## Abstract

This paper analyzes the occurrence of the group-size paradox in situations in which groups compete for rents, allowing for degrees of rivalry of the rent among group members. We provide two intuitive criteria for the group-impact function which for groups with within-group symmetric valuations of the rent determine whether there are advantages or disadvantages for larger groups: social-interactions effects and returns to scale. For groups with within-group asymmetric valuations, the complementarity of group members’ efforts and the composition of valuations are shown to play a role as further factors.

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## Notes

- 1.
If the rent under consideration has the character of a group-specific public good, an economically meaningful definition of group-membership is with respect to the “coverage” of the public good. In this sense, consumers who are influenced by some government regulation and who decide not to organize any form of resistance nevertheless form the group of consumers.

- 2.
Impact functions are defined as the functions with which individuals transform effort into relative chance of success in a contest (Wärneryd 2001). Group impact functions correspondingly play the role of production functions with which group members jointly “produce” a higher relative chance of their group winning the contest.

- 3.
In Appendix K we show that this approach yields the same results as a comparison between groups and argue that it is slightly more general.

- 4.
- 5.
- 6.
This claim may appear to be at odds with Esteban and Ray (2001) who focus on convexities in the cost-of effort functions. However, their model is isomorphic to a model with linear costs and nonlinear impact functions that is a special case of our model.

- 7.
- 8.
The literature on contests between groups has been surveyed by Corchón (2007, Section 4.2), Garfinkel and Skaperdas (2007, Section 7), and Konrad (2009, Chapters 5.5 and 7). Sheremeta (2018) summarizes the experimental literature on group conflicts, and Kolmar and Hoffmann (2018) summarizes the more recent theoretical papers and compares them with findings from evolutionary biology, social psychology, and neuroscience.

- 9.
- 10.
For example, \(M = \{Anne,Bob,Cora,Dora,Ercan\}=\{A,B,C,D,E\}\) and \(N=\{\{A,B\},\{C,D,E\}\}\). The only possible composition for group \(\{A,B\}\) is the entire group while \(\mu _{\{C,D,E\}}=\{\{C,D\},\{C,E\},\{D,E\},\{C,D,E\}\}\) is the set of compositions of group \(\{C,D,E\}\). A contest would then for example be a game with players \(\{A,B,C,E\}\).

- 11.
See Cornes and Sandler (1996) for a comprehensive discussion of different types of public goods with crowding. Note that the linear case (as for example in Esteban and Ray 2001) \(v_k(i) = \alpha \frac{w}{\sharp i} + (1-\alpha ) w'\), where

*w*is the utility from the rival dimensions (with an equal-sharing rule being applied) of the rent and \(w'\) the utility from the non-rival part, is a special case of our formulation. - 12.
It is also possible to consider other cases, but for reasons of space these will only shortly be discussed.

- 13.
To illustrate this notation, assume that group

*i*has three members, \(\sharp i=3\), and \(i = \{1,2,3\}\) with valuations \(v_1(i) = 5, v_2(i) = 10, v_3(i) = 15\). Let \(i' = \{1,2\}\) and \(i'' = \{2,3\}\) be two compositions of group members. Then, \(\vec{v}_{i'}(i) = (5,10)\) and \(\vec{v}_{i''}(i) = (10,15)\). - 14.
- 15.
These assumptions rule out impact functions with for example hyperbolic (Cobb-Douglas) or L-shaped (perfect complements) indifference curves. Impact functions with \(\partial q_{i'}(0,...,0)/\partial x^k =0\) usually lead to multiple equilibria because irrespective of valuations, all group members of any group may jointly contribute zero effort and the remaining groups may play interior best responses. See Skaperdas (1992) for an extensive discussion in a somewhat different context. This would cause additional and merely technical problems that would divert attention from the main focus of the paper.

- 16.
Suppose a group has access to a mechanism solving its collective action problem. In this case, agents fully internalize their effect on the payoff of others and thus optimize as if their valuation of the rent were \(v_i(i') = \sum _{k\in i'} v_k(i')\). Therefore, equilibrium efforts (and thus winning probabilities) will be equal to those obtained in a contest with within-group symmetric valuations \(v_i(i')\). If the rent is not too rival and the new group members’ valuations are not too low, we will further have \(v_i(i')<v_i(i')\) and thus the described case.

- 17.
In Appendix L we show that this also holds for voluntary-contribution games as Bergstrom et al. (1986).

- 18.
It could be argued that a class of impact functions should fulfill a stronger condition than Assumption 7 such as \(\forall i',i'': q_{i'}(\vec{x}_{i'})=q_{i''}(\vec{x}_{i''})\) whenever \(x_k = 0\) for all \(k\in i''\backslash i'\). We do not require (and indeed by Assumption 5 necessarily violate) this condition for the following reason: Consider 100 individuals participating in a political campaign. It may matter for their impact on policies a lot whether they belong to a group of 100 or 1000 individuals affected by that policy. The notion of complementarity captures this idea. Large complementarities means that an interest group of 1000 individuals will only have an impact if all individuals contribute and not only a subset. The above condition however violates this intuition.

- 19.
We restrict attention to \(\gamma _i \in (0,1)\) to guarantee uniqueness of the equilibrium. If \(\gamma _i \le 0\), multiple equilibria can occur because of within-group coordination failure: If at least one group member exerts zero effort, group impact is zero and it is rational for the other group members to also exert zero effort. However, Propositions 3 and 4 continue to hold for \(\gamma _i \le 0\) in all but the extreme equilibrium where all members of all groups exert zero effort.

