Abstract
I study a two-player repeated game where payoffs are asymmetric. Attempts to form cooperative agreements in such an environment, for example by pro-rating actions relative to the one-shot Nash equilibrium, have generally struggled in practice. I show that cooperative arrangements when payoff functions are asymmetric tend to disproportionately favor the larger player. Incorporating social concerns, either via envious feelings on the part of the smaller player or altruistic feelings on the part of the larger player, shift quasi-cooperative incentives toward outcomes that are more favorable to the smaller player.
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Notes
United States v. Socony-Vacuum Oil Co., 310 US 150 (1940), reversing 105 F.2d 809 (7th Cir. 1939), reversing 23 F. Supp. 937 (W.D. Wisc. 1938).
The Saudis again honored their quota, while Iran produced slightly more than their allocated amount (2454 bpd). By contrast, Venezuela’s substantially exceeded their quota, producing 1852 bpd. See [3, Ch. 4] for discussion.
It is not clear that signatories could be forced to remain in any agreement—witness former President Trump’s recent decision to extract the USA from the Paris Agreement; and in any event the actions in the second stage are what really matter.
A second topic for consideration is the nature of the repeated game strategy. While the strategy used in Duffy and Muñoz García [15]—the grim strategy—is often used in the literature, Axelrod [5] suggests a potentially important role for strategies that are more forgiving. To that end, I consider both the grim strategy—under which defection yields perennial “punishment”—and a penal code strategy—which punishes for one period, and then relents in the event that all parties play in accordance with the strategy.
A simple condition that ensures this feature of reaction functions is \(\frac{\partial {\uppi }_1(y,y)}{\partial x_1} > \frac{\partial {\uppi }_2(y,y)}{\partial x_2}\).
Qualitatively similar results emerge in a repeated game with unknown endpoint, if \({\updelta }\) is interpreted as the probability the game will continue one more period. Alternatively, a collusive regime could emerge if players believe there is a positive probability that their rival is irrational [20, 27].
Note that, by construction, \(x_i^N = R_i(x_j^N), i = 1,2.\)
Two caveats apply. First, the Nash equilibrium satisfies the pair of conditions Eqs. (1)–(2); as there will be combinations that raise both players’ payoffs so long as \({\updelta } > 0\), I focus on the more cooperative combination. Second, for sufficiently large discount values the players can achieve what we might call “full cooperation,” namely combinations where one player’s payoffs are maximized subject to a minimum payoff constraint for the rival. I suppose the discount factor is too small to engender such an outcome in the discussion below.
It is algebraically tedious to characterize these various constraints. The code for these numerical analyses, which were conducted in MATLAB, is available upon request.
Recall that \(R_1 > R_2\).
[35, p. 417] describe a structure where “motivation can be described by a utility function depending on own payoff and deviation from fairness.”
The framework Fehr and Schmidt [18] propose is \(U_i({\uppi }_i,{\uppi }_j) = {\uppi }_i - {\upalpha }_i \text {max} ({\uppi }_j - {\uppi }_i, 0) - {\upbeta }_i \text {max} ({\uppi }_i - {\uppi }_j, 0)\) in a two-player setting. With \({\uppi }_1 > {\uppi }_2\), this collapses to \(U_2 = (1 + {\upalpha }_2) {\uppi }_2 - {\upalpha }_2 {\uppi }_1,\) which is equivalent to the description in Eq. (10) when \(\lambda _2 = -{\upalpha }_2/(1 - {\upalpha }_2)\), and \(U_1 = (1 - {\upbeta }_1) {\uppi }_1 + {\upbeta }_1 {\uppi }_2,\) which is equivalent to the description in Eq. (10) when \(\lambda _1 = {\upbeta }_1/(1-{\upbeta }_1).\) Assuming \(1> {\upalpha }_2, {\upbeta }_1 > 0,\) we then have \(\lambda _2< 0 < \lambda _1\).
For this diagram, as well as Fig. 5 below, I impose the constraint that player 2 is the small player, i.e., \(s_2 \le 1/2\). While this constraint is irrelevant when \(\lambda _2 = 0\), player 2’s share can exceed 1/2 at small values of \({\upalpha }\) when \(\lambda _2 < 0\).
