Abstract
This paper studies the role of risk attitudes in determining the optimality of winner-take-all contests. We compare the typical single-winner lottery contest with two alternatives, both spreading the rewards to more players: through holding multiple prize-giving lottery competitions or through guaranteeing a bottom prize for the losers. In the first comparison, we find that the multiple-competition contest is as effective as the winner-take-all contest when the contestants are risk neutral, but the former induces more effort than the latter when the contestants are both risk averse and prudent. In the second comparison, we find that the contest with a bottom prize is always dominated by the winner-take-all contest when the contestants are risk neutral, but the former could have an advantage over the latter when the contestants are both risk averse and prudent, and it is more likely so as the contestants become more prudent.
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Notes
A primary example is IAAF’s Diamond League series where world’s top athletes of each of the 32 covered disciplines compete for prizes in each of the “qualification” meetings with those who accumulate the highest points also qualifying for the “final” meeting. Tennis is another example in which a meta-organization controls the total number and the structure of competitions in a sport. The ATP decides about the list of tournaments, and created the ATP new tour structure in 2009 called ATP World Tour consisting of ATP world Tour Masters 1000, ATP World Tour 500, and ATP World Tour 250 tier tournaments.
Note that the multiple-competition contest is different from the multiple-battle contest that has been extensively studied in the literature (e.g., Barbieri & Serena, 2019; Fu & Lu, 2012; Fu et al., 2015; Klumpp & Polborn, 2006; Konrad & Kovenock, 2009). In the multiple-battle contest model, a player (either on behalf of himself/herself or as a member of a team) makes battle-specific effort for each battle in order to earn credits towards eventually winning a contest.
Though not the focus of their formal analysis, O’Keeffe et al. (1984, pp. 29–30) assert such a direct relation between the prize gap and the effort level: “If the prize spread is substantial …, workers may exert excessive effort…”; and “Insufficient effort is also a possibility…, if the bottom prize in a contest is relatively high”.
Another possible reason for the contest with a bottom prize not receiving enough attention is that it is mathematically equivalent to a single-prize contest in which every player’s wealth is increased by an amount equal to the bottom prize. Despite such equivalence, nevertheless, the comparative statics analysis in the contest with a bottom prize with respect to an increase in the size of the bottom prize while holding the prize budget constant is not simply the comparative statics analysis in the single-prize contest with respect to an increase in the initial wealth.
Share contests have received relatively little attention compared to the winner-take-all lottery contests, even though the contest success functions can be interpreted either as probabilities or as shares. This is probably due to the fact that the two alternative interpretations are equivalent under risk neutrality (Cason et al., 2020). Recent examples of research on share contests beyond the simple setting of additive linear payoffs/costs include Guigou et al. (2017) who study the effects of risk aversion in share contests (see also Long & Vousden, 1987), and Dickson et al. (2018) who examine the implications of non-constant rate of substitution between the payoff and the cost in share contests. To the best of our knowledge, nevertheless, the present paper is the first one recognizing the share contest as the limiting case of the lottery contest with multiple competitions that are based on the same set of one-shot player inputs.
Our paper provides a general and systematic treatment of the roles of risk aversion and prudence in the comparison between the winner-take-all contest and the multiple-prize contest, which generates clear-cut results in line with those of Moldovanu and Sela (2001) and Fang et al. (2020) that are obtained under convex bidding cost functions for the players. There could be other reasons in favor of multiple prizes that are different from ours (which is the insurance value). For example, Blavatskyy (2004) provides a justification for multiple prizes based on player heterogeneity (our model has identical players), and the entry possibility (our model has a fixed number of participants).
The existence and uniqueness of symmetric and asymmetric equilibria in contests with risk-averse or risk-loving players are also studied in Cornes and Hartley (2012), Jindapon and Whaley (2015), Jindapon and Yang (2017) and Skaperdas and Gan (1995), under various assumptions on the utility function and the contest success functions. In particular, Cornes and Hartley (2012) show, using a common logistic contest success function, that the symmetric equilibrium of symmetric contests is always unique. In the more general KST model, Treich (2010) shows that there exists a unique symmetric equilibrium under decreasing absolute risk aversion (DARA) when the prize is sufficiently “small”. Moreover, note that even if the equilibrium is not unique, the comparative statics results are useful since they permit to compare the lowest and highest equilibria (Milgrom & Roberts, 1994; Treich, 2010).
