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14th Annual DNB Research Conference
2-4 November 2011




Discussion of

“Google matrix of the world trade network”
by L. Ermann and D.L .Shepelyansky


Kimmo Soramäki
www.fna.fi
The paper
• Investigates the properties of a particular centrality measure -
  Pagerank

• And its applicability in describing nodes in commodities trade
  networks

• Ties in with research developed in parallel in matrix theory,
  physics, sociology, computer science

• Question today: can the approach could be used for banking
  networks
Common centrality measures


Degree: number of links

Closeness: distance to other
nodes via shortest paths

Betweenness: number of shortest
paths going through the node

Eigenvector: nodes that are linked by
other important nodes are more central,
probability of a random process
Centrality depends on
network process

Trajectory   geodesic paths, paths, trails or walks
Transmission parallel/serial duplication or transfer




                                                Source: Borgatti (2004)




                                                                          4
Problem with EV centrality

It can be (meaningfully) calculated only for “Giant Strongly
Connected Component” (GSCC)


                                        Random process would
                                        end at GOUT (dangling
                                           links, dead-ends)
Pagerank solves this with
“damping factor”
• Damping factor

   – Gi,j= Si,j
   –        complete symmetric network
   –        EV centrality

• Original story: Web surfer will go to a random page
  after surfing to a page without outbound links
      -> How good of a story for other processes,
      such as trade?
How about bipartite networks

• Bipartite networks have links between two types of nodes
  (call them exporters and importers)

• Are countries in mainly exporter or importers? Does
  it work better for more complex products.

• How much are the results driven by
  the damping factor?

• How much more information does
  Pagerank or Cheirank bring?
All commodities




       PageRank   CheiRank   ImportRank   ExportRank
Barley




         PageRank   CheiRank   ImportRank ExportRank
Use it for financial stability?
• Mostly interested in contagion process, high policy interest for
  measures of systemic importance


• Quite a number of empirical papers on financial systems that look at
  different metrics
    – Interbank payments: Soramäki et al (2006), Becher et al. (2008), Boss et al.
      (2008), Pröpper et al. (2009), Embree and Roberts (2009), Akram and
      Christophersen (2010) …
    – Overnight loans: Atalay and Bech (2008), Bech and Bonde (2009), Wetherilt et
      al. (2009), Iori et al. (2008) and Heijmans et al. (2010), Craig & von Peter
      (2010) …
    – Flow of funds, Credit registry, Stock trading…: Castren and Kavonius (2009),
      Bastos e Santos and Cont (2010), Garrett et al. 2011, Minoiu and Reyes (2011),
      (Adamic et al. 2009, Jiang and Zhou 2011) …
    – More at www.fna.fi/blog
Interpretation for financial stability
• Similar process as payments (transfer), not so sure about
  counterparty risk (parallel duplication)
• Closest to Bech-Chapman-Garratt (2008)
   – “Which Bank Is the “Central” Bank? An Application of Markov Theory to the
     Canadian Large Value Transfer System”



• Page/Cheirank as systemic importance/ vulnerability?
   – “too interconnected to fail”



• What is the theory, what is the process in the network?
   – Contagion models? Cascading failures models?

• How to test it?
   – Regressions? Simulations that emulate the process? Agent-based models?
The paper ends with:

“We hope that this new approach based on the
Google matrix will find further useful applications
to investigation of various flows in trade
and economy.”
Try it with some BIS statistics
• Nodes
   – Countries that have out and inbound links reported
   – Consider GSCC only

• Links
   – National banking systems' on-balance sheet financial claims by country
   – Table 9D, “Foreign claims by nationality of reporting banks, ultimate risk
     basis”

• Look at damping factor and Page/Cheirank plane


                              Has claim from
                       A                          B
                              Owes money to
Alpha 1 (left) and 0.85 (right)
Alpha 0.5 (left) and 0 (right)
Pagerank vs Cheirank
Page vs Cheirank

