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Journal of Economic Interaction and Coordination

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13-01-2023 | Regular Article

The financial network channel of monetary policy transmission: an agent-based model

Authors: Michel Alexandre, Gilberto Tadeu Lima, Luca Riccetti, Alberto Russo

Published in: Journal of Economic Interaction and Coordination | Issue 3/2023

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Abstract

The purpose of this paper is to explore the impact of monetary policy shocks on a financial network, which we dub the “financial network channel of monetary policy transmission”. To this aim, we develop a agent-based model (ABM) in which banks extend loans to firms. The resulting bank–firm credit network is structured as determined by plausible behavioral assumptions, with both firms and banks being always willing to close a credit deal with the network partner perceived to be less risky. As our ABM succeeds in reproducing several key stylized facts of bank–firm credit networks, we then assess through simulations how exogenous shocks to the policy interest rate affect some key topological measures of the bank–firm credit network (density, assortativity, size of largest component, and degree distribution). Our simulations show that such topological features of the bank–firm credit network are significantly affected by shocks to the policy interest rate, with such an impact varying quantitatively and qualitatively with the sign, magnitude, and duration of the shocks.

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There are other types of indirect interconnections that give rise to the operation of other mechanisms of shock propagation but are not our object of study here. For instance, when agents are interconnected through common asset exposures, shock propagation is engendered by fire sales (Acharya 2009). We neglect these mechanisms for simplicity, in order to keep the model clearly understandable. Our choice can be justified by the fact that most of the existing literature even neglects bank–firm linkages—however, there are relevant exceptions such as Huser and Kok (2020)—, being restricted to the interbank market (Battiston et al. 2016). For a thorough review on financial contagion mechanisms, see Riccetti (2022).

We use the term “financial investment” to stress the difference with respect to the most common use of I as real investment. However, despite being a financial variable, this amount is used for real investment and production.

HtM consumers allocate almost all, if not all, their current income to consumption due to unsophisticated behavior (of the non-optimizing or rule-of-thumb variety) or inability to trade in asset markets because of high transaction costs (Weil 1992). There is robust empirical evidence that HtM consumers correspond to a large fraction of households in developed countries and have a high marginal propensity to consume even out of temporary income shocks (Kaplan et al. 2014; Attanasio et al. 2020). Another feature of our model that further validates the assumption that households behave as HtM consumers, and which is in keeping with the evidence offered in Kaplan and Violante (2010), is that households do not have access to consumer credit.

Abildgren et al. (2013) use data for Denmark to show that during the financial crisis of 2008-2009 firms with a weak bank had a significantly higher probability of default than firms with relations to sound banks, even after controlling for differences in the credit quality of firms.

A firm does not strategically and deliberately demand credit from a highly leveraged bank betting on the prospect that the bank is likely or about to go bankrupt, so that the respective debt will not have to be paid back in full. The reason is that the government is openly and credibly committed to bail out a bank if its net worth becomes negative, as described later.

A comprehensive review of the research on the structure of interbank relations and theoretical models set forth to evaluate the contagious potential of shocks via the interbank network is provided in Lux (2017).

This minimum level is equal to the maximum between i) the net worth necessary to meet the maximum leverage ratio: \(BO_{j,t}=max(0,\kappa B_{j,t}^{S}-NPL_{j,t})\), and ii) 5% of the firms’ average net worth.

In general, the resilience or robustness of a network is related to the ability of its nodes to communicate being unaffected even by unrealistically high failure rates. In our case, it refers to the ability of firms (banks) to borrow from (extend loans to) banks (firms). In fragmented networks, in which the fraction of nodes belonging to the largest cluster is small, the removal of a link will create isolated nodes with a higher probability. For more details, see, for instance, Albert et al. (2000) and Newman (2003).

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Title: The financial network channel of monetary policy transmission: an agent-based model
Authors: Michel Alexandre
Gilberto Tadeu Lima
Luca Riccetti
Alberto Russo
Publication date: 13-01-2023
Publisher: Springer Berlin Heidelberg
Published in: Journal of Economic Interaction and Coordination / Issue 3/2023
Print ISSN: 1860-711X
Electronic ISSN: 1860-7128
DOI: https://doi.org/10.1007/s11403-023-00377-w

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