voting geometry: a mathematical study of voting methods and their properties alan t. sherman dept....

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Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

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Page 1: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Voting Geometry:A Mathematical Study of Voting Methods and Their Properties

Alan T. ShermanDept. of CSEE, UMBC

March 27, 2006

Page 2: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Reference Work

• Saari, Donald G., Basic Geometry of Voting, Springer (1995). 300 pages.

– Distinguished Professor: Mathematics and Economics (UC Irvine)

– National Science Foundation support– Former Chief Editor, Bulletin of the American

Mathematical Society– 103 hits on Google Scholar

Page 3: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Main Results

• Application of geometry to study voting systems

• New insights, simplified analyses, greater clarity of understanding

• Borda Count (BC) has many attractive properties, but all methods have limitations

Page 4: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Question:

• Does plurality always reflect the desires of the voters?

Page 5: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Beer, Wine, Milk

Profile # Voters

M > W > B 6

B > W > M 5

W > B > M 4Total: 15

What beverage should be served?

Page 6: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Plurality

Profile #

M > W > B 6

B > W > M 5

W > B > M 4

B W M

5 4 6

Page 7: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Runoff

Profile #

M > W > B 6

B > W > M 5

W > B > M 4

B M

9 6

Page 8: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Pairwise Comparison

Profile #

M > W > B 6

B > W > M 5

W > B > M 4

W > B > M

10 : 5 9 : 6

>

9 : 6

Page 9: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Borda Count

Profile #

M > W > B 6

B > W > M 5

W > B > M 4

W B M

1 0 2

1 2 0

2 1 0

4 3 2

Page 10: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 1: Method Determines Outcome

Method Outcome

Plurality milk

Runoff beer

Pairwise wine

Borda Count wine

Page 11: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Outline

• Motivation• Why voting is hard to analyze• History• Modeling voting• Methods: pairwise, positional• Properties: Arrow’s Theorem• Other issues: manipulation, apportionment• Conclusion

Page 12: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Motivation

• Understand election results

• Understand properties of election methods

• Find effective methods for reasoning about election methods

• Identify desirable properties of election methods

• Help officials make informed decisions in choosing election methods

Page 13: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Why is Voting Difficult to Analyze?

• K candidates, N voters• K! possible rankings of candidates• Number of possible outcomes:

(k!)N - with ordering of votes cast

k! + N – 1 - without ordering of votes castN

(3!)15 = 615 = 470,184,984,576

Page 15: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Modeling Voting

Profiles

(candidate rankings by each voter)

Election Outcome

Election

Page 16: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

ProfilesFrequency counts of rankings by voters

P = (p1, p2, …, p6) (k = 3 candidates,

P = (6,5,4,0,0,0) N = 15 voters)

P = (6/15,5/15,4/15,0,0,0) normalized

M B

W

6 5

4

Page 17: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Election Mappings

f : Si(k!) → Si(k) (k = # candidates)

Si(k!) = normalized space of profiles;dimension k! – 1 (a simplex)

Si(k) = normalized space of outcomes;dimension k – 1 (a simplex)

f is linear

Page 18: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Voting Methods

• Pairwise methods– Agenda, Condorcet winner/loser

• Positional methods– Plurality, Borda Count (BC)

• Hybrid Rules– Runoff, Coomb’s runoff– Black’s procedure, Copeland method

Page 19: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Pairwise Methods:Outline

• Agenda

• Condorcet winner

• Arrow’s Theorem

Page 21: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 2: Two Agendas

Agenda B,K,N

K 5

B 10

N 10

B 5

Agenda K,N,B

N 5

K 10

B 10

K 5

B > K > N 5

K > N > B 5

N > B > K 5

Page 22: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Condorcet Winner/Loser

• Condorcet Winner – wins all pairwise majority vote elections

• Condorcet Loser – loses all pairwise majority vote elections

Page 23: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Question:

• Does the Condorcet winner always reflect the first choice of the voters?

Page 24: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Problems with Condorcet Winners

• Condorcet winner does not always exist• Confused voters (non-transitive preferences)• Missing intensity of comparisons

election

Page 25: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 3: Condorcet Winner

M B

W

1 10

110

30 29

B

W

1 10

110

10 1

B

W

0 0

00

20 28

M

Moriginal

Condorcet

reduced

41-40 20-28

Remove confused voters!

Page 26: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Arrow’s Theorem: Hypotheses

• Universal Domain (UD)Each voter may rank candidates any way

• Independence of Irrelevant Alternatives (IIA)Relative rank x-y depends only on ranks x-y

• Involvement (Invl)candidates x,y, profiles p1,p2 p1 x>y and p2 y>x

• Responsiveness (Resp)Outcomes cannot always agree with some single voter

Page 27: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Arrow’s Theorem

Theorem (1963). For 3 voters, there is no voting procedure with strict rankings that satisfies UD, IIA, Invl, and Resp.

Corollary (Arrow). The only voting procedure that always gives strict rankings of 3 candidates, and that satisfies UD, IIA, and Invl, is dictatorship.

Page 28: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Borda Count

• “Appears to be optimal”

• Unique method to represent true wishes of voters

• Minimizes number and kind of paradoxes

• Minimizes manipulation

Page 29: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Additional Issues

• Manipulation / Strategic voting

• Apportionment

Page 30: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Gibbard-Satterthwaite

Theorem (1973,1975). All non-dictatorial voting methods can be manipulated.

Page 31: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 4: Committees

Divide voters into two committees of 13 for straw polls.

Entire group votes.

Plurality voting, with runoffs.

Page 32: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Example 4: Committees I,II

Profile Frequency Committee Joint

I II I II

A > B > C 4 4 A 4,7 4,7 A 8

B > A > C 3 3 B 3 6,6 B 9,17

C > A > B 3 3 C 6,6 3 C 9,9

C > B > A 3 0

B > C > A 0 3

Page 33: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Desirable Properties

• Monotonicity

• Unbiased

• Resistance to manipulation

Page 34: Voting Geometry: A Mathematical Study of Voting Methods and Their Properties Alan T. Sherman Dept. of CSEE, UMBC March 27, 2006

Conclusions

• Geometry simplifies analysis and facilitates understanding.

• Problems with Condorcet explain many paradoxes.

• Borda Count is attractive.– most resistant to manipulation, minimizes paradoxes

• Runoff is usually better than plurality.• All methods have limitations, and there is no

simple way to select “best” method.