Supply Network Formation and Fragility

We model the production of complex goods in a large supply network. Each firm sources several essential inputs through relationships with other firms. Individual supply relationships are at risk of idiosyncratic failure, which threatens to disrupt production. To protect against this, firms multisource inputs and strategically invest to make relationships stronger, trading off the cost of investment against the benefits of increased robustness. A supply network is called fragile if aggregate output is very sensitive to small aggregate shocks.

Prof. Daniel Zizzo (University of Queensland)

Hosts:

Associate Professor Edoardo Gallo

Professor Matt Elliott

Visiting from:

3rd January 2023 - 19th January 2023

networks

Learning in Canonical Networks

Subjects observe a private signal and then make an initial guess; they observe their neighbors’ guesses and guess again, and so forth. We study learning dynamics in three networks: Erdös-Rényi, Stochastic Block (reflecting homophily) and Royal Family (that accommodates both highly connected celebrities and local intearctions). We find that the Royal Family network is more likely to sustain incorrect consensus and that the Stochastic Block network is more likely to persist with diverse beliefs. These aggregate patterns are consistent with individuals following DeGroot updating rule.

Gabriela Stockler

Host: 

Prof. Vasco Carvalho and Prof. Matt Elliott

Visiting from: 

22nd May - 22nd July 2022

Stats Room, Desk 20:211

networks
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