Systemic Risk on Trade Credit Systems: with the Tangible Interconnectedness

Jisang Lee (), Duk Hee Lee () and Sung-Guan Yun ()
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Jisang Lee: Korea Advanced Institute of Science and Technology (KAIST) Bldg. N22
Duk Hee Lee: Korea Advanced Institute of Science and Technology (KAIST) Bldg. N22
Sung-Guan Yun: Payment and Settlement Systems Department

Computational Economics, 2018, vol. 51, issue 2, No 3, 226 pages

Abstract: Abstract Using the unique data set of all the transactions with trade credit via 17 major banks in Korea during 2008–2012, we investigate the relationship between the network structure and the contagion of failures in the financial network. Due to the difference of terms between two types of trade credits in Korea, Account Receivable Financing and Supplier Loan, a non-trivial directed network of banks and firms can be formulated. With respect to this trade credit network (TCN), we propose a measure for systemic risk on liquidity channels by calculating the monthly potential risk of liquidity shortage in the worst-case scenarios and show some comparisons with the basic network characteristics. Results claim that the PageRank centralities of individual banks have significant positive impact on the level of systemic risk. More on, degrees of nodes in TCN follows power-law distributions and the network heterogeneity of given month also has significant positive impact on the risk level: that is, the high degree of imbalance in the liquidity channel implies the severe systemic shortage of the liquidity in the worst-case.

Keywords: Systemic risk; Trade credit; Liquidity channels; Tangible interconnectedness (search for similar items in EconPapers)
JEL-codes: D85 G32 G33 L14 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10614-016-9632-x

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