INET Oxford and the Bank of England develop an agent-based model of the UK housing market
13 Oct 2016
INET Oxford Complexity Economics Director, Prof. J. D. Farmer, Doctoral Student Rafa Baptista, and INET Oxford Alumnus Daniel Tang, have co-authored a Bank of England Staff Working Paper alongside Bank of England researchers Marc Hinterschweiger, Katie Low and Arzu Uluc. The paper, titled "Macroprudential policy in an agent-based model of the UK housing market", describes an agent-based model that the joint INET Oxford/Bank of England team built and used to explore the dynamics of the UK housing market and scenarios for macroprudential policies to mitigate housing bubbles. The project is one of the first examples of the use of an agent-based model for the purpose of supporting central bank policymaking.
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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.