Risk aversion and prudence (or downside risk aversion) play an important role in the self-protection decision—a single-player, nonstrategic version of the contest model in which the decision maker exerts effort to increase the probability of no loss. See, for example, Briys and Schlesinger (1990), Chiu (2005), Crainich et al. (2016), Denuit et al. (2016), Dionne and Eeckhoudt (1985), Dionne and Li (2011), Ebert (2015), Eeckhoudt and Gollier (2005), Jullien et al. (1999), Lee (1998), Liu et al. (2009), Menegatti (2009), and Peter (2017, 2020). In particular, Denuit et al. (2016) explain that the composite change in the final wealth distribution caused by an increase in self-protection effort includes a component of downside risk increase in the sense of Menezes et al. (1980) that is disliked by downside risk averse decision makers.
In a two-period version of the rent-seeking contest of KST, Menegatti (2020) shows that making the rent risky reduces player effort under risk aversion alone (without prudence).
Although the assumption that the competitions of different rounds are statistically independent seems quite natural, it does not hold in many cases. Consider, for instance, the example of tennis competitions in the ATP World Tour, mentioned in Footnote 3. In this case, it sometimes happens that the winner of a tournament withdraws from the next tournament if the two tournaments are very close. This suggests that the idea of statistically independent competitions is plausible, but not always verified.
Although the assumption of equal prizes seems plausible in some instances, it is certainly not verified in general. Following comments in Footnotes 3 and 14, the ATP World Tour provides an example with different categories of tournaments, and thus where competitions offer different prizes.
In reality, of course, the number of competitions is constrained by the transaction costs associated with organizing competitions.
Fu et al. (2019) apply the nested lottery procedure of Clark and Riis (1996) to allocate a set of prizes. To do this, however, they assume that the contest success functions have a special form (e.g., the ratio form) so that they are still (unambiguously) well-defined when the number of players changes. In the present paper, on the other hand, the CSFs are of a more general form on which the nested lottery procedure is not well-defined.
Indeed, it is easy to see through a change in notation that the condition H(x,a) strictly decreasing in x is equivalent to Condition 1.
Ross more risk averse implies, but is not implied by, Arrow–Pratt more risk averse (Pratt, 1964; Ross, 1981). Extensions of the Ross notion of greater risk aversion to the general nth-degree are studied in Denuit and Eeckhoudt (2010), Jindapon and Neilson (2007), Li (2009), Liu and Meyer (2013), and Liu and Neilson (2019). We use “prudent” and “downside risk averse” interchangeably because both are characterized by \(u^{\prime\prime\prime} > 0\) in the expected utility framework. In addition, we also use “more prudent” and “more downside risk averse” interchangeably, both of which are defined according to Definition 1. We should point out that “more prudent” in the literature may have a different meaning from Definition 1 (Kimball, 1990), and there exist alternative notions of greater downside risk aversion (see the next footnote).
Following Modica and Scarsini (2005), Liu et al. (2018) use this Ross notion of greater downside risk aversion in a contest model. Alternatively, Sahm (2017) uses an Arrow–Pratt version of greater downside risk aversion. For discussions of alternative notions of greater downside risk aversion, see Crainich and Eeckhoudt (2008), Keenan and Snow (2016), Liu and Wong (2019) and Peter (2020), among others.
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Acknowledgements
We would like to thank an anonymous reviewer, Qiang Fu, Mario Menegatti, Andreas Richter, Kip Viscusi and Richard Watt for their helpful comments and suggestions on earlier versions of this paper. Nicolas Treich thanks SCOR at TSE-Partnership and ANR under Grant ANR-17-EURE-0010 for financial support.
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Appendices
Appendix 1: Condition 1 under the ratio-form contest success function and the CARA or CRRA utility function
Let \(p_{i} (x_{1} , \ldots ,x_{n} ) = \frac{{x_{i}^{r} }}{{\sum\nolimits_{k = 1}^{n} {x_{k}^{r} } }}\), we have
Therefore,
Note that the derivative of \(- \left[ {\tfrac{1}{n}u^{\prime}(w + b - x) + (1 - \tfrac{1}{n})u^{\prime}(w - x)} \right]\) in F(x) is non-positive when \(u^{\prime\prime}( \cdot ) \le 0\). As a result, a sufficient condition for Condition 1 to hold is
or equivalently (according to (13))
-
(i)
The Case of CARA: \(u(y) = - e^{ - \lambda y}\), \(\lambda \ge 0\), \(y > 0\)
In this case, \(\lambda\) is the (constant) absolute risk aversion measure, and (14) is equivalent to
$$\lambda x - 1 < 0.$$(15)That is, Condition 1 is satisfied as long as x is sufficiently small (given the value of \(\lambda\)).
