A Note on Multi-winner Contest Mechanisms

Similar documents
Multiple Equilibria in Tullock Contests

Linking Individual and Collective Contests through Noise Level and Sharing Rules

A contest success function with a tractable noise parameter

Multi-Player Contests with Asymmetric Information Karl Wärneryd

A contest success function with a tractable noise parameter

Academic Editor: Ulrich Berger Received: 12 August 2016 ; Accepted: 5 September 2016 ; Published: 9 September 2016

Best-shot Versus Weakest-link in Political Lobbying: An Application of Group All-pay Auction *

Volume 35, Issue 4. Group contests and technologies. Dongryul Lee Department of Economics, Sungshin University

Journal of Economic Behavior & Organization

Asymmetric Rent-seeking Contests with Multiple Agents of Two Types

Incentives versus Competitive Balance

The Strategic Equivalence of Rent-Seeking, Innovation, and Patent-Race Games

On Overdissipation of Rents in Contests with Endogenous Intrinsic Motivation. Volker Schlepütz

Information Sharing in Private Value Lottery Contest

Contests with Bilateral Delegation: Unobservable Contracts

On the Existence of a Bayesian Nash Equilibrium in Tullock Contests with Incomplete Information y

Existence of Equilibrium in Tullock Contests with Incomplete Information

public-good prizes Katsuya Kobayashi December 28, 2017 Abstract

Tullock Contests with Asymmetric Information

THE MAX-MIN GROUP CONTEST: WEAKEST-LINK (GROUP) ALL-PAY AUCTION

Information Advantage in Tullock Contests

SIRE DISCUSSION PAPER

Auctions with Rent Seeking

DISCUSSION PAPER SERIES

Individual Responsibility in Team Contests

Universidad Carlos III de Madrid Calle Madrid, 126

Players with Fixed Resources in Elimination Tournaments Alexander Matros Department of Economics University of Pittsburgh.

Ability Matters, and Heterogeneity Can Be Good: The Effect of Heterogeneity on the Performance of Tournament Participants

Mixed equilibria in Tullock contests

Indefinitely Repeated Contests: An Experimental Study

Relative Di erence Contest Success Function

Microeconomics II Lecture 4: Incomplete Information Karl Wärneryd Stockholm School of Economics November 2016

Game theory lecture 4. September 24, 2012

Lottery versus All-Pay Auction Contests

Splitting Tournaments

Welfare Maximizing Contest Success Functions when the Planner Cannot Commit

Advanced Microeconomics II

A nested contest: Tullock meets the All-Pay Auction*

Majoritarian Blotto Contests with Asymmetric Battlefields: An Experiment on Apex Games

Working Paper Series. Asymmetric All-Pay Contests with Heterogeneous Prizes. Jun Xiao. June Research Paper Number 1151

The Lottery Contest is a Best-Response Potential Game

SIGNALING IN CONTESTS. Tomer Ifergane and Aner Sela. Discussion Paper No November 2017

All-Pay Contests. Ron Siegel Graduate School of Business Stanford University. May Abstract

The incidence of overdissipation in rent-seeking contests

Multi prizes for multi tasks: externalities and the optimal design of tournaments

Optimal Favoritism in All-Pay Auctions and Lottery Contests

A Simple Model of Competition Between Teams

Should all competitors cooperate together? A coopetition contest model.

Working Paper Intention-based fairness preferences in two-player contests

A simple microfoundation for the utilization of fragmentation indexes to measure the performance of a team

Asymmetric All-Pay Contests with Heterogeneous Prizes

University of Toronto Department of Economics. Carrots and Sticks: Prizes and Punishments in Contests

Common-Value All-Pay Auctions with Asymmetric Information

Conjectural Variations in Aggregative Games: An Evolutionary Perspective

Tullock Contests with Asymmetric Information y

Discussion Papers Department of Economics University of Copenhagen

Rent-seeking with Non-Identical Sharing Rules: An Equilibrium Rescued

Escalation in dynamic conflict: On beliefs and selection

econstor Make Your Publications Visible.

