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Unconventional monetary policies in an agent-based model with mark-to-market standards

Mattia Guerini, Francesco Lamperti, Mauro Napoletano, Andrea Roventini and Tania Treibich
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Francesco Lamperti: Scuola Superiore Sant’Anna

Review of Evolutionary Political Economy, 2022, vol. 3, issue 1, 73-107

Abstract: Abstract We employ an agent-based model to shed light on the macroeconomic effects of accounting principles, unconventional monetary policies, and of their possible interactions. If mark-to-market accounting standards may entail positive feedbacks which amplify economic or financial shocks, unconventional policies may introduce negative feedbacks that might dampen instabilities in financial and real markets. For these reasons, we jointly study these two sets of policies by employing a modified version of the Schumpeter meeting Keynes (K+S) macroeconomic agent-based model. Our results confirm that, due to its pro-cyclical nature, the mark-to-market accounting standard amplifies credit cycles, generating more instability with respect to a simulated economy wherein the historical accounting principle is employed. In contrast, unconventional monetary policy is counter-cyclical and it improves macroeconomic indicators. Finally, we study a scenario wherein mark-to-market accounting and unconventional monetary policy interact. We find that unconventional monetary policy can counterbalance the negative effects brought about by the application of mark-to-market accounting. Our results suggest that unconventional monetary policy instruments should not be considered as temporary interventions to be employed only during crisis periods. They should be part of the toolbox of central banks also in normal times.

Keywords: Unconventional monetary policy; Accounting principles; Mark-to-market; Agent-based models (search for similar items in EconPapers)
JEL-codes: C63 E58 G01 G18 (search for similar items in EconPapers)
Date: 2022
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Working Paper: Unconventional monetary policies in an agent-based model with mark-to-market standards (2022)
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DOI: 10.1007/s43253-022-00065-8

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