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Pandemic shocks and macroprudential policy

Authors: Bratsiotis, George John; id_orcid 0000-0001-8740-6254; Gloria, Manuel;

Pandemic shocks and macroprudential policy

Abstract

Abstract We introduce an extended borrower–saver DSGE (Dynamic Stochastic General Equilibrium) model, where classifications of occupations are split further into two subcategories, according to whether their occupation is directly “affected” by a pandemic shock. We find that, contrary to the standard literature, during a pandemic shock an increase in the Loan-to-Value (LTV) ratio can increase social welfare and make all four agent types (borrowers affected, borrowers non-affected, savers affected, and savers non-affected) better off. Countercyclical optimal LTV rules are shown to increase social welfare, with savers gaining at the expense of borrowers, including those mostly affected by the pandemic. An interest rate mortgage subsidy to those worst affected (“affected” mortgage borrowers), in coordination with stricter monetary and LTV policy, are shown to increase both social welfare and the welfare of borrowers and savers affected by the pandemic.

Country
United Kingdom
Related Organizations
Keywords

welfare, monetary policy, pandemic shock, Covid-19, macroprudential policy, loan-to-value, financial stability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
hybrid