Taming Macroeconomic Instability: Monetary and Macro Prudential Policy Interactions in an Agent-Based Model

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe develop an agent-based model to study the macroeconomic impact of alternative macro prudential regulations and their possible interactions with different monetary policy rules. The aim is to shed light on the most appropriate policy mix to achieve the resilience of the banking sector and foster macroeconomic stability. Simulation results show that a triplemandate Taylor rule, focused on output gap, inflation and credit growth, and a Basel III prudential regulation is the best policy mix to improve the stability of the banking sector and smooth output fluctuations. Moreover, we consider the different levers of Basel III and their combinations. We find that minimum capital requirements and counter-cyclical capital buffers allow to achieve results close to the Basel III first-best with a much more simplified regulatory framework. Finally, the components of Basel III are non-additive: the inclusion of an additional lever does not always improve the performance of the macro prudential regulation.

Agent-based model calibration using machine learning surrogates

“…Such developments are especially important for complex macroeconomic agent-based models (see e.g. Dosi et al, 2010Dosi et al, , 2013Dosi et al, , 2015Dosi et al, , 2017aPopoyan et al, 2017) as they could allow the development of a standardized and robust procedure for model calibration and validation, thus closing the existing gap with Dynamics Stochastic General Equilibrium models (see Fagiolo and Roventini, 2017, for a critical comparison of ABM and DSGE models). Accordingly, a user-friendly Python surrogate modelling library will also be released for general use.…”

The interaction between monetary and macroprudential policy: should central banks ‘lean against the wind’ to foster macro-financial stability?

“…We contribute to the literature on regulatory impact assessment and the interaction between monetary policy and financial stability in the following way: First, by providing an agent-based macro-model 6 with endogenous money, we contribute to model pluralism in this area. Currently, we are not aware of any comparable studies using an ACE model in this field, except for Popoyan et al (2017); Alexandre and 3 See also Disyatat (2010). 4 Recent examples would be Levine and Lima (2015); Gambacorta and Signoretti (2014) ;Badarau and Popescu (2015); Rubio and Carrasco-Gallego (2014).…”

Agent-Based Macroeconomics

“…6 In the following we will refer mainly to Ashraf et al (2016) and Ashraf et al (2017). For an extension and application to monetary and macro-prudential policy, see Popoyan et al (2017) 7 Delli Gatti et al (2005) is the most significant early example of a CATS model, populated by myopic optimizing firms, which use only capital to produce goods. Russo et al (2007) develop an early model along similar lines, with an application to fiscal policy.…”

“…An extensive agent-based analysis of the effect of different types of regulatory schemes for banks is also carried out in Popoyan et al (2017). They build their analysis on an extension of the AGH model, in which the banks' rule for granting loans to shops is based on a frequently used approach for determining creditworthiness, the '6C' approach.…”