THE THEORY OF MECHANISM DESIGN: APPLICATIONS TO VOTING AND AUCTIONS - PowerPoint PPT Presentation

1 / 23
About This Presentation
Title:

THE THEORY OF MECHANISM DESIGN: APPLICATIONS TO VOTING AND AUCTIONS

Description:

Voters realize they are playing a Game. ... Suppose that she believes that (excluding herself), n1 voters will vote 10 and n0 will vote 01. ... – PowerPoint PPT presentation

Number of Views:59
Avg rating:3.0/5.0
Slides: 24
Provided by: downloads1
Category:

less

Transcript and Presenter's Notes

Title: THE THEORY OF MECHANISM DESIGN: APPLICATIONS TO VOTING AND AUCTIONS


1
THE THEORY OF MECHANISM DESIGN APPLICATIONS TO
VOTING AND AUCTIONS
  • Arunava Sen
  • Indian Statistical Institute

Shaastra 2006 IIT ChennaiSeptember 29, 2006
2
A SimpleVoting Model
  • N voters
  • Two alternatives, 1 (Change) and 0 (Status
    Quo)
  • Each voter has an opinion either prefers 1 to
    0 (written 10) or 0 to 1 (written 01). Each
    voters opinion known only to herself.
  • Each voters votes, i.e. announces either 10 or
    01.
  • Voting Rule count number of voters who have
    voted 1 (n1) and 0 (n0). If n1 gt n0, 1 is
    elected otherwise 0 is elected.

3
A Simple Voting Model (contd)
  • Question what should each voter announce i.e.
    tell the truth or lie?
  • Note that the outcome depends not only on what a
    voter announces but on what all voters announce.
  • Voters realize they are playing a Game.
  • In order to decide how to vote, each voter must
    have beliefs over how she thinks other voters
    will vote.

4
A Simple Voting Model (contd)
  • Claim No voter can do better than by announcing
    her true opinion (henceforth, the truth)
    irrespective of how she believes other voters
    will vote.
  • Suppose that she believes that (excluding
    herself), n1 voters will vote 10 and n0 will vote
    01.
  • Suppose n1-n0 gt 1. Then she does not believe
    that her announcement can affect the outcome. So
    she cannot do better by not telling the truth.

5
A Simple Voting Model (contd)
  • Suppose her true opinion is 10 and n1-n0 1,0 or
    1. Then telling the truth yields outcomes 1,1
    and 0 in the three cases respectively while lying
    (i.e. announcing 01) will yield outcomes 0,0 and
    0 respectively. Clearly lying does not help in
    any case.
  • If her true opinion is 01, then truth-telling
    yields outome 0 in every case while lying will
    give 1,1 and 0 respectively. Lying doesnt help.

6
A Simple Voting Model (contd)
  • Are there other voting rules which have the same
    property regarding the incentives to tell the
    truth?
  • Yes.
  • For Example (and this is almost the complete
    class) Pick an integer (quota) q ? N. Elect 1
    if n1 ? q otherwise elect 0.
  • An example of a rule which does not satisfy it
    pick integers r and s such that 0 ? r lt s ? N and
    elect 1 iff n1 lies between r and s.

7
Voting 3 Candidates, 2 Voters
  • Set of candidates A a,b,c
  • Two voters 1 and 2
  • Each voters opinon is a ranking of the
    candidates, i.e. one of abc, acb, bac, bca, cab,
    cba (here abc means a better than b better than
    c). Known only to the voter.

8
Voting 3 Candidates, 2 Voters (contd)
  • Each voter votes by announcing her opinion, i.e.
    one of abc, acb, bac, bca, cab or cab.
  • Voting rule Each voters top choice gets 2
    points, middle 1 point and bottom 0 point. The
    points for candidate is summed across voters
    candidate with the highest no of points is
    elected. Ties broken in the order a gt b gt c.
  • E.g. (abc, bca) ? b, (abc, cba) ? c etc.
  • The voting rule can be represented as a matrix
    whose entries are a, b or c.

9
Voting 3 Candidates, 2 Voters (contd)
abc acb bac bca cab cba
abc a a a b a a
acb a a a a a c
bac a a b b a b
bca b a b b c b
cab a a a c c c
cba a c b b c c
10
Voting 3 Candidates 2 Voters (contd)
  • Suppose voter 1s opinion is abc and she believes
    2 will announce bca. Truth-telling will yield b
    while lying by announcing acb will yield a. Note
    that a is better than b according to her true
    opinion.This voting rule may not induce
    truth-telling.
  • Is there a voting rule which will induce
    truth-telling if there are 3 or more candidates?
  • Yes

11
Voting Dictatorship
abc acb bac bca cab cba
abc a a a a a a
acb a a a a a a
bac b b b b b b
bca b b b b b b
cab c c c c c c
cba c c c c c c
12
The Gibbard-Satterthwaite Theorem Informal
Statement
  • Any other voting rules which induce
    truth-telling?
  • NO!!
  • The Gibbard-Satterthwaite Theorem (1973) The
    only voting rule which has a range of at least
    three which induces truth-telling is the
    dictatorial one.

