Macroprudential Policy Analysis via an Agent Based Model of the Real Estate Sector

Gennaro Catapano (), Francesco Franceschi (), Valentina Michelangeli and Michele Loberto
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Gennaro Catapano: Bank of Italy
Francesco Franceschi: Bank of Italy

No 1338, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: In this paper, we extend and calibrate with Italian data the Agent-based model of the real estate sector described in Baptista et al., 2016. We design a novel calibration methodology that is built on a multivariate moment-based measure and a set of three search algorithms: a low discrepancy series, a machine learning surrogate and a genetic algorithm. The calibrated and validated model is then used to evaluate the effects of three hypothetical borrower-based macroprudential policies: an 80 per cent loan-to-value cap, a 30 per cent cap on the loan-service-to-income ratio and a combination of both policies. We find that, within our framework, these policy interventions tend to slow down the credit cycle and reduce the probability of defaults on mortgages. However, with respect to the Italian housing market, we only find very small effects over a five-year horizon on both property prices and mortgage defaults. This latter result is consistent with the view that the Italian household sector is financially sound. Finally, we find that restrictive policies lead to a shift in demand toward lower quality dwellings.

Keywords: agent based model; housing market; macroprudential policy (search for similar items in EconPapers)
JEL-codes: D1 D31 E58 R2 R21 R31 (search for similar items in EconPapers)
Date: 2021-06
New Economics Papers: this item is included in nep-cba, nep-cmp, nep-eec, nep-hme, nep-mac and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:bdi:wptemi:td_1338_21

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