This suggests that envy might potentially offset a considerable part of player 2’s payoff disadvantage.
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Mason summarized existing literature, described repeated game model, ran simulations, and wrote the draft.
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I thank two referees and the guest editor, each of whom provided insightful feedback that greatly improved the presentation of the manuscript. The usual disclaimer applies.
This article is part of the topical collection “Dynamic Games in Environmental Economics andManagement" edited by Florian Wagener and Ngo Van Long.
Appendix: Introducing Asymmetry Makes Player 1 Less Cooperative Under Pro-rata Reductions in the Linear-Quadratic Framework
Appendix: Introducing Asymmetry Makes Player 1 Less Cooperative Under Pro-rata Reductions in the Linear-Quadratic Framework
Consider the linear-quadratic framework introduced above, where \({\uppi }_i = ({\upalpha }_i - X)x_i, X = x_1 + x_2\) and \({\upalpha }_1 = 1, {\upalpha }_2 = 1 - {\upalpha }\). The incentive constraint supporting a quasi-cooperative regime when players choose the grim strategy is
where \({\uppi }_i^N = (x_i^N)^2, \ x_1^N = (1+{\upalpha })/3, \ x_2^N = (1-2{\upalpha })/3, \ X^N = x_1^N + x_2^N = (2-{\upalpha })/3\). Pro-rata reductions implies \(x_i^c = \mu x_i^N\), with \(\mu < 1.\) In this setting, \({\uppi }_i^c = \mu ({\upalpha }_i - \mu X^N) x_i^N\). Optimal defection, should it occur, would entail \(x_i^d = R_i(x_j^c) = ({\upalpha }_i - \mu x_j^N)/2\) and \({\uppi }_i^d = (x_i^d)^2\).
The incentive constraint can be recast as a condition on the discount factor:
Define \(\Omega = {\hat{{\updelta }}}_1 - {\hat{{\updelta }}}_2\); it is immediate that \(\Omega = 0\) if \({\upalpha } = 0\). I claim that \(\partial \Omega /\partial {\upalpha } > 0\), from which it follows that \(\Omega > 0\), for \({\upalpha } \in (0, .5]\). It is easy to see that \(\Omega \) is proportional to \({\upomega } \equiv ({\uppi }_2^d - {\uppi }_2^N)({\uppi }_1^d - {\uppi }_1^c) - ({\uppi }_1^d - {\uppi }_1^N)({\uppi }_2^d - {\uppi }_2^c)\), so it suffices to show that \({\upomega }\) is increasing in \({\upalpha }\). Expanding the definition of \({\upomega }\) yields:
Defining \(G_i^d = {\uppi }_i^d - {\uppi }_i^c\) and \(G_i^c = {\uppi }_i^c - {\uppi }_i^N\) allows \({\upomega }\) to be expressed more compactly as
I note that when \({\upalpha } = 0\) one has \(G_i^d = G^d \equiv \frac{(1 - \mu )^2}{4}\) and \(G_i^c = G^c \equiv -\frac{(1-\mu )(1 + 2\mu )}{9}\), for \(i = 1, 2\).
It is straightforward to calculate
Using these expressions along with the characterizations of \(G_i^c\) and \(G_i^d\), evaluating at \({\upalpha } = 0\), and inserting into Eq. (15) yields
where I used the fact that \(\mu < 1\), which implies the second term in the second line is strictly positive. Noting that \(\frac{(1-\mu )(1 + 2\mu )}{81} >0\) for \(\mu < 1\), and simplifying the first term, I conclude that a sufficient condition for \({\upomega } > 0\) is \(7\mu (\mu + 3) - 9 >0,\) which is easily seen to hold for \(\mu \ge 1/2.\)
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Mason, C.F. Cooperation in Dynamic Games with Asymmetric Players: The Role of Social Preferences. Dyn Games Appl 12, 977–995 (2022). https://doi.org/10.1007/s13235-022-00435-1
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DOI: https://doi.org/10.1007/s13235-022-00435-1