Propagation of negative shocks across nation-wide firm networks

Inoue, Hiroyasu, and Yasuyuki Todo. "Propagation of negative shocks across nation-wide firm networks." PloS one 14.3 (2019): e0213648.

21 Pages Posted: 15 Mar 2017 Last revised: 21 Jul 2019

See all articles by Hiroyasu Inoue

Hiroyasu Inoue

University of Hyogo, Graduate School of Information Science

Yasuyuki Todo

Waseda University

Date Written: March 13, 2017

Abstract

This paper examines how negative shocks due to, for example, natural disasters, propagate through supply chains, applying a simulation technique to actual data on supply chains of Japanese firms. We obtained the five results. (1) Network structures severely affect the speed of propagation in the medium run and the total loss in the long run. The scale-free nature of the actual supply-chain network, i.e., the power-law degree distribution, leads to faster propagation, while dense links between firms within the community in the actual network slow propagation. (2) More intensive damages, i.e., larger damages on fewer firms, result in faster propagation than extensive damages of the same total size. (3) When substitution of undamaged suppliers for damaged suppliers is more difficult, propagation of negative shocks becomes substantially fast. (4) Direct damages in industrial regions promote faster propagation than those in rural regions. (5) Different sectoral damages cause large differences in the speed of propagation and the long-run loss. All of these results imply that the same size of direct damages by disasters can generate considerably different damages, depending on the structure of the supply-chain network in the economy.

Keywords: supply chain, propagation, disaster, simulation

JEL Classification: L14

Suggested Citation

Inoue, Hiroyasu and Todo, Yasuyuki, Propagation of negative shocks across nation-wide firm networks (March 13, 2017). Inoue, Hiroyasu, and Yasuyuki Todo. "Propagation of negative shocks across nation-wide firm networks." PloS one 14.3 (2019): e0213648., Available at SSRN: https://ssrn.com/abstract=2932559 or http://dx.doi.org/10.2139/ssrn.2932559

Hiroyasu Inoue (Contact Author)

University of Hyogo, Graduate School of Information Science ( email )

7-1-28 Minato-jima, Minami-machi
Chuo-ku
Kobe, Hyogo 650-0047
Japan

Yasuyuki Todo

Waseda University ( email )

1-104 Totsukamachi, Shinjuku-ku
tokyo, 169-8050
Japan

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