- 20.
These results are given in Kolmar and Rommeswinkel (2013). For our purposes, explicit results are not necessary.

- 21.
Quite literally, since in the perfect substitute case with rivalry, all old group members will become freeriders.

- 22.
Notice that if the marginal productivity gain of adding group member

*k*to the composition would be effort independent, this can be captured via the function \(\zeta _i\) and is therefore accounted for. - 23.
In a contest with \(q_{i'}(0,\dots ,0)=0\) at least two groups participate. Since we do no make this assumption, it may be that all groups contribute zero effort because the starting advantage of one group is too large. However, then at least one group will have \(q_{i'}(0,\dots ,0)>0\).

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## Author information

### Affiliations

### Corresponding author

## Additional information

### Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

We thank three anonymous referees, Stefan Bühler, Hung-Chi Chang, Philipp Denter, Jörg Franke, Reto Föllmi, Magnus Hoffmann, Wen-Tai Hsu, Nick Netzer, Marco Runkel, Dana Sisak, and Felix Várdy for very helpful comments.

Financial support by the Swiss National Science Foundation through grants P1SGP1_148727 and P2SGP1_155407 is gratefully acknowledged.

## Appendices

### Appendix A: Proof of Theorem 1

For ease of notation, define \(Q_{-i}= \sum _{j' \in N' \backslash \{i'\}} q_{j'}(\vec{x}_{j'})\) and \(Q= \sum _{j'\in N'} q_{j'}(\vec{x}_{j'})\). For notational convenience, in the following proofs we will often omit the arguments of functions, i.e., write \(q_{i'}\) instead of \(q_{i'}(\vec{x}_{i'})\).

The first order conditions (FOCs) are:

We start by showing that the first order conditions are sufficient conditions for an equilibrium. The second order conditions for a local maximum are:

which holds for \(Q_{-i} \ge 0\) and \(\frac{\partial ^2 q_{i'}(\vec{x}_{i'})}{\partial (x_k)^2} \le 0\), which holds by Assumption 3. Since the above concavity condition holds for all \(x_k \in [0,\infty )\) we only need to verify that \(\pi (\infty , \vec{x}_{-k}) \le \pi (x_k^*, \vec{x}_{-k})\) and \(\pi (0, \vec{x}_{-k}) \le \pi (x_k^*, \vec{x}_{-k})\). Since the FOC is strictly decreasing in \(x_k\), we must have for all \(x_k \in [0,x_{i'}^*)\): \(\frac{\partial \pi _i^k(x_k,\vec{x}_{-k})}{\partial x_k}>\frac{\partial \pi _i^k(x_{i'}^*,\vec{x}_{-k})}{\partial x_k}\). This means profits are strictly increasing in \(x_k\) over the interval \([0,x_{i'}^*)\) and thus \(\pi (0, \vec{x}_{-k}) < \pi (x_k^*, \vec{x}_{-k})\). Further, since \(\pi (\infty , \vec{x}_{-k})=-\infty < 0 \le \pi (0, \vec{x}_{-k})\) the solution to the FOCs indeed yields a global maximum of the expected payoff for each player.

What is left to show is that there exists a unique solution to the system of FOCs given that \(\forall i,k: x_{k}^*=x_{i'}^*\).^{Footnote 23} By Assumption 4 we have for all *k*, *l*: \(\frac{\partial q_{i'}(x_i,\dots ,x_i)}{\partial x_k} = \frac{\partial q_{i'}(x_i,\dots ,x_i)}{\partial x_l}\). Therefore, if \(\forall i,k: x_k^*=x_{i'}^*\), then the system of FOCs can be reduced to:

where *k* is an arbitrary member of \(i'\).

We furthermore have the following relation between *Q*, \(p_{i'}\) and \(x_i\):

where \({{\underline{p}}_{i'}}(Q)\) is the lower bound on the winning probability given a specific *Q*. Since \(q_{i'}(x_i,\dots ,x_i)\) is strictly increasing in \(x_i\), we can solve this for \(x_i(Q,p_{i'})\) as long as \(Q>0\) and \(p_{i'} \ge{{\underline{p}}_{i'}}(Q)\). Finally, we can rewrite

which by Assumption 3 is weakly decreasing in *Q* and \(p_{i'}\). The left equation of the Kuhn–Tucker conditions then becomes:

Since \(\rho\) is weakly decreasing in *Q* and \(p_{i'}\), the LHS of (A.3) is strictly decreasing in \(p_{i'}\) and *Q*. Further, for \(p_{i'}\rightarrow \infty\), the LHS is negative while for \(p_{i'}={q_{i'}(0,\dots ,0)/Q}\) it can be negative or positive. Therefore, for each strictly positive *Q* there exists a unique \(p_{i'} \in [0,\infty )\) which solves the Kuhn–Tucker conditions where \(p_{i'}=q_{i'}(0,\dots ,0)/Q\) if \(v_i(i')/Q \cdot \rho (Q,0)\le 1\) and \(p_{i'}=1\) if \(Q=0\). We can therefore form the function \(p_{i'}(Q)\) as the solution to the FOC of each group *i*.

