27
An Experimental Test of House Matching Algorithms Onur Kesten Carnegie Mellon University Pablo Guillen University of Sydney

An Experimental Test of House Matching Algorithms

Embed Size (px)

DESCRIPTION

An Experimental Test of House Matching Algorithms. Onur Kesten Carnegie Mellon University Pablo Guillen University of Sydney. Mechanism Design Overview. FCC spectrum auctions (McMillan (1994), Cramton (1995), McAfee & McMillan (1996), Milgrom (2000) ) - PowerPoint PPT Presentation

Citation preview

Page 1: An Experimental Test of House Matching Algorithms

An Experimental Test of House Matching Algorithms

Onur KestenCarnegie Mellon University

Pablo GuillenUniversity of Sydney

Page 2: An Experimental Test of House Matching Algorithms

Mechanism Design Overview FCC spectrum auctions (McMillan (1994), Cramton

(1995), McAfee & McMillan (1996), Milgrom (2000) )

NRMP (Roth (2002), Roth & Peranson (1999))

School choice (Abdulkadiroglu & Sonmez (2003), Chen & Sonmez (2004), Abdulkadiroglu, Sonmez, Pathak, & Roth (2005), Kesten (2005))

House allocation Chen & Sonmez (2002)

Kidney exchange (Roth, Sonmez, & Unver (2004, 2005), Sonmez & Unver (2006))

Page 3: An Experimental Test of House Matching Algorithms

House allocation with existing tenants Problem components - newcomers - existing tenants - priority order

Main application: Graduate housing

Examples: Michigan, Princeton, Rochester, Stanford, CMU, MIT, etc.

Page 4: An Experimental Test of House Matching Algorithms

Outline of the Talk Model

Real-life Mechanisms

1. Random serial dictatorship with squatting rights

2. MIT-NH4

A mechanism from recent theory

3. Top trading cycles mechanism

Main result

Page 5: An Experimental Test of House Matching Algorithms

The Model

Agents: I={1, 2,…, n}

- Existing tenants: IE

- Newcomers: IN

Houses H={h1, h2,…, hm}

- Occupied houses: IO

- Vacant houses: IV

A list of strict preferences R=(Ri)i€I

A priority order f:{1,…,n} -> I

Page 6: An Experimental Test of House Matching Algorithms

A house allocation problem is a pair consisting of

List of agents’ preferences (R) A priority order (f)

An allocation is a list s.t.

every agent is assigned at most one house no house is assigned to more than one agent

Page 7: An Experimental Test of House Matching Algorithms

What is a mechanism?

Allocations

Mechanism

(R, f)

(R, f)

(R, f)

µ1

µ2

µ3

Page 8: An Experimental Test of House Matching Algorithms

What is a good mechanism?

1. Individual rationality (existing tenants)

2. Fairness (priority order)

3. Efficiency (e.g. Pareto)

4. Incentive compatibility (no gaming)

Page 9: An Experimental Test of House Matching Algorithms

Properties of Mechanisms

1. Individual Rationality: No existing tenant is assigned a house which is worse for him than his current house.

Page 10: An Experimental Test of House Matching Algorithms

Properties of Mechanisms

2. Fairness: An agent prefers someone else’s assignment (to his own) only if either of the following holds:

The other agent is an existing tenant who is

assigned his own house The other agent has higher priority

Page 11: An Experimental Test of House Matching Algorithms

Properties of Mechanisms

3. Pareto Efficiency: It is not possible to find an alternative allocation that makes

All agents at least as well off At least one agent strictly better off

However, an inefficient mechanism need not always select inefficient outcomes!!!

Page 12: An Experimental Test of House Matching Algorithms

Properties of Mechanisms

4. Strategy-proofness (Incentive compatibility):

It is always a dominant strategy for each agent to truthfully reveal his preferences.

Page 13: An Experimental Test of House Matching Algorithms

Trade-offs between propertiesProposition 1: There is no mechanism which is

individually rational, fair, and Pareto efficient.

