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Assessing Interbank Contagion Risk Using Consolidated Data

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This study uses the maximum entropy method to estimate bilateral interbank exposure in order to simulate the contagion effect in the UK interbank market using consolidated data. Almost all existing studies use unconsolidated data, which could significantly distort the real contagion effect as the banking sectors of most countries are highly concentrated with most large banks owning a significant number of subsidiaries. The results show that exposure is much more severe using consolidated data, implying that some money center banks or systematically important banks were underestimated by the contagion model before the 2008 financial crisis.

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Fig. 1


  1. 1.

    Contagious defaults arise when losses from exposure to defaulting banks exceed the capital of the creditor bank. Banks that fail because of contagion are then scaled by adding up the total assets of each defaulting bank divided by the total assets of the entire banking sector. Total assets are counted, rather than a proportion of assets, such as interbank balances, considering that the liquidation process involves all assets when banks go bankrupt. This calculation to measure contagion is uniform throughout the study. The reason is that the study emphasizes the measurement of contagious impact of defaulting banks as entities rather than the measurement of its source of contagion, that is, defaulting interbank assets.

  2. 2.

    This type of data is not always available at the supervisory level, at least not before 2008, as the literature discussion in this paper reveals. The banks of some countries are only required to report large exposure data. For instance, as Figure 1 shows, reports of Switzerland, Germany, Austria, Denmark, the UK, Belgium, and Italy are confined to incomplete information. Therefore, when the contagion impact of these countries is measured, the maximum entropy approach has to be applied to deal with the data limitation.

  3. 3.

    Here, contagious defaults refer to total assets of defaulting banks. Total assets are counted rather than a proportion of assets, such as interbank balances, considering that the liquidation process involves the entire assets when banks go bankrupt.

  4. 4.

    Tier 1 capital is the core measure of a bank’s financial strength from a regulator’s point of view. Tier-1 capital consists primarily of shareholders’ equity but may also include preferred stock, which is irredeemable and non-cumulative, and retained earnings.

  5. 5.

    The interbank loan data are obtained from the annual reports of banks with lump sum numbers under the liability items of "loans and advances to banks" and "deposits by banks". Unfortunately, the bank books do not reveal the category of securities collateralized when loans are made between banks. However, since the contagion simulation assumes the first bank defaults because of some idiosyncratic shock, the classification limitation has little impact on the magnitude of contagion.

  6. 6.

    The joint default of small banks may cause contagion. However, as the total interbank assets of the small banks exceed the combined interbank assets of many of the largest banks, the joint default amounts to an assumption of a common macroeconomic shock to all banks. Hence, instead of including the aggregate data of small banks, this study simulates the common shock later by assuming that most of the interbank assets of a bank turn out to be defective. The historical comparison section of this paper examines this scenario from 2002 to 2004.

  7. 7.

    The money center structure is constructed in comparison with the complete market structure. However, the assumption may be slightly divergent from the real market, in which small and mid-sized banks transact with each other. This study allows this to occur by weighting the shares of transactions of small banks. Higher weights are assigned to the transactions of small banks with large banks while lower shares represent transactions among small banks.


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Correspondence to Xiaojun Li.

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Li, X., Dong, S. Assessing Interbank Contagion Risk Using Consolidated Data. Int Adv Econ Res 22, 421–432 (2016).

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  • Entropy maximization
  • Systemic contagion
  • Consolidated information


  • G20