Optimal sequential contests

Psychology and Economics (Lecture 3)

General idea. Firms can use competition between agents for. We mainly focus on incentives. 1 incentive and. 2 selection purposes 3 / 101

Winner-Take-All Crowdsourcing Contests with Stochastic Production

Game Theory and Algorithms Lecture 2: Nash Equilibria and Examples

Ability Grouping in All-Pay Contests

Columbia University. Department of Economics Discussion Paper Series. Caps on Political Lobbying: Reply. Yeon-Koo Che Ian Gale

A Simple Model of Competition Between Teams

Sharing contests with general preferences

Contest Functions: Theoretical Foundations and Issues in Estimation

Sequential Majoritarian Blotto Games

Contests between groups of unknown size

Robert Wilson (1977), A Bidding Model of Perfect Competition, Review of Economic

Second Welfare Theorem

FOUNDATIONS FOR CONTEST SUCCESS FUNCTIONS

Contest Functions: Theoretical Foundations and Issues in Estimation

Unique Equilibrium in Contests with Incomplete Information

Turning up the heat: The demoralizing effect of competition in contests

Second Price Auctions with Differentiated Participation Costs

Group Size, Collective Action and Complementarities in Efforts

EconS 501 Final Exam - December 10th, 2018

Algorithmic Game Theory Introduction to Mechanism Design

Hybrid All-Pay and Winner-Pay Contests

Inducing stability in hedonic games

Game Theory: Spring 2017

All-pay auctions with interdependent valuations: The highly competitive case 1

Crowdsourcing contests

Contests between groups of unknown size

DEPARTMENT OF ECONOMICS YALE UNIVERSITY P.O. Box New Haven, CT

Design Patent Damages under Sequential Innovation

Survey of Voting Procedures and Paradoxes

Information Disclosure in Markets: Auctions, Contests and Matching Markets

Contests with Endogenous and Stochastic Entry

A Micro Foundation of Generalized Multi-Prize Lottery Contests: A Noisy Ranking Perspective

The Impact of Organizer Market Structure on Participant Entry Behavior in a Multi-Tournament Environment

Vickrey-Clarke-Groves Mechanisms

Module 8: Multi-Agent Models of Moral Hazard

THE FUTURE OF FORECASTING AT METROPOLITAN COUNCIL. CTS Research Conference May 23, 2012

arxiv: v1 [cs.gt] 16 Feb 2012

Uncertainty. Michael Peters December 27, 2013

The Value of Information in Matching Tournaments

Transcription:

A Note on Multi-winner Contest Mechanisms Subhasish M. Chowdhury and Sang-Hyun Kim February 11, 2014 Abstract In this note we consider a realistic multi-winner nested elimination contest in which losers are sequentially eliminated to attain the set of winners. This is a variant of a widely used mechanism introduced by Clark and Riis (1996) that allows one to select the winners sequentially. We show that the nested elimination mechanism becomes equivalent to another popular mechanism suggested by Berry (1993) where the winners are chosen simultaneously.. JEL Classifications: C72; D72 Keywords: Contest; Multiple Winner; Selection mechanism We appreciate the useful comments of Kyung Hwan Baik, Dana Sisak and the seminar participants at the University of East Anglia. Any remaining errors are our own. Corresponding author. School of Economics, Centre for Behavioural and Experimental Social Science, and the ESRC Centre for Competition Policy, University of East Anglia, Earlham Road, Norwich NR4 7TJ, UK. Phone: +44 160-359-2099. E-mail: s.modak-chowdhury@uea.ac.uk School of Economics, and the ESRC Centre for Competition Policy, University of East Anglia, Earlham Road, Norwich NR4 7TJ, UK. Phone: +44 160-359-3422. E-mail: sang-hyun.kim@uea.ac.uk 1

