A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market

P. Mazzarisi, P. Barucca, F. Lillo and D. Tantari

European Journal of Operational Research, 2020, vol. 281, issue 1, 50-65

Abstract: We propose a dynamic network model where two mechanisms control the probability of a link between two nodes: (i) the existence or absence of this link in the past, and (ii) node-specific latent variables (dynamic fitnesses) describing the propensity of each node to create links. Assuming a Markov dynamics for both mechanisms, we propose an Expectation-Maximization algorithm for model estimation and inference of the latent variables. The estimated parameters and fitnesses can be used to forecast the presence of a link in the future. We apply our methodology to the e-MID interbank network for which the two linkage mechanisms are associated with two different trading behaviors in the process of network formation, namely preferential trading and trading driven by node-specific characteristics. The empirical results allow to recognize preferential lending in the interbank market and indicate how a method that does not account for time-varying network topologies tends to overestimate preferential linkage.

Keywords: Temporal networks; Markov processes; Expectation-Maximization; Interbank market; Link prediction (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:281:y:2020:i:1:p:50-65

DOI: 10.1016/j.ejor.2019.07.024

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