We develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental, and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let (BTL) investors, and renters. This approach can, therefore, offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real-estate online search engine as well as loan-level regulatory data. With a series of comparative static exercises, we investigate the impact of (i) a hard loan-to-value limit and (ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to BTL investors affects both the supply of and the demand for rental properties.
Adrian Carro, Marc Hinterschweiger, Arzu Uluc, J Doyne Farmer, Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market, Industrial and Corporate Change, 2022, dtac030, https://doi.org/10.1093/icc/dtac030