1 Introduction In many contests, in which players expend costly resources in order to win a prize, there are multiple winners. Examples include multiple medals in sports, early bird prizes, set of winners in rent-seking, set of recipients of research grants - to name a few. In the literature these contests are interchangably called multi-winner contests (Berry, 1993) or multi-prize contests (Sisak, 2009). We define multi-winner contests as contests in which there are more than one prize, but one player may win at most one of them. Most of the examples mentioned above is covered by this definition. In this note we consider a particular multi-winner contest mechanism, in which losers are sequentially eliminated to reach the final set of winners, that is widely applied in the field. We show that it is a variant of a highly cited mechanisms introduced by Clark and Riis (1996); and is equivalent to another famous mechanism introduced by Berry (1993). Berry (1993) was the first to analyze multi-winner contests using the framework of rentseeking (Tullock, 1980). He considers a contest among N players, and k(< N) prizes. He assumes that the probability of a player to win a prize is the sum of efforts expended by any combination of a k-player group that includes the specified player, divided by any combination of a k-player group. Hence, the probability that player i wins a prize is: Pi B (x) = (k 1) X i + (N 1)x i (N 1) (X i + x i ) where x is the vector of the efforts, x i is the effort of player i and X i is the total effort of all other players. Clark and Riis (1996) show that this winner selection mechanism inadvertently allows one prize to be allocated according to effort outlays, while the others are allocated independent of the effort outlays. This, in turn, results in free riding among players. They further introduce a nested mechanism in winner selection according to which, players expend effort, then one player is selected as winner using a Tullock (1980) contest success function. Then that player and his efforts are taken out of the calculation and another Tullock contest is run among the remaining (N 1) players using their already expended effort, and another winner is taken out. This procedure is repeated for k times to select the k winners. Here, the probability 2

that player i wins a prize becomes: [ k 1 j ] Pi CR (x) = p 1 i + (1 p s i )p j+1 j=1 where p s i is the probability of player i to win the prize at period s. The issue of allocation of prizes being independent of the effort outlays does not arise under this mechanism. Both of the mechanisms are used and cited by researchers investigating issues in multiwinner contests (see Sisak (2009) for a survey). However, as Clark and Riis (1996) mention, when one allows the imperfectly discriminating rent-seeking contest to have several winners, there is no unique method for selecting those winners". There are other mechanisms that are employed in the field in addition to the two mechanisms introduced above. One of the popular mechanisms employed in the field is very similar to the one introduced in the Clark and Riis (1996) study. However, instead of selecting-in winners in each nested period, the mechanism selects-out losers. This is common in elimination contests in which the losers are gradually selected out. s=1 i This includes elimination of losers in sit-and-draw contests (in which contestants draw pictures and the examiners decide upon the winners by eliminating the not-so-good drawings), elimination of job candidates to reach the final set (in which job candidates CVs are used to eliminate the candidates who do not have a chance), promotional tournaments (where conestants are gradually taken out) etc. Here we consider a mechanism similar to Clark and Riis (1996) to eliminate (N k) possible losers in (N k) elimination periods and show that it turns out to be equivalent to the mechanism suggested by Berry (1993). We then discuss the implications and possible extensions regarding those mechanisms. 2 Model Consider a contest among N players, and k(< N) prizes. The players exert effort only once, but the winner selection (or loser elimination) process is of multi periods through which N k among the N players are eliminated. In each period, one player is eliminated, and when k players are left, the identical prizes (with individual valuation V ) are granted to the 3

survivors. A lottery (Tullock, 1980) type contest success function is employed to eliminate losers in every period. To define the probability of winning a prize, first let I t be the set of survivors at period t. Also denote the effort level of jth player in I t by x t j. 1 Since one and only one player is dropped out in each period, the number of elements in set I t is and the aggregate effort at period t is I t = N t + 1, X t (I t ) = N t+1 Then, conditional on player i has survived the previous periods, the probability that he is eliminated in period t is j=1 x t j q t i(i t ) = X t x i X t x t 1 + X t x t 2 + + X t x t N t+1 = Xt x i (N t)x t As one can easily notice, this probability can be described as a Tullock-type contest failure function. The denominator is the sum of all possible combinations of N t players efforts, and the numerator is the aggregate effort less player i s. Next, we define the sequence of losers s l as s l = ( ) n 1 l, n 2 l,, n N k l where n t l is the player eliminated in period t according to the schedule of s l. Since s l has the same information that sequence {I t } N k t=1 has, we can define the probability of n t l being eliminated in period t as p t (s l ) = q t n t l(i t ) provided that s l and I t are consistent; i.e., none of { n 1 l, n2 l,, } nt 1 l is in It, but n t l I t. Then, the probability that player i wins a prize is defined as follows: P i (x) = [ N k ] p t (s l ) s l S i 1 Note that the effort is expended only once at the start of the contest. Due to the elimination of players in each period, denoting the effort for each period (x t j ) separately, however, allows ease of notation. 4 t=1

