK-wide specification, given the role of local constraints, planning frictions, and structural and cyclical differences across regions. Consequently, our indicator of supply, based on housing stock and population dynamics at the aggregate level, adds only very little information to the model (yellow bars).

Higher mortgage rates (purple bars) have a negative impact on house price growth. We can see that within mortgage rates, the increase in spreads over risk-free rates drove some of the decline in house prices during the GFC while the loosening of monetary policy thereafter supported house price growth. While the long-term decline in risk-free rates until the late 2010s on average supported house price growth, as discussed in detail by Miles and Monro (2021), the rise in Bank Rate since 2021 explains most of the weakness in recent years.

The residual (pink bars) captures changes in house prices that cannot be explained by the house price model. It is particularly large during the GFC, suggesting that the impact of falling incomes and widening mortgage spreads may have been amplified by banking sector difficulties. The ‘race for space’ during Covid probably explains some of the positive residuals in 2020–21.

Chart 1: Historical decomposition of real house price growth

Model implications

One feature of the house price model is that we can use it to monitor monetary transmission via the house price channel, which has implications for impacts of monetary policy on the wider economy.

When assessing the direct impact from Bank Rate on house prices through mortgage rates, and holding all else equal, the model indicates that house prices respond to a 100 basis points rise in Bank Rate with a 2.5% fall, which is fully realised after three years. This assumes that changes in Bank Rate are directly mirrored by an equal change in mortgage rates.

A change in Bank Rate can also affect house prices indirectly, through its effect on household income and house building but also other channels including business investment (Bahaj et al (2020)). Some of our models suggest that these indirect effects can be at least as large as direct effects via mortgage rates.

Over the recent tightening cycle, the model indicates that the rise in Bank Rate through its direct impact via mortgage rates may have kept real house prices nearly 10% lower relative to a counterfactual with unchanged interest rates, abstracting from any additional indirect effects. This can be seen by the purple bars in Chart 2. This effect is estimated to have partly been offset by a recovery in real incomes. In addition, model residuals start pulling down on house prices as early as 2022 Q2 before fizzling out for most recent data. It is possible that the direct impact of monetary policy on the housing market may have been transmitted more quickly than typically observed in the model’s estimation sample, although the overall peak impact remains similar.

Falling house prices can dampen household consumption by reducing homeowners’ net wealth. This reduction in wealth also limits the collateral households have available to borrow against, tightening credit conditions. The combined effect of weaker consumption and constrained borrowing can weigh on overall economic activity.

Chart 2: Change in the level of real house prices since 2021 Q3

Conclusion

This house price model provides a useful lens through which to analyse the dynamics in house prices over multiple years and the broader economic conditions that drive them. To inform policy, this model would need to be complemented with other tools that are better suited to monitor housing market developments in the near term.

To ensure the model remains transparent and simple to use, it abstracts from many real-world complexities. This includes other possible drivers of house prices like changes in mortgage characteristics, credit supply conditions, household financial wealth and changes in tax and regulation over time. Structural modelling can in more detail speak to causal linkages between monetary policy, housing markets and economic activity (eg Albuquerque et al (2025)). And regional analysis of house price dynamics may better be able to pick up the impact of housing supply.

Arno Hantzsche works in the Bank’s Structural Economic Division and Harriet Jeanes works in the Bank’s Current Economic Conditions Division.

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