Optimal Time-Consistent Macroprudential Policy
Javier Bianchi and
Enrique Mendoza
PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania
Abstract:
Collateral constraints widely used in models of financial crises feature a pecuniary externality: Agents do not internalize how borrowing decisions taken in “good times" affect collateral prices during a crisis. We show that agents in a competitive equilibrium borrow more than a financial regulator who internalizes this externality. We also find, however, that under commitment the regulator's plans are time-inconsistent, and hence focus on studying optimal, time-consistent policy without commitment. This policy features a state-contingent macroprudential debt tax that is strictly positive at date t if a crisis has positive probability at t + 1. Quantitatively, this policy reduces sharply the frequency and magnitude of crises, removes fat tails from the distribution of returns, and increases social welfare. In contrast, constant debt taxes are ineffective and can be welfare-reducing, while an optimized macroprudential Taylor rule" is effective but less so than the optimal policy.
Keywords: Financial crises; macroprudential policy; systemic risk; collateral constraints (search for similar items in EconPapers)
JEL-codes: D62 E32 E44 F32 F41 (search for similar items in EconPapers)
Pages: 78 pages
Date: 2015-08-01, Revised 2015-08-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)
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https://economics.sas.upenn.edu/sites/default/files/filevault/15-032.pdf (application/pdf)
Related works:
Journal Article: Optimal Time-Consistent Macroprudential Policy (2018) 
Working Paper: Optimal time-consistent macroprudential policy (2015) 
Working Paper: Optimal Time-Consistent Macroprudential Policy (2015) 
Working Paper: Optimal Time-Consistent Macroprudential Policy (2013) 
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Persistent link: https://EconPapers.repec.org/RePEc:pen:papers:15-032
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