Stability of the world trade web over time

Stability of the World Trade Web over time.

Scott PaulsDepartment of MathematicsDartmouth College

Conference on Emergent Risk, Princeton University

September 28-29,2012

Stability of the World Trade Web over time.

Scott PaulsDepartment of MathematicsDartmouth College

Conference on Emergent Risk, Princeton University

September 28-29,2012

Adaptabilit

y

Systemic and emergent risk

“Whereas systemic risk is the threat that individual failures or accidents represent to a system through the process of contagion, emergent risk is the threat to the individual parts produced by their participation in and interaction with the system itself.” (Centeno and Tham)

Conference on Emergent Risk, Princeton University

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Stability and robustness

Structure

Dynamics

Robustness

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We use network models: actors are nodes, relationships are edges.

We construct dynamics to model exchanges between the actors.

We define robustness in terms of responses to shocks.

World Trade Web

nodes are countries.

edges are directed and weighted, giving the dollars that flow from country i to country j for traded goods.

dynamics are given by the Income-Expenditure model.

Conference on Emergent Risk, Princeton University

September 28-29,2012

Barbieri, Katherine, Omar M. G. Keshk, and Brian Pollins. 2009. “TRADING DATA: Evaluating our Assumptions and Coding Rules.” Conflict Management and Peace Science. 26(5): 471-491.

Income-Expenditure model

In/out-strength:

Relationships:

Iterative model:

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propensity to spend

debt

Markov model

Attacks on the system

Edge deformation: policy decisions, sharp trade evolution.

Bilateral edge deletion: war, collapse of trade agreement.

Node deformation: internal collapse (e.g. bhat collapse in the 1980s)

Node deletion: unrealistic but useful as a type of worst case scenario

Maximal Extinction Analysis (MEA): really a worst case scenario!

Conference on Emergent Risk, Princeton University

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Power and robustness

Given an attack, a , we measure two things:

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Total initial income

Income after rebalancing

Conference on Emergent Risk, Princeton University

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WTWs are “robust yet fragile”

Left hand side: TARGETED ATTACKThe strength of maximal attacks of each type. Colored bars (and circles) indicate significance.

Right hand side: RANDOM ATTACKCircles indicate the proportion of all possible attacks which are not significant.

The role of connectance

Conference on Emergent Risk, Princeton University

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The role of connectance

Conference on Emergent Risk, Princeton University

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A closer look

Conference on Emergent Risk, Princeton University

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U.S./Canada link

U.S.deformation

Conclusions and the big picture

Conference on Emergent Risk, Princeton University

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We see evidence that increased connectance has two effects related to systemic risk.

1. On one hand, denser connections allow for more paths through which shocks may be mitigated.

2. But, on the other, denser connection patterns provide more paths along which collapse can spread.

These two are in tension.

With regard to emergent risk, we see an additional wrinkle related to connectance coupled with the topology of the network.

3. Denser connections allow for propagation of shocks which, while possibly mitigated overall, can have adverse impact on individual countries.

Emergent and Systemic riskIn our model, the tension is resolved in different ways depending on the size of the shock.

Systemic risk

a. Smaller shocks are easily absorbed into the system (and sometimes result in income increases!).

b. But, there is a tipping point above which the larger shocks spark a substantial contagion effect.

Emergent Risk

c. Even with smaller shocks, we see evidence that mere participation in the WTW brings new risk.

d. Large shocks amplify this risk.

We need a new lexicon to describe these types of networks.Conference on Emergent Risk,

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