What remains to be shown is that a unique strictly positive \({Q'}^*\) exists such that the winning probabilities \(p_{i'}({Q'}^*)\) sum to one. Notice that \(p_{i'}(Q)\) has the following properties: It is continuous, \(\lim _{Q\rightarrow 0} p_{i'}(Q)=1\) and \(\lim _{Q\rightarrow \infty } p_{i'}(Q)=0\) and it is strictly decreasing. Therefore, \(\sum _{i'} p_{i'}(Q)\) is also strictly decreasing, continuous and has \(\lim _{Q\rightarrow 0} \sum _{i'} p_{i'}(Q)>1\) as well as \(\lim _{Q\rightarrow \infty } \sum _{i'} p_{i'}(Q)=0\). It follows by the intermediate value theorem that a \({Q'}^* \in (0,\infty )\) exists such that \(\sum _{i'} p_{i'}({Q'}^*)=1\). Since \(\sum _{i'} p_{i'}(Q)\) is strictly decreasing, this \({Q'}^*\) is unique. Given a unique \({Q'}^*\), we can obtain unique solutions for \(p_{i'}({Q'}^*)\) and thus \(x_{i'}^*\) and via \(\forall i,k: x_k^{*}=x_{i'}^*\) also for all \(x_k^{*}\).

### Appendix B: Proof of Theorem 2

The first order condition for an equilibrium is:

First notice that Assumption 5 implies Assumption 4, i.e., we are only considering a subset of the impact functions, therefore the results from the proof of Theorem 1 carry over. Since we thus know that the equilibrium is unique given \(\forall i,k: x_k^*\), we only need to show that under the more strict Assumption 5, any equilibrium must fulfill \(\forall i,k: x_k^*\).

From Assumption 5 we have that

Therefore, in equilibrium it can never be that case that \(x_l^{*} =0\) if \(x_k^* >0\) since then the above FOC (B.1) does not hold for at least one group member. Thus, either \(\forall k: x_k^*=0\) or \(\forall k: x_k^*>0\). If \(x_k^*>0\) then inserting the FOC for player *k* into the FOC for player *l* yields \(x_k^*=x_l^*\) and thus the desired condition.

Inserting this into the FOCs reduces the equilibrium conditions to (A.2). We therefore obtain as shown in the existence proof for each group *i* a best response function \(p_{i'}(Q)\) which is continuous and strictly decreasing for \(p_{i'}(Q)>0\). The necessary condition for an equilibrium is now \(\sum _{i'} p_{i'} (Q) =1\). Since \(\sum _{i'} p_{i'} (Q)\) is strictly decreasing in *Q*, if there exists a \({Q'}^*\) which solves the necessary condition (as has been shown in the existence proof), it is unique. Since \(p_{i'}(Q)\) is monotonic in *Q* and \(x_i(p_{i'}, Q)\) is monotonic in \(p_{i'}\), the strategies \(x_k^*=x_i(p_{i'}({Q'}^*),{Q'}^*)\) are unique solutions to the FOCs.

We can now write \(x_{i''}(p_{i'},Q)\) as the solution of \(p_{i'}=\frac{q_{i'}(x_i,\dots ,x_i)}{Q}\) for \(x_i\) when \(Q>0\). Since \(q_{i'}\) is strictly increasing, \(x_{i''}\) is a function and strictly increasing in *Q* for \(p_{i'}>0\) and strictly increasing in \(p_{i'}\).

It follows from non-increasing RTS and Assumptions 3, and 5 that \(\frac{\partial q_{i'}(x_i,\dots ,x_i)}{\partial x_k}\) is non-increasing in \(x_i\). Therefore, the LHS of the left equation in (A.2) is strictly decreasing in \(p_{i'}\) and *Q*, which, together with Continuity of \(q_{i'}\) from Assumption 3 implies that for each group *i* there exists a unique best response function \(p_{i''}(Q)\) which solves the above FOC. Notice that since the LHS is strictly decreasing in both *Q* and \(p_{i'}\), \(p_{i''}(Q)\) must be strictly decreasing whenever the FOC holds with equality, i.e., whenever \(p_{i'} \ge 0\). This reduces all equilibrium conditions to \(\sum _{i'} p_{i''} (Q) =1\). Since all \(p_{i''}\) are decreasing in *Q* and for \(\sum _{i'} p_{i''}(Q)>0\) at least for some *i* the function \(p_{i''}(Q)\) is strictly decreasing, the LHS is strictly decreasing in *Q*. Thus, if there exists a \({Q'}^*\) which solves the equilibrium condition, it is unique.

### Appendix C: A useful Lemma

### Lemma 1

*Suppose a contest fulfills Assumptions*1, 2, 3, *and*4*for all groups. Further*, \(\forall j,k: v_k(m_j)=v_j(m_j)\). *Consider two within-group symmetric equilibria, which only differ by the group sizes*\(i' \ne i'\)*and/or the impact functions*, \(q_{i'}(\cdot ) \ne q_{i'}(\cdot )\). *Suppose group**i**participates under group size*\(i'\)*and impact function*\(q_{i'}(\cdot )\)*with winning probability*\(p_{i'}^*\). *Let the winning probability under group composition*\(i''\)*and impact function*\(q_{i''}(\cdot )\)*be*\(p_{i''}^*\). *Then the following equivalence holds*:

*where*\(x_{i''}\)*is defined such that*

This Lemma has a very intuitive explanation: If and only if for a switch from \(i'\) to \(i''\) (while holding the winning probability constant) the LHS of the FOC is too low, the group will respond by increasing the effort from which a higher winning probability results. The only complication in the proof is that one has to address the possibility of a response by other groups which overcompensates this effect.

