  Crises like COVID-19 or the Japanese earthquake in 2011 exposed the fragility
of corporate supply networks. The production of goods and services is a highly
interdependent process and can be severely impacted by the default of critical
suppliers or customers. While knowing the impact of individual companies on
national economies is a prerequisite for efficient risk management, the
quantitative assessment of the involved economic systemic risks (ESR) is
hitherto practically non-existent, mainly because of a lack of fine-grained
data in combination with coherent methods. Based on a unique value added tax
dataset we derive the detailed production network of an entire country and
present a novel approach for computing the ESR of all individual firms. We
demonstrate that a tiny fraction (0.035%) of companies has extraordinarily high
systemic risk impacting about 23% of the national economic production should
any of them default. Firm size alone cannot explain the ESR of individual
companies; their position in the production networks does matter substantially.
If companies are ranked according to their economic systemic risk index (ESRI),
firms with a rank above a characteristic value have very similar ESRI values,
while for the rest the rank distribution of ESRI decays slowly as a power-law;
99.8% of all companies have an impact on less than 1% of the economy. We show
that the assessment of ESR is impossible with aggregate data as used in
traditional Input-Output Economics. We discuss how simple policies of
introducing supply chain redundancies can reduce ESR of some extremely risky
companies.
