Early warning indicators and macro-prudential policies: a credit network agent based model

Catullo, Ermanno; Palestrini, Antonio; Grilli, Ruggero; Gallegati, Mauro

doi:10.1007/s11403-017-0199-y

Cited by 5 publications

(5 citation statements)

References 39 publications

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“…Furthermore, we include two dummy variables: the first one catches the role of loyalty, is loyal, the second one accounts for economic recessions, crisis. Following Catullo et al (2017), this second dummy identifies periods where the production collapse 21 of more than 5%. In Tab.2 we show Model a) regression results.…”

Section: Robustness Analysismentioning

confidence: 99%

Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks

Grilli

Tedeschi

Gallegati

2020

Journal of Economic Dynamics and Control

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In this paper we characterize the evolution over time of a credit network in the most general terms as a system of interacting banks and firms operating in a threesector economy with goods, credit and interbank market. Credit connections change over time via an evolving fitness measure depending from lenders' supply of liquidity and borrowers' demand of credit. Moreover, an endogenous learning mechanism allows agents to switch between a loyal or a shopping-around strategy according to their degree of satisfaction. The crucial question we investigate is how financial bubbles and credit-crunch phenomena emerge from the implemented mechanism.

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Section: Robustness Analysismentioning

confidence: 99%

Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks

Grilli

Tedeschi

Gallegati

2020

Journal of Economic Dynamics and Control

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“…Credit agreement stands for one period and it is repaid at the end of it. In line with Riccetti et al (2013), Catullo et al (2015), Catullo et al (2018), the dynamics of the credit network emerges from a preferential attachment mechanism that allows banks that offer better credit conditions in terms of interest rate to increase the amount of loans granted to firms.…”

Section: The Modelmentioning

confidence: 97%

Macro- And Microprudential Policies: Sweet and Lowdown in a Credit Network Agent-Based Model

2019

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The paper presents an agent-based model reproducing a stylized credit network that evolves endogenously through the individual choices of firms and banks. We introduce in this framework a financial stability authority in order to test the effects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro- and macroprudential policies reduces systemic risk but at the cost of increasing banks’ capital volatility. Moreover, the agent-based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the diffusion of local shocks. Our results support the idea that the mesoprudential policy is able to reduce systemic risk without affecting the stability of banks’ capital structure.

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“…4 For macroeconomic agent-based models with integration of credit and financial markets see Alexandre and Lima (2017), Assenza et al (2015), Bookstaber et al (2017), Caiani et al (2016), Ashraf et al (2017), Catullo et al (2017), Dosi et al (2010, 2015), Delli Gatti et al (2005, Fagiolo et al (2017a), Gross and Población (2017), Gai et al (2011), Gurgone et al (2018), Klimek et al (2015), Krug et al (2015), Krug (2018), Lengnick et al (2013), Montagna and Kok (2016), Napoletano et al (2015), Poledna et al (2014), Riccetti et al (2018), Russo et al (2016), Raberto et al (2012), Seppecher and Salle (2015), Sakiyama et al (2016), Teglio et al (2012), van der Hoog (2018).…”

Section: Introductionmentioning

confidence: 99%

Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market

Popoyan

Napoletano

Roventini

2020

Journal of Economic Dynamics and Control

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We develop a macroeconomic agent-based model to study how financial instability can emerge from the co-evolution of interbank and credit markets and the policy responses to mitigate its impact on the real economy. The model is populated by heterogenous firms, consumers, and banks that locally interact in dfferent markets. In particular, banks provide credit to firms according to a Basel II or III macro-prudential frameworks and manage their liquidity in the interbank market. The Central Bank performs monetary policy according to dfferent types of Taylor rules. We find that the model endogenously generates market freezes in the interbank market which interact with the financial accelerator possibly leading to firm bankruptcies, banking crises and the emergence of deep downturns. This requires the timely intervention of the Central Bank as a liquidity lender of last resort. Moreover, we find that the joint adoption of a three mandate Taylor rule tackling credit growth and the Basel III macro-prudential framework is the best policy mix to stabilize financial and real economic dynamics. However, as the Liquidity Coverage Ratio spurs financial instability by increasing the pro-cyclicality of banks' liquid reserves, a new counter-cyclical liquidity buffer should be added to Basel III to improve its performance further. Finally, we find that the Central Bank can also dampen financial instability by employing a new unconventional monetarypolicy tool involving active management of the interest-rate corridor in the interbank market.

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Early warning indicators and macro-prudential policies: a credit network agent based model

Cited by 5 publications

References 39 publications

Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks

Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks

Macro- And Microprudential Policies: Sweet and Lowdown in a Credit Network Agent-Based Model

Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market

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