### Proof

The first-order condition for an interior solution, evaluated at the solution, becomes after rearranging terms:

We first show that

and since the cases are exhaustive, the reverse implication is then automatically proven.

\(p_{i'}^* > p_{i''}^*\): This implies that either \({Q'}^* <{Q''}^*\) or \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*)>q_{i'}(x_{i''}^*,\dots ,x_{i''}^*)\). We first show that \({Q'}^* <{Q''}^*\) yields a contradiction: If \(p_{i'}^* > p_{i''}^*\) then there exists a group *j*: \(p_{j'}^*<p_{j''}^*\). Together with \({Q'}^* <{Q''}^*\), this implies that

By (C.2) this is equivalent with:

Since \(q_{j'}(\ldots )\) has constant or decreasing RTS, this implies \(q_{j'}(x_{j'}^*,\dots ,x_{j'}^*) \ge q_{j'}(x_{j''}^*,\dots ,x_{j''}^*)\). But since \({Q'}^*<{Q''}^*\), we have \(p_{j'}^* > p_{j''}^*\) and thus a contradiction. From this follows that if \(p_{i'}^* > p_{i''}^*\), then \({Q'}^* \ge{Q''}^*\) and \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*)>q_{i'}(x_{i''}^*,\dots ,x_{i''}^*)\). The latter implies \(x_{i''}> x_{i''}^*\) via the definition of \(x_{i''}\). Since \(q_{i'}\) has constant or decreasing RTS, we have:

From \(p_{i'}^* > p_{i''}^*\) and \({Q'}^* \ge{Q''}^*\) follows \({Q'}^*/(1-p_{i'}^*) >{Q''}^*/(1-p_{i''}^*)\). Using the FOCs, we have:

Combining this equation with (C.5), immediately yields the \(p_{i'}^*>p_{i''}^*\) part of (C.3).

The proof for \(p_{i'}^* < p_{i''}^*\) follows the same steps with reverse inequalities and is therefore omitted.

\(p_{i'}^* = p_{i''}^*\): This implies that either \({Q'}^* ={Q''}^*\) and \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*)=q_{i'}(x_{i''}^*,\dots ,x_{i''}^*)\) or \({Q'}^* \lessgtr{Q''}^*\)\(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*) \lessgtr q_{i''}(x_{i''}^*,\dots ,x_{i''}^*)\).

Suppose \({Q'}^* ={Q''}^*\) and \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*)=q_{i'}(x_{i''}^*,\dots ,x_{i''}^*)\) hold. Then it immediately follows from the FOCs that

By definition of \(x_{i''}\) we then have the symmetric part of (C.1).

For the case \({Q'}^* \lessgtr{Q''}^*\), \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*) \lessgtr q_{i''}(x_{i''}^*,\dots ,x_{i''}^*)\) we can show that this yields a contradiction. It follows from these assumptions that there exists a group *j* with \(p_{j'}^*\gtreqqless p_{j''}^*\) such that:

Furthermore,

Applying the FOCs gives us:

But from this follows \(x_{j'}^*<x_{j''}^*\) since the group composition does not change between \(j'\) and \(j''\) and thus

which contradicts (C.6).

Suppose \({Q'}^*<{Q''}^*\) and \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*) > q_{i'}(x_{i''}^*,\dots ,x_{i''}^*)\). Then there exists a group *j* such that: \(q_{j'}(x_{j'}^*,\dots ,x_{j'}^*)<q_{j''}(x_{j''}^*,\dots ,x_{j''}^*)\) and by \(q_{j'}=q_{j''}\) being a strictly increasing function, \(x_{j'}^*<x_{j''}^*\). From this follows by Assumption (3) that

By the FOCs we then have:

Since \({Q'}^*<{Q''}^*\) this implies \(p_{j'}^* > p_{j''}^*\). But then there must exist a group *g* such that \(p_{g'}^*< p_{g''}^*\) since \(p_{i'}^* \ge p_{i''}^*\). It follows that \(q_{g'}(x_{g'}^*,\dots ,x_{g'}^*)<q_{g''}(x_{g''}^*,\dots ,x_{g''}^*)\) and thus \(x_{g'}^*< x_{g''}^*\). Due to Assumption (3) we then have for some *l* in \(g'\) that

from which follows

But then \(p_{g'}^* > p_{g''}^*\) which yields the contradiction. \(\square\)

### Appendix D: Proof of Proposition 1

### Proof

We employ the total differential:

For equal inputs we can write \(q_{i'}(x_i,\dots ,x_i)=g(x_i, i')\). The total differential then becomes for symmetric efforts:

and thus

for \(x_i-x_i' \rightarrow 0\). Similarly, we have:

for \(x_i-x_i' \rightarrow 0\). It follows from (D.3) and (D.4) that:

since by absent SSIE it holds that \(g({x_i}, i')=g({x_i}\frac{\sharp i'}{\sharp i'}, i'')\) and \(g({x_i'}, i')=g({x_i'}\frac{\sharp i'}{\sharp i'}, i'')\).