Individually rational Fair

Pareto efficient

Strategy-proof

Page 14: An Experimental Test of House Matching Algorithms

Real-life Mechanisms

1. Random serial dictatorship with squatting rights

(CMU, Duke, Harvard, Northwestern, Upenn, etc. )

Each existing tenant initially decides whether to participate or not. If participates, gives up his current house

A priority ordering f of participants is randomly chosen

First agent (according to f) is assigned his favorite house, second agent is assigned his favorite house among the remaining houses, and so on.

Page 15: An Experimental Test of House Matching Algorithms

Random serial dictatorship with squatting rights

Properties

1. Individual rationality

2. Fairness

3. Pareto efficiency

4. Incentive compatibility

Page 16: An Experimental Test of House Matching Algorithms

Real-life Mechanisms2. MIT-NH4 Mechanism

1. The first agent is tentatively assigned his top choice among all houses, the

next agent is tentatively assigned his top choice among the remaining houses, and so on, until a squatting conflict occurs.

2. A squatting conflict occurs if it is the turn of an existing tenant but every remaining house is worse than his current house. That means someone else, the conflicting agent, is tentatively assigned the existing tenant's current house. When this happens, solve the squatting conflict as follows:

Assign the existing tenant his current house and remove him Erase all tentative assignments starting after the conflicting agent

3. The process is over when there are no houses or agents left.

Page 17: An Experimental Test of House Matching Algorithms

MIT-NH4 MechanismProposition 2:

1. Individual rationality

2. Fairness

3. Pareto efficiency

4. Incentive compatibility

Page 18: An Experimental Test of House Matching Algorithms

The best fair and individually rational mechanism

Corollary: The MIT-NH4 mechanism Pareto dominates any other fair and individually rational mechanism.

Page 19: An Experimental Test of House Matching Algorithms

A mechanism from recent theory3. Top Trading Cycles Mechanism (Abdulkadiroglu & Sonmez)

Assign the first agent (according to f) his top choice, the second agent his top choice among the remaining houses, and son on, until someone demands the house of an existing tenant.

If at that point the existing tenant whose house is demanded is already assigned a house, then do not disturb the procedure.

Otherwise insert him to the top and proceed. Similarly, insert any existing tenant who is not already served at the top of the line once his or her house is demanded.

If at any point, a loop forms, (it is formed by exclusively existing tenants

and each of them demands the house of the tenant next in the loop), remove all agents in the loop by assigning them the houses they demand, and proceed.

Page 20: An Experimental Test of House Matching Algorithms

Top Trading Cycles Mechanism

Properties

1. Individual rationality

2. Fairness

3. Pareto efficiency

4. Incentive compatibility

Page 21: An Experimental Test of House Matching Algorithms

SUMMARY

Individually rational Fair

Pareto efficient

Strategy-proof

TTC

RSDwSR

MIT-NH4

Page 22: An Experimental Test of House Matching Algorithms

TTC vs. RSDwSR: An interesting experimentChen & Sonmez (2002) find that

TCC is significantly more efficient than RSDwSR

Basically, because existing tenants decide to participate in TTC more often than in RSDwSR

There is no significant difference in truthtelling between TTC and RSDwSR

Page 23: An Experimental Test of House Matching Algorithms

Our Experiment: Which is better? TTC or MIT-NH4

Strategy-proof

Individually rational Fair

Pareto efficient

TTC

MIT-NH4

Strategy-proof

Page 24: An Experimental Test of House Matching Algorithms

TTC vs. NH4: Experimental design Two treatments, 5 groups in each treatment,

12 agents per group (8 existing tenants and 4 newcomers)

Existing tenants first decide whether to participate or not

Then subjects report their preferences. One shot game

The priority order is randomly determined, allocation computed and subjects paid

Page 25: An Experimental Test of House Matching Algorithms

TTC vs. MIT-NH4: An (even more) interesting experimentWe find that

In the lab, NH4 is equally or more efficient than TTC

Basically, because existing tenants decide to participate in NH4 more often than in TTC

There is no significant difference in truthtelling between NH4 and TTC

Page 26: An Experimental Test of House Matching Algorithms

Our main result

Individually rational Fair

Pareto efficient

TTC

MIT-NH4

Strategy-proof

Page 27: An Experimental Test of House Matching Algorithms