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Estimating the Structure of the Payment Network in the LVTS: An Application of Estimating Communities in Network Data

James Chapman () and Yinan Zhang

Staff Working Papers from Bank of Canada

Abstract: In the Canadian large value payment system an important goal is to understand how liquidity is transferred through the system and hence how efficient the system is in settling payments. Understanding the structure of the underlying network of relationships between participants in the payment system is a crucial step in achieving the goal. The set of nodes in any given network can be partitioned into a number of groups (or "communities"). Usually, the partition is not directly observable and must be inferred from the observed data of interaction flows between all nodes. In this paper we use the statistical model of Copic, Jackson, and Kirman (2007) to estimate the most likely partition in the network of business relationships in the LVTS. Specifically, we estimate from the LVTS transactions data different "communities" formed by the direct participants in the system. Using various measures of transaction intensity, we uncover communities of participants that are based on both transaction amount and their physical locations. More importantly these communities were not easily discernible in previous studies of LVTS data since previous studies did not take into account the network (or transitive) aspects of the data.

Keywords: Payment clearing and settlement systems; Financial stability (search for similar items in EconPapers)
JEL-codes: C11 D85 G20 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2010
New Economics Papers: this item is included in nep-ban and nep-net
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Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:10-13

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