Abstract
Conventional theories of competition classify contests as being either “productive”, when the competitive efforts generate a surplus for society, or “unproductive”, when competition generates no social surplus and merely distributes already existing resources. These two discrete categories of competition create a division of real-world situations into analytical categories that fails to recognize the entire spectrum of competitive activities. Taking the existing models of productive and unproductive competition as benchmark idealizations, this paper revisits the relationship between the privately and socially optimal levels of competition in the full range of intermediate cases, as well as in the extremum cases of destructive and super-productive competition.
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Notes
Gordon Tullock (1967) laid the foundations for the study of “unproductive competition”, which Krueger (1974) later termed “rent seeking”. Bhagwati (1982) generalized the contributions of Tullock and Krueger, formulating a general theory of “directly-unproductive profit seeking”. The common characteristic of these situations (and innumerably many others) is that the rents sought by the contestants are fixed—their competitive efforts do not enlarge the prize at stake. This desire to bridge the boundaries of productive and unproductive competition serves as a main motivation for this paper. On competition, socially productive rivalry and regulation, see also Demsetz (1973, 1976) and Crain and Ekelund (1976).
Patent races are indeed traditionally regarded as inefficient, mainly because the winner-take-all nature of the competition leads to excessive and wasteful research expenditures (e.g., Hirshleifer 1971; Hartwick 1991). Many contributions have sought policy solutions to mitigate this problem (e.g., Ménière and Parlane 2008; Gilbert and Katz 2011).
Throughout the paper, depending upon the category of competition under consideration, we use the term activity in its lay meaning, encompassing both productive and unproductive undertakings. Bhagwati (1982) focused exclusively on directly unproductive, profit-seeking (DUP) activities.
It is worth noting that T and V are stationary flows: there is no dynamics in the contest apart from that generated by the innovation (Denicolo 1999).
In Denicolo (1999), T is assumed to be strictly positive, although the author acknowledged the possibility of non-pathological examples with a null or negative T. Our general taxonomy includes also these latter cases.
In the simplest case with no externalities, T is the sum of producer surplus and consumer surplus. When externalities arise, T reflects also the positive or negative effects generated on society. See, among others, Congleton (1989), Paul and Wilhite (1994), Chung (1996) and Lee and Kang (1998) for examples of rent seeking with externalities.
Paul and Wilhite (1994) examined the “negative externality that results from market participants use of coercion and violence in attempts to control trade in the illegal good.”. They show that the social cost of rent seeking exceeds the value of resources dissipated in rent-seeking contest.
Advertising is a dimension of non-pricing competition through which rent seeking may occur. There is a long standing debate whether advertising is informative to consumers or wasteful, in order to measure correctly the social loss produced by rent seeking (Cowling and Mueller 1978; Littlechild 1981). See also Dixit and Norman (1978) and related work to this debate. For the purpose of our analysis, the inclusion of this example under this category is merely illustrative and has no bearing on this debate.
Lin (1997) argued that if the winner of the patent can capture all the social value of the innovation, the R&D race in general leads to socially wasteful R&D effort due to its winner-take-all feature. In this case, licensing appears to be socially desirable if it can eliminate excessive R&D. If instead the social value of the patent is not equal to V, it is not clear how licensing affects welfare: a slower innovation process is not necessarily welfare improving. In this case, the welfare effect of licensing will ultimately depend on the difference between the social and private value of the discovery.
Patent-race scholars have occasionally made the point that even when competition is intrinsically good, competition may be excessive. See for example Dasgupta and Stiglitz (1980).
For an extensive review of the experimental literature on contests, see Dechenaux et al. (2015).
The analysis presented here can be extended to consider an endogenous prize increasing in the level of parties’ efforts. The qualitative nature of our conclusions does not change.