-
(ii)
The Case of CRRA: \(u(y) = \frac{{y^{1 - \gamma } }}{1 - \gamma }\), \(\gamma \ge 0{\text{ and}}\;\gamma \ne 1\), \(y > 0\)
In this case, \(\gamma\) is the (constant) relative risk aversion measure, and (14) is equivalent to
$$- \frac{1}{x}\frac{1}{1 - \gamma }\left[ {(w + b - x)^{1 - \gamma } - (w - x)^{1 - \gamma } } \right] - \left[ {(w + b - x)^{ - \gamma } - (w - x)^{ - \gamma } } \right] < 0.$$(16)
Note that the LHS of (16) is zero when b = 0. So for (16) to hold when b > 0, it is sufficient that the derivative of the LHS of (16) with respect to b is negative, or
That is, Condition 1 is satisfied as long as x is sufficiently small (given the value of \(\gamma\)).
Appendix 2: Derivation of (4′)
The first order condition for player i’s problem to maximize expected utility \(\sum\nolimits_{k = 0}^{m} {\left[ {\left( {\begin{array}{*{20}c} m \\ k \\ \end{array} } \right)p_{i}^{m - k} (1 - p_{i} )^{k} u\left( {w + (m - k)\frac{b}{m} - x_{i} } \right)} \right]}\), where \(\left( {\begin{array}{*{20}c} m \\ k \\ \end{array} } \right) = \frac{m(m - 1) \cdots (m - k + 1)}{{k!}}\), by choosing \(x_{i}\) is
Imposing symmetry—\(x_{i} = x{\text{ for all }}i\)—on the first order condition, the symmetric interior Nash equilibrium satisfies
where \(p_{x} (x) \equiv \tfrac{{\partial p_{i} }}{{\partial x_{i} }}(x, \ldots ,x) \ge 0\). Note that
Therefore, we have (4′)
Appendix 3: Proof of Proposition 3′
The symmetric equilibrium effort is determined by (2) when m = 1 and by (4′) when \(m \ge 2\).
-
(i)
Players are risk neutral: \(u^{\prime\prime}( \cdot ) = 0\).
In this case, \(F(x) = p_{x} b - 1\), and
$$\begin{aligned} G_{m} (x) &= p_{x} \left\{ {\sum\limits_{k = 0}^{m - 1} {m\left( {\begin{array}{*{20}c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} \left( {w + (m - k)\frac{b}{m} - x} \right)}}\right.\\&\quad\left.{ - \sum\limits_{k = 0}^{m - 1} {m\left( {\begin{array}{*{20}c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} \left( {w + (m - 1 - k)\frac{b}{m} - x} \right)} } \right\} \hfill \\&\quad- \sum\limits_{k = 0}^{m} {\left( {\begin{array}{*{20}c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} } \hfill = p_{x} \left\{ {m\left( {w - x + \frac{b}{m} + \frac{m - 1}{n}\frac{b}{m}} \right)}\right.\\&\quad\left.{- m\left( {w - x + \frac{m - 1}{n}\frac{b}{m}} \right)} \right\} - \left( {\frac{1}{n} + 1 - \frac{1}{n}} \right)^{m} = p_{x} b - 1. \hfill \end{aligned}$$Therefore, m has no effect on the equilibrium effort.
-
(ii)
Players are both risk averse and prudent: \(u^{\prime\prime}( \cdot ) < 0\) and \(u^{\prime\prime\prime}( \cdot ) > 0\).
In this case,
$$\begin{aligned} & G_{m} (x) - F(x) = p_{x} (m + 1)\\& \left\{ \begin{gathered} \left[ {\frac{m}{m + 1}\sum\limits_{k = 0}^{m - 1} {\left( {\begin{array}{*{20}c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} u\left( {w + (m - k)\frac{b}{m} - x} \right)} + \frac{1}{m + 1}u(w - x)} \right] \hfill \\ - \left[ {\frac{m}{m + 1}\sum\limits_{k = 0}^{m - 1} {\left( {\begin{array}{*{20}c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} u\left( {w + (m - 1 - k)\frac{b}{m} - x} \right) + \frac{1}{m + 1}u(w + b - x)} } \right] \hfill \\ \end{gathered} \right\} \hfill \\&+ \left[ {\tfrac{1}{n}u^{\prime}(w + b - x) + (1 - \tfrac{1}{n})u^{\prime}(w - x)} \right] - \left[ {\sum\limits_{k = 0}^{m} {\left( {\begin{array}{*{20}c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} } \right]. \hfill \end{aligned}$$The two bracketed items in the curly parentheses are the expected utility of two wealth distributions respectively, and the second distribution is a Rothschild-Stiglitz risk increase over the first, both having a mean of \(w - x + \frac{b}{m + 1}\left( {1 + \frac{m - 1}{n}} \right)\). So their difference is positive since \(u^{\prime\prime}( \cdot ) < 0\). In addition, the last two bracketed items above are the expected utility—with \(u^{\prime}( \cdot )\) being the utility function—of two wealth distributions respectively, and the first distribution is a Rothschild-Stiglitz risk increase over the second, both having a mean of \(w - x + \frac{b}{n}.\) So their difference is also positive since \(u^{\prime\prime\prime}( \cdot ) > 0\). Therefore, \(G_{m} (x) - F(x) > 0\) for all x. This, together with Condition 1, suggests that the equilibrium effort level increases from m = 1 to \(m \ge 2\). □
Appendix 4: Proof of Proposition 5
-
(i)
This is true because for risk-neutral players, the symmetric equilibrium effort level is determined by \(p_{x} b - 1 = 0\) under both the shared-prize contest and the m-round multiple-competition contest.