To apply Lemma 1, we need to know what the symmetric effort level \(x_{i''}\) of the group after the increase in size would need to be in order to obtain \(q_{i'}(x_{i'}^*,\dots ,x_{i'}^*) = q_{i''}(x_{i''},\dots ,x_{i''})\). With absent SSIE we have:

Lemma 1 then yields:

which given (D.5) reduces to the desired condition:

Therefore, if the rent is a public good, the winning probability is independent of group size for an impact function with absent SSIE at the equilibrium effort \(x_{i'}^*\) for a change in group size from \(\sharp i'\) to \(\sharp i''\). If the rent is partly private, it is strictly decreasing in group size.

For the welfare effects, we have:

\(v_i(i')=v_i(i'')\): It follows from \(p_{i'}^*=p_{i''}^*\) and \(S_i(x_{i'}^*,i',i')\) that \(x_{i'}^*>x_{i''}^*\). Inserting this into \(\pi _i^*-\pi _{i''}^*\) we get: \((p_{i'}^*-p_{i''}^*)(v_i(i')) - (x_{i'}^*-x_{i''}^*)\). Since the first term is equal to zero and the second term negative, we get that \({\pi '_k}^{*}<{\pi _k''}{*}\) from which the statements for average and total utility follow for \(v_i(i')=v_i(i'')\).

\(v_i(i')>v_i(i'')\): Let \(v_i(i'')\rightarrow 0\). Then \({\pi _{k}'}^{*} \rightarrow 0\). Since \({\pi _{k}'}^{*}>0\), and \({\pi _{k}''}^{*}\) is continuous in \(v_i(i'')\) the existence of \(\underline{v_i(i'')}\) follows.

We cannot specify \(\underline{v_i(i'')}\) more precisely under the very general assumptions. Especially, we cannot know, whether \(\underline{v_i(i'')}\lesseqgtr \sharp i'v_i(i')/\sharp i''\) which is the private good case. \(\square\)

### Appendix E: Proof of Proposition 2

### Proof

We assume throughout that we are in a symmetric, interior equilibrium. By homogeneity of degree \(r_i\), we have from Euler’s theorem

and further

Using homogeneity of the impact function and the above expression for the partial derivative, we get for the measure of SSIE:

Lemma 1 now tells us that

where \(x_{i''}\) is defined such that

We can make use of homogeneity of degree \(r_i\) and solve for \(x_{i''}\):

where the last step follows from (E.3). Plugging this definition back into (E.4), we get using (E.2):

By canceling terms, this simplifies to:

For the welfare effects, we have:

\(\pi _{i'}^{A}\gtreqless \pi _{i''}^{A} \quad \Leftrightarrow \quad p_{i'}^*v_i(i')-x_{i'}^* \gtreqless p_{i''}^*v_i(i'')- x_{i''}^*.\) We furthermore have:

from inserting (E.2) into (B.1). Inserting this into the above equation for \(x_{i'}^*\) and \(x_{i''}^*\) and rearranging terms yields the result. The total welfare effects follow by multiplying with \(\sharp i'\) and \(\sharp i''\) on the LHS and RHS, respectively.

For public goods \(v_i(i')=v_i(i'')\) it immediately follows that for \(\pi _i^{k*}\ge \pi _{i''}^{k*}\) to hold, we must have \(p_{i'}^* > p_{i''}^*\) and thus the group-size paradox must hold strictly for the welfare group-size paradox to hold. For private goods this is not the case. The average utility criterion yields: \(p_{i'}^*/\sharp i' \left( 1-(1-p_{i'}^*)\frac{r_i}{\sharp i'}\right) \ge p_{i''}^*/\sharp i''\left( 1-(1-p_{i''}^*)\frac{r_i}{\sharp i''}\right)\). The total utility criterion yields: \(p_{i'}^* \left( 1-(1-p_{i'}^*)\frac{r_i}{\sharp i'}\right) \ge p_{i''}^*\left( 1-(1-p_{i''}^*)\frac{r_i}{\sharp i''}\right)\). For the total utility criterion we therefore again need the group-size paradox to hold strictly for the welfare group-size paradox to hold. \(\square\)

### Appendix F: Proof of Theorem 3

### Proof

We prove that the only class of impact functions fulfilling the assumptions is given by:

\(\gamma _i \in (0,1)\), \(r_i \in (0,1]\).

From independence of the class of impact functions, the continuity of the impact functions, strict monotonicity of the impact functions, and Theorem 1 of Gorman (1968), we have that for group sizes larger or equal to 3:

where \(T_{i'}\) and \(f_{k,i'}\) are continuous strictly monotone functions and without loss of generality \(f_{k,i'}(0)=0\).

By Homogeneity of degree \(r_i\), we have after setting \(x_l=0\) for all \(l\ne k\) and taking the inverse of *f*,

Moreover, we can derive from homogeneity and Euler’s homgeneous function theorem the functional equation:

to which we can apply Pexider’s functional equation Aczél and Dhombres (1989) \(g_0(\sum _k s_k) = \sum _k g_k(s_k)\) with the continuous solution being that all functions are affine. The solution to the functional equation yields therefore

This is an ordinary differential equation with solution:

Since *k* was arbitrarily chosen (or by solving the corresponding ordinary differential equations induced by the solutions to RHS of the Pexider equation), this solution must hold for all *k*. By our normalization assumption, we have that \(B_k=0\). It is straightforward to use Assumption 5 to obtain that \(A_{k,i'}\) and \(C_{k,i'}\) do not depend on *k*. Moreover, using Assumption 7 we can establish that \(A_{k,i'}\) is even consistent across group compositions, i.e., \(A_{k,i'}=\gamma _i\). We have therefore derived

The only parameter that remains to be chosen is \(T_{i'}[f_{k,i'}(1)]\) which may depend on composition. Letting \(T_{i'}[f_{k,i'}(1)] = \frac{\zeta _i(i')}{(\sharp i')^{r_i/a_i}-r_i}\) yields our desired functional form. The impact function of \(\sharp i' = 2\) follows from independence by substituting \(x_k=0\) into an impact function of a composition with \(\sharp i''=3\). Order equivalence on the remaining two dimensions and identical returns to scale guarantee that the impact function of two dimensions must be equal to a linear transformation of the impact function with 3 group members and some \(x_k=0\).