Contests can be generally classified as either perfectly or imperfectly discriminating. Among others, see Hillman and Riley (1989) for a comparison of these two categories of contests. In perfectly discriminating contests, the highest effort secures the win, as, for example, in an all-pay auction (Hillman and Samet 1987; Baye et al., 1996; Krishna and Morgan 1997; Moldovanu and Sela, 2001). In imperfectly discriminating contests, a higher effort leads to a higher probability of a win, but this does not necessarily imply a win (Dixit and Norman 1978; Nitzan 1991, 1994). Most contributions on imperfectly discriminating contests adopted the logit-form contest success function (e.g., Skaperdas and Grofman 1995; Nti 1997, 1999), whereas a few papers adopted the probit form (e.g., Lazear and Rosen 1981; Dixit 1987).
Similarly, our analytical framework is a special case of the ‘success function with possibility of a draw’ defined in Blavatskyy (2010). Blavatskyy (2010) defined a draw as the contest outcome without either side winning, when two or more contestants obtain equal rights for the prize and they share the price. In this respect, we consider the case in which the contest outcome is restricted (i.e., either one of the contestants wins the contest unilaterally or all contestants end up in a draw; Blavatskyy 2010, Section 3.2, p. 272), and, in the case of a draw, the prize is not shared among contestants (for example, it is retained by the contest designer as in Dasgupta and Nti 1998).
The specific functional form adopted here follows Dasgupta and Nti (1998, Equation 1, p. 590) with the difference that we consider imperfectly discriminating contests (\(z > 0\)).
This remark clearly holds also in Sect. 3, where each agent has a linear production function for effective investment.
The probability that “one of the two firms discovers” is the sum of the probabilities of “firm 1 discovers first” and “firm 2 discovers first” by mutual exclusivity.
In the R&D literature, the term “spillover effect” is generally used when knowledge of the R&D results leaks to other firms (Arrow 1962). Baye and Hoppe (2003) argued that innovation tournaments exhibit not only negative externalities due to the well-known negative business-stealing effect, but also positive externalities among players’ R&D efforts due to a “leap-frogging effect” on the value of the prize. Baye et al. (2012) and Chowdhury and Sheremeta (2011a, b, 2015) examined contests in which winner and loser prizes may be asymmetrically influenced by rival effort. See also Dechenaux and Mancini (2008) analyzing a generalized contest payoff function in all-pay auctions.
Our analysis is consistent with \(\theta\) ranging in the interval (0, 1] and \(z > (1 - \theta ^2) / \theta\). This allows negative spillovers to have more impact on each party’s winning probability than positive spillovers. This is intuitive: if more than 100% of each player’s effort can be exploited by the competitor(s), players would find the contest not appealing and they are very unlikely to enter in competition. Relaxing these conventional assumptions has the potential to generate convexity issues that may undermine the existence of a unique Nash equilibrium. The coexistence of weak and strong positive spillover effects in competition may be a fruitful avenue for future theoretical and experimental research.