     Systemically important   Systemically important and vulnerable




                                     Systemically vulnerable
Thank you

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Discussion of "Google matrix of world trade" @ DNB

  • 1. 14th Annual DNB Research Conference 2-4 November 2011 Discussion of “Google matrix of the world trade network” by L. Ermann and D.L .Shepelyansky Kimmo Soramäki www.fna.fi
  • 2. The paper • Investigates the properties of a particular centrality measure - Pagerank • And its applicability in describing nodes in commodities trade networks • Ties in with research developed in parallel in matrix theory, physics, sociology, computer science • Question today: can the approach could be used for banking networks
  • 3. Common centrality measures Degree: number of links Closeness: distance to other nodes via shortest paths Betweenness: number of shortest paths going through the node Eigenvector: nodes that are linked by other important nodes are more central, probability of a random process
  • 4. Centrality depends on network process Trajectory geodesic paths, paths, trails or walks Transmission parallel/serial duplication or transfer Source: Borgatti (2004) 4
  • 5. Problem with EV centrality It can be (meaningfully) calculated only for “Giant Strongly Connected Component” (GSCC) Random process would end at GOUT (dangling links, dead-ends)
  • 6. Pagerank solves this with “damping factor” • Damping factor – Gi,j= Si,j – complete symmetric network – EV centrality • Original story: Web surfer will go to a random page after surfing to a page without outbound links -> How good of a story for other processes, such as trade?
  • 7. How about bipartite networks • Bipartite networks have links between two types of nodes (call them exporters and importers) • Are countries in mainly exporter or importers? Does it work better for more complex products. • How much are the results driven by the damping factor? • How much more information does Pagerank or Cheirank bring?
  • 8. All commodities PageRank CheiRank ImportRank ExportRank
  • 9. Barley PageRank CheiRank ImportRank ExportRank
  • 10. Use it for financial stability? • Mostly interested in contagion process, high policy interest for measures of systemic importance • Quite a number of empirical papers on financial systems that look at different metrics – Interbank payments: Soramäki et al (2006), Becher et al. (2008), Boss et al. (2008), Pröpper et al. (2009), Embree and Roberts (2009), Akram and Christophersen (2010) … – Overnight loans: Atalay and Bech (2008), Bech and Bonde (2009), Wetherilt et al. (2009), Iori et al. (2008) and Heijmans et al. (2010), Craig & von Peter (2010) … – Flow of funds, Credit registry, Stock trading…: Castren and Kavonius (2009), Bastos e Santos and Cont (2010), Garrett et al. 2011, Minoiu and Reyes (2011), (Adamic et al. 2009, Jiang and Zhou 2011) … – More at www.fna.fi/blog
  • 11. Interpretation for financial stability • Similar process as payments (transfer), not so sure about counterparty risk (parallel duplication) • Closest to Bech-Chapman-Garratt (2008) – “Which Bank Is the “Central” Bank? An Application of Markov Theory to the Canadian Large Value Transfer System” • Page/Cheirank as systemic importance/ vulnerability? – “too interconnected to fail” • What is the theory, what is the process in the network? – Contagion models? Cascading failures models? • How to test it? – Regressions? Simulations that emulate the process? Agent-based models?
  • 12. The paper ends with: “We hope that this new approach based on the Google matrix will find further useful applications to investigation of various flows in trade and economy.”
  • 13. Try it with some BIS statistics • Nodes – Countries that have out and inbound links reported – Consider GSCC only • Links – National banking systems' on-balance sheet financial claims by country – Table 9D, “Foreign claims by nationality of reporting banks, ultimate risk basis” • Look at damping factor and Page/Cheirank plane Has claim from A B Owes money to
  • 14. Alpha 1 (left) and 0.85 (right)
  • 15. Alpha 0.5 (left) and 0 (right)
  • 17. Page vs Cheirank Systemically important Systemically important and vulnerable Systemically vulnerable