The cases of \(r_i<0\), \(r_i> 1\), \(\gamma _{i'}>1\), and \(\gamma _i\le 0\) are excluded by monotonicity in \(x_k\), concavity (both from Assumption 3), and nonnegativity of the range of \(q_{i'}\). \(\square\)

### Appendix G: Proof of Theorem 4

Before beginning the main proof, it will be useful to derive the following two lemmas.

### Lemma 2

*If*
\(a_1 \ge a_2 > a_3\)
*or*
\(a_3 > a_2 \ge a_1\)
*and*
*f*
*is an integrable convex function, then*

### Proof

Case \(a_3<a_1\): From convexity of *f*, we have for all *h*

Integrating both sides gives:

which yields the desired condition:

Case \(a_3>a_1\): From convexity of *f*, we have for all *h*

Integrating both sides gives:

which yields the desired condition:

\(\square\)

The above Lemma 2 can be used to derive the following result:

### Lemma 3

*Suppose*\(\vec{v}^{(n)}\)*is obtained from a sequence of*\(\theta\)-*power mean preserving spreads of*\(\vec{v}^{(1)}\). *Then*

### Proof

Suppose \(\vec{v}^{(1)},\dots \vec{v}^{(n)}\) is a sequence of vectors generated by a sequence of \(\theta\)-power mean preserving spreads. If for all *i* it holds that

then it clearly also holds that:

We therefore only need to show this property for vectors which differ by a single power mean preserving spread. Notice that for any \(\phi\):

where \((v^{(i)}_H,v^{(i)}_L)\) refers to the vector of the two elements that are changed by the spreading operation and \((v^{(i+1)}_H,v^{(i+1)}_L)\) to the vector of these two elements after application of the spreading operation. Let w.l.o.g. \(v^{(i)}_H \ge v^{(i)}_L\) from which immediately follows \(v^{(i+1)}_H>v^{(i)}_H \ge v^{(i)}_L>v^{(i+1)}_L\) by the properties of the power mean preserving spread. That is, \(v_H^{(i)}\) refers to the element of \(\vec{v}^{(i)}\) which is increased to \(v_H^{(i+1)}\) and \(v_L^{(i)}\) to the decreased element of \(\vec{v}^{(i)}\).

From the power mean preserving spread also follows via evaluating (G.11) at equality:

which – after solving for \(v^{(i+1)}_H\) – yields:

Combining this condition with (G.11) and (G.9), what is left to show is:

which is implied by the following, more general condition:

Notice that standard mean inequalities or the reverse Jensen inequality from the previous appendix do not apply to prove (G.15). This would also be counterintuitive as then the proof would not rely on \(v^{(i)}_H \ge v^{(i)}_L > v^{(i+1)}_L\). We have to distinguish the cases \(\psi >0\) and \(\psi < 0\).

\(\psi >0\): Define \(f(a)=a^{\psi /\eta }\), which is strictly convex and \(a_1=(v_H^{(i)})^{\eta }\), \(a_2=(v_L^{(i)})^{\eta }\), and \(a_3=(v_L^{(i+1)})^{\eta }\). If \(\eta >0\), we have \(a_1\ge a_2 >a_3\), while if \(\eta <0\), we have \(a_3>a_2 \ge a_1\). In both cases Lemma 2 applies. Employing these definitions in Lemma 2 gives:

which simplifies to (G.15).

\(\psi <0\): Define \(f(a)=a^{\eta /\psi }\), which is strictly convex and \(a_1=(v_H^{(i)})^{\psi }\), \(a_2=(v_L^{(i)})^{\psi }\), and \(a_3=(v_L^{(i+1)})^{\psi }\). Since \(\eta <0\), we have \(a_3>a_2 \ge a_1\). Employing these definitions in Lemma 2 gives us:

which is equivalent with (G.15) since \(\eta\) is negative and the inequality sign thus changes direction once we exponentiate both sides with \(\eta\). \(\square\)

We now turn to the main proof of the theorem.