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Appendix
Appendix
Proof of Proposition 1 and of Corollary 2
The privately optimal investments in effort \(e_i^*, \, i \in \{1,2\}\) are given by:
The second order sufficiency conditions for \(e_i^*\) to be an interior Nash equilibrium, i.e.,
for \(i,j=1,2; \, i \ne j\), are satisfied since \(h{'}(e_i) > 0\) and \(h{''}(e_i) < 0\), \(\forall i\). In equilibrium, \(e_1^* = e_2^* = e^{*}\), where \(e^{*}\) is given by:
To ensure that \(e^*\) is an equilibrium effort per player with payoff function \(R_i\), we have to show that \(e^*\) is in fact a global optimum for \(R_i\) given the other player is choosing \(e^*\). But this follows straightforwardly from the concavity of \(R_i\) in \(e_i\), as shown in (7). Thus, the sufficiency condition for \(e^{*}\) to be an interior Nash equilibrium is clearly satisfied and this implies a unique pure strategy equilibrium. The socially optimal investments in effort \(e_i^{**}, \, i \in \{1,2\},\) are computed as the solutions of the following FOCs:
The second order sufficiency conditions for \(e_i^{**}\) to be an interior Nash equilibrium, i.e.,
for \(i,j=1,2; \, i \ne j\), are satisfied since \(h{'}(e_i) > 0\) and \(h{''}(e_i) < 0\), \(\forall i\). In equilibrium, \(e_1^{**} = e_2^{**} = e^{**}\), where \(e^{**}\) is given by:
The second order sufficiency condition for \(e^{**}\) to be an interior Nash equilibrium is clearly satisfied. The first order conditions (8) and (11) lead to
The LHS in (12) is larger than 1 if and only if \(e^{*} \ge e^{**}\). Conversely, the RHS in (12) is always larger than 1 when \(V \ge T\). When \(V < T\), the RHS in (12) is larger than 1 if and only if \(w \le \underline{w}\), where:
Thus, \(w \le \underline{w}\) is a necessary and sufficient condition for \(e^{*} \ge e^{**}\) when \(V < T\). \(\square\)
Proof of Proposition 3 and of Corollary 4
Player i’s probability of winning the contest is increasing in his expenditure at a decreasing rate:
The marginal impact of an increase of one player’s effort on the other player’s probability of winning the contest is defined as:
Player i’s probability of winning the contest is decreasing in the other player’s expenditure at an increasing rate. This implies \(e_{i,s} (1- \theta ^2) - \theta z > 0\).
The privately optimal investments in effort \(e_{i,s}^{*}, \, i \in \{1,2\},\) are given by:
with \(\theta \in (0,1]\). The second order sufficiency conditions for \(e_{i,s}^{*}\) to be an interior Nash equilibrium, i.e.,
are always satisfied \(\forall i,j=1,2, \, i \ne j\). In equilibrium, \(e_{1,s}^{*} = e_{2,s}^{*} = e_{s}^{*}\), where \(e_{s}^{*}\) is given by:
The second order sufficiency condition for \(e_{s}^{*}\) to be an interior Nash equilibrium is clearly satisfied. By deriving \(e_{s}^*\) from (20) and \(e^{*}\) from the linear specification of (8), it follows that \(e_{s}^* < e^{*}\) for \(\theta \in (0,1]\). The socially optimal investments in effort \(e^{**}_{i,s}, \, i \in \{1,2\},\) are computed as the solutions of the following FOCs:
The second order sufficiency conditions for \(e_{i,s}^{**}\) to be an interior Nash equilibrium, i.e.,
are always satisfied for \(i,j=1,2, \, i \ne j\). In equilibrium, \(e_{1,s}^{**} = e_{2,s}^{**} = e_{s}^{**}\), where \(e_{s}^{**}\) is given by:
The second order sufficiency condition for \(e_{s}^{*}\) to be an interior Nash equilibrium is clearly satisfied.
The first order conditions (20) and (23) lead to
The LHS in (24) is larger than 1 if and only if \(e_{s}^{*} \ge e_{s}^{**}\). Conversely, the RHS in (24) is larger than 1 if and only if \(w \le \underline{w}_{s}\), where:
Thus, \(w \le \underline{w}_s\) is a necessary and sufficient condition for \(e_{s}^{*} \ge e_{s}^{**}\). Since \(e_{s}^* < e^*\), when \(e^{*}_{s} (1 - \theta ^2) - \theta z > 0\), \(\underline{w}> \underline{w}_s > 1\). When \(e^{*}_{s} (1 - \theta ^2) - \theta z = 0\), \(\underline{w} > \underline{w}_s = 1\); when \(e^{*}_{s} (1 - \theta ^2) - \theta z < 0\), \(0< \underline{w}_s< 1 < \underline{w}\). \(\square\)
Proof of Proposition 5 and Corollary 6
Player i’s probability of winning the contest is increasing in his expenditure at a decreasing rate:
with \(\theta \in (0,1]\). The marginal impact of an increase of one player’s effort on the other players probability of winning the contest is defined as follows:
with \(i,j,k = 1,2,3, \, i\ne j \ne k\). Player i’s probability of winning the contest is decreasing in the other player’s expenditures at an increasing rate. This implies \(e_{i,sm} (1 - \theta ) (1 + 2 \theta ) - \theta z> 0\).
