Shock Propagations in Granular Networks

30 Pages Posted: 12 Jul 2016

See all articles by Daisuke Fujii

Daisuke Fujii

University of California, Los Angeles (UCLA)

Date Written: July 7, 2016

Abstract

This paper studies a number of features of transaction networks, firm sales growth, and buyer-supplier comovements of sales using a large-scale dataset on the Japanese interfirm transaction network. Larger firms have higher sales growth rates and smaller growth dispersion. Well-connected firms also exhibit higher growth rates, but there is no systematic relationship between the number of partners (degree) and sales growth dispersion. Using a statistical test for spatial interdependence, it is confirmed that there exists a significant network interdependence of sales growth. By employing spatial autoregressive models, various propagation factors are estimated. In the baseline specification, the elasticity of average sales growth of suppliers is estimated to be 0.153 while that of customers is 0.257 for year 2012. In all years, the upstream propagation factor is larger than the downstream factor implying a difficulty of replacing an existing customer or adjusting to a demand shock. The manufacturing sector is characterized by a large degree of propagation. For both downstream and upstream propagations, manufacturing and wholesale sectors exhibit higher propagations factors while retail and service sectors exhibit lower propagation factors. The interdependence of intermediate physical inputs produced by other firms may generate an additional margin for the buyer-supplier comovements. It was also found that larger firms have higher propagation factors. Larger firms have more partners, and their degree of propagation is also higher. This result stresses an even larger impact of big firms for aggregate fluctuations in a granular production network.

Keywords: networks, shock propagation, firm growth, and aggregate volatility

JEL Classification: D22, D57, D85, L14

Suggested Citation

Fujii, Daisuke, Shock Propagations in Granular Networks (July 7, 2016). USC-INET Research Paper No. 16-23. Available at SSRN: https://ssrn.com/abstract=2808094 or http://dx.doi.org/10.2139/ssrn.2808094

Daisuke Fujii (Contact Author)

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

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