-
(ii)
Suppose \(u^{\prime\prime}( \cdot ) < 0\) and \(u^{\prime\prime\prime}( \cdot ) > 0\). The symmetric equilibrium effort level is determined by \(p_{x} b - 1 = 0\) under the shared-prize contest, and it is determined by (4′) under the m-round multiple-competition contest. To prove that the solution to \(p_{x} b - 1 = 0\) is larger than the solution to (4′), it is sufficient to show that at the effort level x where \(p_{x} b - 1 = 0\), \(G_{m} (x) < 0\). Indeed, substituting \(p_{x} = 1/b\) into the expression of \(G_{m} (x)\) in (4′), we have
$$\begin{aligned} G_{m} (x) = &\frac{m}{b}\biggl\{ \sum\limits_{k = 0}^{m - 1} {\left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} u\left( {w + (m - k)\frac{b}{m} - x} \right)} \\&- \sum\limits_{k = 0}^{m - 1} {\left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} u\left( {w + (m - 1 - k)\frac{b}{m} - x} \right)} \biggr\}\\& - \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ &< \sum\limits_{k = 0}^{m - 1} \left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} \biggl[ \frac{1}{2}u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)\\ &+ \frac{1}{2}u^{\prime}\left( {w + (m - 1 - k)\frac{b}{m} - x} \right) \biggr] - \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ & \le \sum\limits_{k = 0}^{m - 1} \left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k} \biggl[ \frac{1}{n}u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right) \\ &+ \left( {1 - \frac{1}{n}} \right)u^{\prime}\left( {w + (m - 1 - k)\frac{b}{m} - x} \right) \biggr] - \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ =& \sum\limits_{k = 0}^{m - 1} \left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right) \\ &+ \sum\limits_{k = 0}^{m - 1} {\left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - 1 - k} \left( {1 - \frac{1}{n}} \right)^{k + 1} u^{\prime}\left( {w + (m - 1 - k)\frac{b}{m} - x} \right)} \\ & - \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ =& \sum\limits_{k = 0}^{m - 1} \left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right) \\ &+ \sum\limits_{k = 1}^{m} {\left( {\begin{array}{c} {m - 1} \\ {k - 1} \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ & - \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)_{{}}^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\=& \left( \frac{1}{n} \right)_{{}}^{m} u^{\prime}\left( {w + b - x} \right) + \sum\limits_{k = 1}^{m - 1} {\left( {\begin{array}{c} {m - 1} \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} \\ &\times\sum\limits_{k = 1}^{m - 1} {\left( {\begin{array}{c} {m - 1} \\ {k - 1} \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} + \left( {1 - \frac{1}{n}} \right)^{m} u^{\prime}\left( {w - x} \right) \\ &- \sum\limits_{k = 0}^{m} {\left( {\begin{array}{c} m \\ k \\ \end{array} } \right)\left( \frac{1}{n} \right)^{m - k} \left( {1 - \frac{1}{n}} \right)^{k} u^{\prime}\left( {w + (m - k)\frac{b}{m} - x} \right)} = 0, \end{aligned}$$where the first inequality is due to Lemma 2, the second inequality due to \(n \ge 2\) and \(u^{\prime\prime}( \cdot ) < 0\), and the last equality due to Pascal’s rule, namely \(\left( {\begin{array}{*{20}c} {m - 1} \\ k \\ \end{array} } \right) + \left( {\begin{array}{*{20}c} {m - 1} \\ {k - 1} \\ \end{array} } \right) = \left( {\begin{array}{*{20}c} m \\ k \\ \end{array} } \right)\).
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Liu, L., Treich, N. Optimality of winner-take-all contests: the role of attitudes toward risk. J Risk Uncertain 63, 1–25 (2021). https://doi.org/10.1007/s11166-021-09355-8
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DOI: https://doi.org/10.1007/s11166-021-09355-8