where x is the vector of the efforts, and S i is the set of all sequences (of length N k) that do not have i in its slots. Since the valuations are symmetric, we naturally focus on the symmetric case. Let us assume that player i exerts x i and all the others x i. Then, for any s l S i, and N k t=1 p t (s l ) = = p t (s l ) = Xt x n t l (N t)x t = (N t 1)x i + x i (N t) [(N t)x i + x i ], (N 2)x i + x i (N 3)x i + x i (N 1) [(N 1)x i + x i ] (N 2) [(N 2)x i + x i ] (k 1) x i + x i k [kx i + x i ] (k 1) x i + x i (N 1)(N 2) k [(N 1)x i + x i ] Noting that the number of elements in S i is S i = (N 1)! (k 1)! which is the number of cases to choose N k losers among N 1 players (player i is already chosen as a winner), we can write the probability of player i winning a prize as P i (x) = (N 1)! (k 1)! (k 1) x i + x i (N 1)(N 2) k [(N 1)x i + x i ] = (k 1) x i + x i (N 1)x i + x i This contest success function is identical with the one suggested by Berry (1993). 2 Hence, the equilibrium effort and the corresponding comparative statics are also the same as the ones in Berry (1993). 3 Discussion We consider a multi-winner nested elimination contest in which losers are sequentially eliminated to attain the set of winners. This mechanism incorporates an array of real life contests 2 When player i exerts x i and all the others x i, the probability of winning a prize in Berry s mechanism is Pi B(x) = [(k 1) X i + (N 1)x i ] / [(N 1) (X i + x i )] = [(k 1) x i + x i ] / [(N 1)x i + x i ] where X i is the total effort of all the other players. 5

and is similar to the one by Clark and Riis (1996), who consider sequential acceptance of winners. We show that theoretically this mechanism is equivalent to the simultaneous selection mechnism of Berry (1993). Since the theoretical results predict different rent-dissipation among winner selection mechanisms, the equivalence result allows contest designers to implementation the appropriate mechanism in accordance to their objectives. It may be possible in the future for one to introduce other popularly employed mechanisms and compare them with the existing ones. It is also possible to introduce risk aversion, player asymmetry, and prize asymmetry within this structure. Finally, the existing results provide clear ranking of rent-dissipation among multiwinner mechanisms, but it would be interesting to investigate whether the theoretical benchmark results still hold behaviorally. Very little experimental research had been caried out in the area of multi-winner contests (see Dechenaux et al. (2012) for a comprehensive survey), and one obvious first attempt can be to test and compare these three mechanisms in the laboratory. References [1] Berry, S. K. (1993). Rent-seeking with multiple winners, Public Choice, 77, 437-443. [2] Clark, D. & Riis, C. (1996). A multi-winner nested rent-seeking contest, Public Choice, 87, 177-184. [3] Dechenaux, E., Kovenock, D., and Sheremeta. R. M. (2012). A survey of experimental research on contests, all-pay auctions, and tournaments. Chapman University Working Paper. [4] Sisak, D. (2009). Multiple-prize contests: The Optimal allocation of Prizes. Journal of Economic Surveys, 23, 82 114. [5] Tullock, G. (1980). Effi cient Rent Seeking. In James M. Buchanan, Robert D. Tollison, Gordon Tullock, (Eds.), Toward a theory of the rent-seeking society. College Station, TX: Texas A&M University Press, pp. 97-112. 6