### Proof

Suppose \(\vec{v}'\) is more asymmetric than \(\vec{v}\) at mean parameter \(\theta\). Then \(\exists \omega : \omega \cdot \vec{v}'' = \vec{v}'\) and \(\vec{v}''\) is obtained from a sequence of \(\theta\)-power mean preserving spreads of \(\vec{v}\). Thus by Lemma 2,

By definition of a \(\theta\)-power mean preserving spread we have \({{\mathcal{M}}}(\vec{v}, \theta )={{\mathcal{M}}}(\vec{v}'', \theta )\). We therefore obtain:

Making use of the homogeneity of degree 1 of \({\mathcal{M}}\) and the definition of \(\omega \vec{v}''\) we have:

\(\square\)

### Appendix H: Proof of Theorem 5

### Proof

The proof proceeds similarly to the one for single-player contests in Cornes and Hartley (2005), with the main difference that first one has to obtain equilibrium conditions that fix relative efforts within each group. The optimality condition for individual *k* in composition \(i'\) yields:

with equality if \(x_k > 0\). Notice first that in equilibrium it can never be the case that \(Q_{-i}=0\), since then some individual will have an incentive to provide effort \(x_k=\epsilon\) with \(\epsilon \rightarrow 0\) to win the rent with probability 1. The expression for the partial derivative of the impact function becomes after rearranging terms:

From this expression can already be derived that if one group member participates in equilibrium, all group members do: Notice that if some group member *l* of group *i* participates in equilibrium, \(q_{i'} > 0\) and therefore at \(x_k=0\), \(\frac{\partial q_{i'}}{\partial x_k} = \infty\). But then the first order condition cannot hold for individual *k* in that equilibrium, since we have \(Q>0\) and \(Q_{-i}>0\) and thus the LHS of the optimality condition (H.1) is infinite, which is greater than the RHS.

Since either all group members participate or none, we can express the following relationship among efforts within a group:

Notice that this relation trivially also holds for groups that do not participate. Rearranging and summing over all *l* yields:

Substituting this relation into the optimality condition yields:

where \(V_i=r_i \zeta _i(i')^{1/r_i} \cdot \left( \frac{1}{\sharp i'} \sum _l (v_l)^{\frac{\gamma _i}{1-\gamma _i}}\right) ^{\frac{1-\gamma _i}{\gamma _i}}\).

We now show that for every group *i*, there exists a function \(p_{i'}(Q)\) such that at \(p_{i'}(Q)=\frac{q_{i'}}{Q}\), the optimality condition is fulfilled. \(p_{i'}(Q)\) corresponds to a share function of a single player contest (Cornes and Hartley 2005), only with the change of interpretation that it is the share of the whole group on which the within-group equilibrium condition (H.3) has been imposed.

Notice that if \(r_i < 1\) we have that \(q_{i'}=0\) can never be a best response to any positive \(Q_{-i}\), since then the LHS of the above optimality condition (H.4) is infinite. We rewrite the optimality condition therefore in terms of winning probabilities \(p_{i'} = q_{i'}/Q\):

It is now easy to see that for all *Q* there exists a \(p_{i'}(Q)\) such that the optimality condition is fulfilled: Notice that for \(p_{i'}=1\), the LHS is strictly smaller than the RHS, while for \(p_{i'}=0\), the RHS is strictly smaller than the LHS. Since both are continuous functions of \(p_{i'}\), by the intermediate value theorem there then exists at least one \(p_{i'}(Q)\) such that the optimality condition holds with equality. Further, this point is unique, since the LHS is strictly decreasing in \(p_{i'}\), while the RHS is strictly increasing in \(p_{i'}\). This proves that there exists a unique best response \(p_{i'}(Q)\) to any level of *Q*. Moreover, \(p_{i'}(Q)\) is strictly decreasing in *Q* as can be verified from the following argument: Suppose *Q* increases, then the RHS is larger than the LHS of the optimality condition. Since the RHS is strictly increasing in \(p_{i'}\) and the LHS strictly decreasing, \(p_{i'}\) must decrease in order to maintain equality.

Suppose \(r_i=1\), then the optimality condition becomes

We can therefore directly solve for the best response winning probability:

which has the properties \(p_{i'}(0)=1\) and \(p_{i'}(V_i)=0\) and is obviously weakly decreasing in *Q*.

A Nash equilibrium is now given by a \({Q'}^*\) such that \(\sum _{i'} p_{i'}({Q'}^*) =1\). Without loss of generality, assume that the groups are ordered such that first all groups with \(r_i<1\) appear in any order and then the groups with \(r_i=1\) appear with \(V_{i} \ge V_{i+1}\). Notice that for \(Q=0\), we have \(p_{i'}(0)=1\) for all groups, while for \(Q\rightarrow \infty\), we have that \(p_{i'}(\infty )\rightarrow 0\). Therefore, \(\sum _{i'} p_{i'}(0)> 1 > \sum _{i'} p_{i'}(\infty )\) and a solution exists. For uniqueness, We distinguish two cases. In the first case, at least one group has \(r_i<1\) and therefore \(\sum _{i'} p_{i'}(Q)\) is strictly decreasing for all \(Q\in{\mathbb{R}}\) since \(p_1\) is strictly decreasing and all other \(p_{i'}\) are at least weakly decreasing. In the second case, all groups have \(r_i=1\). In this case, \(p_1\) is strictly decreasing on \([0,V_1]\) and \(p_2\) is strictly decreasing on \([0,V_2]\). Since for all \(i\ge 2\), \(p_{i'}(V_2) = 0\), we have that \(\sum _{i'} p_{i'}(V_2)<1\). Therefore, all solutions must lie in the interval \([0,V_2]\) in which \(\sum _{i'} p_{i'}(Q)\) is strictly decreasing and therefore a unique \({Q'}^*\) exists. Define \(n^*\) as the highest index of a group with \(r_i=1\) such that \(0> 1-{Q'}^*/V_i\), or if no such group exists as the number of groups with \(r_i<1\). This completes the proof. \(\square\)

### Appendix I: Proof of Theorem 6

### Proof

The proof goes by contradiction. Suppose we have that \(V_i\ge V_{i''}\) and \(p_{i'}^* < p_{i''}^*\). Then it follows that \(V_i\cdot (1-p_{i'}^*)>V_{i''}\cdot (1-p_{i''}^*)\). By (9) this is equivalent to:

and thus \({Q'}^*>{Q''}^*\).