The privately optimal investments in effort \(e_{i,sm}^{*}, \, i \in \{1,2,3\}\) are given by:
The second order sufficiency conditions for \(e_{i,sm}^{*}\) to be an interior Nash equilibrium, i.e.,
are always satisfied \(\forall i,j,k \in \{1,2,3\}\). In equilibrium, \(e_{1,sm}^{*} = e_{2,sm}^{*} = e_{3,sm}^{*} = e_{sm}^{*}\), where \(e_{sm}^{*}\) is given by:
The second order sufficiency condition for \(e_{sm}^{*}\) to be an interior Nash equilibrium is clearly satisfied. By deriving \(e^{*}_{s}\) from (20) and \(e^{*}_{sm}\) from (32), it can be shown that \(e^{*}_{s} > e^{*}_{sm}\), for all \(V,z > 0\) such that \(e^{*}_{s}, e^{*}_{sm} > 0\). In the absence of spillover (i.e., \(\theta = 0\)), (32) becomes:
By deriving \(e^{*}\) from the linear specification of (8) and \(e^{*}_{m}\) from (33), it follows that \(e_m^{*} < e^{*}\), and that \(3 e^{*}_{m} > 2 e^{*}\), \(\forall V, \, z >0\). The socially optimal investments in effort \(e^{**}_{i,sm}, \, i \in \{1,2,3\}\), are computed as the solutions of the following FOCs:
The second order sufficiency conditions for \(e^{**}_{i,sm}\) to be an interior Nash equilibrium, i.e.,
are always satisfied. In equilibrium, \(e^{**}_{1,sm} = e^{**}_{2,sm} = e^{**}_{3,sm} = e^{**}_{sm}\), where \(e^{**}_{sm}\) is given by:
The second order sufficiency condition for \(e^{**}_{sm}\) to be an interior Nash equilibrium is clearly satisfied. In the absence of spillover (i.e., \(\theta = 0\)), (36) becomes:
The first order conditions (32) and (36) lead to
The LHS in (38) is larger than 1 if and only if \(e_{sm}^{*} \ge e_{sm}^{**}\). Conversely, the RHS in (38) is always equal or larger than 1 if an only if \(w \le \underline{w}_{sm}\), where:
Thus, \(w \le \underline{w}_{sm}\) is a necessary and sufficient condition for \(e_{sm}^{*} \ge e_{sm}^{**}\). Given \(e^{*}_{s} > e^{*}_{sm}\), by comparing (25) and (39) it follows that \(\underline{w}_{s} < \underline{w}_{sm}\) when \(2 e^{*}_{sm} > e^{*}_s\). In the absence of spillover (i.e., \(\theta = 0\)), (38) becomes:
The LHS in (40) is larger than (equal to) 1 if and only if \(e_{m}^{*} > e_{m}^{**}\) (\(e_{m}^{*} = e_{m}^{**}\)). Conversely, the RHS in (40) is always equal or larger than 1 when \(V \ge T\). When \(V < T\), the RHS in (40) is equal or larger than 1 if an only if \(w \le \underline{w}_{m}\), where:
Given \(e^{*}_{m} < e^{*}\) and \(3 e^{*}_m > 2 e^{*}\), by comparing (13) and (41), it can be easily verified that \(\underline{w} < \underline{w}_{m}\). \(\square\)
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Guerra, A., Luppi, B. & Parisi, F. Productive and unproductive competition: a unified framework. Econ Polit 36, 785–804 (2019). https://doi.org/10.1007/s40888-017-0077-z
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DOI: https://doi.org/10.1007/s40888-017-0077-z