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Network Topology and Systemically Important Firms in the Interfirm Credit Network

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Abstract

In a transaction between two firms, the buyer is expected to pay the seller with cash; however, due to the buyer’s lack of liquidity, an account receivable might be provided instead. Accounts Receivable Financing (ARF) is a type of trade credit that facilitates Korean interfirm transactions. Under ARF, the obligation to reimburse the bank is imputed to the seller if the buyer does not repay the loan to the bank. When the buyer confronts a liquidity shortage and fails to repay the trade credits, unfortunately, the shock is not limited to damage to only the seller because it propagates throughout the interfirm network. The shock is easily propagated because it is highly likely that the seller would also be unable to repay obligations to its own sellers. Since annual interfirm networks follow a scale-free network model, a single liquidity shock triggers a systemic risk. The insolvency of topologically more central buyer firms is shown to pose a higher potential risk to the financial market. In contrast, the firm size is not significantly related to potential risk. Therefore, firms with high centrality should be closely monitored to prevent insolvency crisis and propagation of the liquidity shock in the interfirm network.

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Authors and Affiliations

  1. School of Business and Technology Management, College of Business, KAIST, Daejeon, 34141, Republic of Korea

    Ohsung Kwon, Seung Hun Han, Yang Hon Chung & Duk Hee Lee

  2. Payment and Settlement Systems Department, Bank of Korea, Seoul, 04531, Republic of Korea

    Sung-guan Yun

Authors
  1. Ohsung Kwon
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  2. Sung-guan Yun
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  3. Seung Hun Han
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  4. Yang Hon Chung
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  5. Duk Hee Lee
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Correspondence to Duk Hee Lee.

Additional information

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (2014S1A3A2044459).

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Kwon, O., Yun, Sg., Han, S.H. et al. Network Topology and Systemically Important Firms in the Interfirm Credit Network. Comput Econ 51, 847–864 (2018). https://doi.org/10.1007/s10614-017-9648-x

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