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Algorithmic and Economic Aspects of Networks

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Algorithmic and Economic Aspects of Networks. Nicole Immorlica. Networked Markets. Garmets Market Marseille Fish Market Labor Markets. Why Network. Trust, predicability, referrals, incomplete contracts, friction, moral hazard/adverse selection price, reputation. - PowerPoint PPT Presentation
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Algorithmic and Economic Aspects of Networks Nicole Immorlica
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Page 1: Algorithmic and Economic Aspects of Networks

Algorithmic and Economic Aspects of Networks

Nicole Immorlica

Page 2: Algorithmic and Economic Aspects of Networks

Networked Markets

Garmets Market

Marseille Fish Market

Labor Markets

Page 3: Algorithmic and Economic Aspects of Networks

Why Network

Trust, predicability, referrals, incomplete contracts, friction,moral hazard/adverse selection

price, reputation

Page 4: Algorithmic and Economic Aspects of Networks

Labor Markets

“You hear about jobs through your friends.”

– Granovetter

better

Page 5: Algorithmic and Economic Aspects of Networks

Boorman’s Model

Network of strong and weak ties

Preferential flow of information about job opennings through network

Page 6: Algorithmic and Economic Aspects of Networks

Strong and Weak Ties

Strong

Weak

Weak + λ∙Strong = Time

Page 7: Algorithmic and Economic Aspects of Networks

Information Flow

1) People need jobs with prob. μ.2) People hear about jobs with prob. δ.

3) People tell (stronger) friends about jobs.

Page 8: Algorithmic and Economic Aspects of Networks

Boorman’s ResultsStudy trees, fix degree of strong/weak ties, consider equilibria via simulation

1) As cost of strong ties , # strong ties .

2) As unemployment prob. , # strong ties .

Page 9: Algorithmic and Economic Aspects of Networks

What’s Missing?

network architecture, e.g., weak ties more likely to be bridges

correlation in employment state over time and network structure

Page 10: Algorithmic and Economic Aspects of Networks

Carvo-Armengol & Jackson

Drop strong/weak distinction, but incorporate time.

Page 11: Algorithmic and Economic Aspects of Networks

Information Flow

1) People need jobs with prob. μ.2) People hear about jobs with prob. δ.

3) People tell friends about jobs.

Page 12: Algorithmic and Economic Aspects of Networks

Tarred with the Same Brush

Time causes correlation in employment:

you are more likely to find a job if more of your friends have jobs

Page 13: Algorithmic and Economic Aspects of Networks

Persistance of (Lack of) Luck

The longer you are unemployed, the less likely you will find a job tomorrow:

because you are more likely to have more unemployed neighbors

Page 14: Algorithmic and Economic Aspects of Networks

Education

Agents can pay cost ci to be educated.

educated – apply previous model

uneducated – payoff zero

Page 15: Algorithmic and Economic Aspects of Networks

Poverty Traps

Payoff: 0.5 – ci Payoff: 0.6 – ci

Payoff: 0.69 – ciPayoff: 0.65 – ci

Page 16: Algorithmic and Economic Aspects of Networks

Networked Exchange Theory

Network represents potential trades

what prices result?

Page 17: Algorithmic and Economic Aspects of Networks

Nash BargainingHow to split a dollar?

Matt ($0.50) Mykell ($0.50)

If negotiations fail, you get nothing.

Page 18: Algorithmic and Economic Aspects of Networks

Nash BargainingHow to split a dollar?

Trevor ($0.70) William ($0.30)

If negotiations fail, Trevor gets $0.60, William gets $0.20.

Page 19: Algorithmic and Economic Aspects of Networks

Nash Bargaining

Any division in which each agent gets at least the outside option is an equilibrium.

Yet …. agents usually agree to split the surplus.

Page 20: Algorithmic and Economic Aspects of Networks

Nash BargainingIf when negotiation fails,

- A gets $a - B gets $b

Then when succeed,- A gets $(a + s/2) - B gets $(b + s/2)

s = (1 – a – b) is the surplus

Page 21: Algorithmic and Economic Aspects of Networks

Nash Bargaining

Nash: “Agents will agree to split the surplus.”

Motivated by axiomatic approach, optimization approach, and outcome of particular game-theoretic formulations.

Page 22: Algorithmic and Economic Aspects of Networks

Bargaining in Networks

Value of outside option arises as result of network structure.

Page 23: Algorithmic and Economic Aspects of Networks

Bargaining in Networks

William ($0.50)

Arun ($0.50)

Bach ($0)

Matt ($0)

Mykell ($0)

Transactions worth $1.

Only one transaction per person!

Page 24: Algorithmic and Economic Aspects of Networks

Bargaining in Networks

Almost all the money.

Page 25: Algorithmic and Economic Aspects of Networks

Bargaining in Networks

v

v gets between 7/12 and 2/3 in negotiation to left.

Page 26: Algorithmic and Economic Aspects of Networks

Bargaining in Networks

v

v gets between 1/2 and 1 in negotiation to left.

Page 27: Algorithmic and Economic Aspects of Networks

Cook and Yamagishi

A solution for a network G is a matching M and a set of values νu for each node u s.t.,

- For (u,v) in M, νu + νv = 1- For unmatched nodes u, νu

= 0

Page 28: Algorithmic and Economic Aspects of Networks

Stable Outcomes

Node u could negotiate with unmatched neighbor v and get (1 - νv).

Outside option of u is αu = maximum over unmatched neighbors v of (1 - νv).

Page 29: Algorithmic and Economic Aspects of Networks

Stable Outcomes

Defn. An outcome is stable if for all u, νu ≥ αu.

Notice there are many stable outcomes, so which one should we

expect to find?

Page 30: Algorithmic and Economic Aspects of Networks

Balanced Outcomes

Each individual bargaining outcome should agree with the Nash bargaining solution.

suv = 1 - αu - αv

νu = αu + s/2

And similarly for νv.

Page 31: Algorithmic and Economic Aspects of Networks

Computing Balanced Outcomes

A balanced outcome exists if and only if a stable outcome exists.

Balanced outcomes can be computed and characterized using Edmonds-Galai decompositions.

[Kleinberg-Tardos STOC’08]

Page 32: Algorithmic and Economic Aspects of Networks

Assignment:• Readings:– Social and Economic Networks, Chapter

10– The two Kearns papers or a paper on

labor markets of your choosing (see refs in book)

• Reaction to paper• Presentation volunteers?


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