Modelling default dependence in automotive supply networks using vine-copula

Abstract

This paper presents an intuitive model for default dependencies in supply networks and its application in firms’ capital management. Modern supply chain networks are characterised by horizontal ties between firms within a particular industry or group, which are sequentially arranged based on vertical ties between firms in different layers. The recognition and accounting of these simultaneous interdependencies is crucial for a more advanced understanding of complex inter-organisational relations. Using the state-of-the art vine-copulae, we model these multidimensional interdependencies in the automotive industry, and capture the default tail dependency between alliance partners. Further, we apply our model to determine the optimal economic capital, such that companies can absorb unexpected losses from defaults in supply chain, while avoiding over-capitalisation. Our findings should spur managers to analyse their supplier networks with respect to default dependencies and to take this phenomenon into consideration when making sourcing decisions.

Keywords:

• default dependence
• supply chain
• vine-copula
• partial correlation
• tail dependence
• economic capital

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 Interested reader are also encouraged to review Ivanov et al. (2017), Ivanov (2017), Ivanov and Rozhkov (2017).

2 http://www.motorintelligence.com

3 Proximity condition implies that if two nodes are joined by an edge in tree $j+1$, the corresponding edges in tree j share a node. For more formal definition, see Kim et al. (2011), Definition 4.iii.