13
A Formal Model
  • A a,b,c, is a set of candidates. We assume
    that A gt 2.
  • N 1,,N set of voters.
  • Each voter i has an opinion over the candidates
    which can be represented by an ordering Pi over
    the elements of A. Thus aPib signifies that i
    prefers a to b when her opinion is Pi.
  • Let IP denote the set of all orderings over A.
  • A profile P ? (P1,,PN) ? IPN.

14
A Formal Model (contd)
  • A voting rule f is a map f IPN ? A.
  • For every profile P, f elects f (P) ? A.
  • The voting rule f induces truth-telling if for
    all voters i, all profiles P and orderings PI,
    we have either f (P) f (P1,..,Pi-1, Pi,
    Pi1,,PN) or f (P) Pi f (P1,..,Pi-1, Pi,
    Pi1,,PN).
  • Suppose Pi represents is true opinion. If f
    induces truth-telling then i cannot do better
    than announcing Pi no matter what she believes
    other voters will announce.
  • The voting rule f is dictatorial if there exists
    a voter i such that for all profiles P, f (P)
    max Pi.

15
The Gibbard-Satterthwaite Theorem
  • Theorem (Gibbard- Satterthwaite)
  • Let f be a voting rule with Range f gt 2. Then
    induces truth-telling if and only if it is
    dictatorial.

16
Single Object Auctions
  • Single object one seller and N potential buyers
    called bidders.
  • Each bidder i has a valuation vi for the object.
  • Bidder is valuation is known only to himself.
    Assume that vis are i.i.d random variables with
    distribution function F and associated density
    function f.
  • If bidder i with valuation vi gets the object his
    payoff is vi pi where pi is his payment
    otherwise his payoff is zero.

17
Single Object Auctions (contd)
  • Each bidder i makes a bid bi, bi ? 0.
  • An auction is an N1 tuple of functions (d,
    p1,,pN) where d IRN ? 1,, N and pi IRN ?
    IR. Here d (b1,,bN) specifies who gets the
    object and pi (b1,,bN) the amount paid by the i
    th bidder as a function of the bids. We will let
    di (b1,,bN) 1 if d (b1,,bN) i and 0
    otherwise.

18
Single Object Auctions (contd)
  • The auction (d, p1,,pN) induces truth-telling
    (is incentive compatible) if vi. di (b1,..vi,bN)
    - pi (b1,..vi,bN) ? vi. di (b1,..bi,bN) - pi
    (b1,..bi,bN) for all vi, bi, b1,,bN and i.
  • In other words, bidder i cannot do better than
    revealing her true valuation irrespective of her
    beliefs about the bids of other bidders.

19
Single Object Auctions (contd)
  • The auction (d, p1,. .,pN) is individually
    rational if vi. di (v1,..vi,vN) - pi
    (v1,..vi,vN) ? 0 for all v1,vN and i.
  • If the auction is individually rational, then
    bidders will participate voluntarily. In
    particular, bidders cannot be charged if they do
    not receive the object.

20
Single Object Auctions (contd)
  • The sellers expected revenue from the auction
    (d, p1,.pN) is given by
  • ?v1..?vN ?i pi (v1..vN) f (v1).f (vN).
    dv1dvN.
  • The problem is to find the auction (d, p1,.pN)
    which maximizes the sellers expected revenue
    subject to incentive compatibility and individual
    rationality.

21
The Optimal Single Object Auction
  • Let c (vi) vi (1 F (vi))/ f(vi)
  • Assume that c (.) is a monotone increasing
    function. Satisfied by most common distributions
    (e.g. uniform).
  • Myerson (1981) shows that there exists an optimal
    auction of the following kind give the object
    to the highest bidder i provided that c (bi) ? 0
    and make him pay max c-1 (0), bj where b is the
    maximum of bids of all bidders other than i. If
    c(bi) lt 0, object stays with seller.
  • Myersons result is actually more general.

22
Optimal Auctions (contd)
  • This is a second price auction with a reserve
    price c-1 (0).
  • In a second price auction, the highest bidder
    gets the object but pays the second highest bid.
    In this case the seller also makes a bid even
    though he has no value for the object. This
    increases his expected revenue.
  • It is is easy to show in these auctions that
    bidders are induced to reveal their valuations
    truthfully.

23
Open Questions
  • Combinatorial Auctions Several objects to be
    sold. Bidders have valuations for all subsets of
    objects (bundles). Examples spectrum auctions,
    airport privatization?
  • What is the revenue optimal auction? Efficiency?
    VCG mechanisms. Important complexity
    considerations. Dynamic auctions.
  • In voting, characterization of
    incentive-compatible voting rules with special
    domains, randomized voting rules etc.
Write a Comment
User Comments (0)
About PowerShow.com