Macroprudential policy in an agent-based model of the UK housing market

Rafa Baptista (), J. Farmer, Marc Hinterschweiger, Katie Low (), Daniel Tang () and Arzu Uluc
Additional contact information
Rafa Baptista: Oxford Martin School, University of Oxford
Katie Low: Bank of England, Postal: Bank of England, Threadneedle Street, London, EC2R 8AH
Daniel Tang: Oxford Martin School, University of Oxford

No 619, Bank of England working papers from Bank of England

Abstract: This paper develops an agent-based model of the UK housing market to study the impact of macroprudential policies on key housing market indicators. This approach enables us to tackle the heterogeneity in this market by modelling the individual behaviour and interactions of first-time buyers, home owners, buy-to-let investors, and renters from the bottom up, and observe the resulting aggregate dynamics in the property and credit markets. The model is calibrated using a large selection of micro-data, mostly from household surveys and housing market data sources. We perform a series of comparative statics exercises to investigate the impact of the size of the rental/buy-to-let sector and different types of buy-to-let investors on housing booms and busts. The results suggest that an increase in the size of the buy-to-let sector may amplify house price cycles and increase house price volatility. Furthermore, in order to illustrate the effects of macroprudential policies on several housing market indicators, we implement a loan-to-income portfolio limit. We find that this policy attenuates the house price cycle.

Keywords: Agent-based mode; housing market; macroprudential policy; buy-to-let sector (search for similar items in EconPapers)
JEL-codes: D31 E58 R21 R31 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2016-10-07
New Economics Papers: this item is included in nep-cba, nep-cmp, nep-eur, nep-mac and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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