Since \(p_{i'}^* < p_{i''}^*\) there must exist at least one group *j* such that: \(p_{j'}^* >p_{j''}^*\). Therefore, \(V_j\cdot (1-p_{j'}^*)>V_j\cdot (1-p_{j''}^*)\), since \(V_j\) does not differ between both equilibria. Using (9) for group *j* gives us:

and thus \({Q'}^*<{Q''}^*\) which yields a contradiction. By an analogous proof for \(V_{i'}\le V_{i''}\) and \(p_{i'}^* > p_{i''}^*\) then follows the theorem. \(\square\)

### Appendix J: Proof of Proposition 3

### Proof

From Theorem 6, we have that:

Rearranging terms and using \(S_i(i',i'') = \zeta _i(i'')/\zeta (i')\) and writing out \({{\mathcal{M}}}(\vec{v}_{i,i''}(i''), \frac{\gamma _i}{1-\gamma _i})\) gives us:

which yields:

from which follows (10), since \(\sharp i''-\sharp i' = \sharp i'''\) . \(\square\)

### Appendix K: Proof of Proposition 4

### Proof

Part (a) follows from using the definitions of \(R_i\) and \(v_k\) in (10):

Employing the definition of \({{\mathcal{M}}}(\vec{w}_{i,i'},{\textstyle \frac{\gamma _i}{1-\gamma _i}})\) gives us:

which after solving for \({{\mathcal{M}}}(\vec{w}_{i'''},{\textstyle \frac{\gamma _i}{1-\gamma _i}})\) yields the desired condition.

Part (a) follows from \({{\mathcal{M}}}(\vec{w}_{i,i'},{\textstyle \frac{\gamma _i}{1-\gamma _i}})\) being a power mean with \(\frac{\gamma _i}{1-\gamma _i}\) as the exponent. Since any power mean is weakly increasing in its exponent, and the exponent is increasing in \(\gamma _i\), \({{\mathcal{M}}}(\vec{w}_{i,i'},{\textstyle \frac{\gamma _i}{1-\gamma _i}})\) is increasing in \(\gamma _i\). Furthermore, any power mean is strictly increasing in its exponent, whenever there exist two unequal elements over which the mean is formed. Inserting \(R_i(i',i'')\) into (10) and simplifying gives the desired result.

(b) Follows directly from Theorem 4 and the assumption that \(\vec{w}_{i'''}\) is more asymmetric than \(\vec{w}_{i'}\) at \(\gamma _i/(1-\gamma _i)\). Note that we only consider cases with \(\gamma _i<1\) and thus \(\gamma _i/(1-\gamma _i)<\infty\).

(c) It is immediately obvious that \(\Gamma (\gamma _i,i',i',R_i,S_i,r_i)\) is increasing in \(R_i\) and decreasing in \(s_i\). The only difficulty is thus the proof of the behavior of \(\Gamma (\gamma _i,i',i',R_i,S_i,r_i)\) with changes in \(\gamma _i\). A useful result on which the proof is based is the reverse Jensen inequality (for a more general version and its proof, see Bullen 2003, p. 43):

### Lemma 4

*If**f**is convex*, \(\varrho _1 > 0\)*and*\(\varrho _i < 0\)*for all*\(2 \ge i \ge n\)*and*\(\sum _{j=1}^n \varrho _j = 1\), *then*\(f(\sum _{j=1}^n \varrho _j a_j) \ge \sum _{j=1}^n \varrho _j f(a_j)\)*for all*\(\sum _{j=1}^n \varrho _j a_j \in I\), *and the inequality holds strictly, if**f**is strictly convex and*\(\exists i,j: a_i \ne a_j\).

We now show that the following term is decreasing in \(\gamma _i\):

Define \(\theta _i = \frac{\gamma _i}{1-\gamma _i}\), which is increasing in \(\gamma _i\). What is to be shown is that the above term is decreasing in \(\theta _i\), thus:

whenever \(\phi _i > \theta _i\) and where \(\Psi = \frac{R_i(i',i')}{S_i(i',i'')^{1/r_i}}\). Note that \(\phi _i,\theta _i \in ( -1 , \infty )\) and therefore we will distinguish the cases \(0 < \phi _i\), and \(\phi _i < 0\). We will furthermore assume that \(\theta _i\) and \(\phi _i\) are not zero (which is equivalent to assuming that \(\gamma _i \ne 0\).

\(0 < \phi _i\): Since \(\phi _i\) is positive, we can rewrite condition (K.4) to:

Setting \(f(a)=a^{\phi _i/\theta _i}\) (which is strictly convex also for negative \(\theta _i\)) and \(\varrho _1 = \frac{i''}{i''-i'}\), \(\varrho _2 = - \frac{i'}{i''-i'}\), and \(a_1 = (\Psi )^{\theta _i}\), \(a_2 = 1^{\theta _i}\) in the above reverse Jensen inequality directly yields equation (K.5).

\(\phi _i < 0\): Since \(\theta _i\) is negative, we can rewrite condition (K.4) to:

Setting \(f(a) = a^{\theta _i / \phi _i}\) (which is strictly convex since the absolute value of \(\phi _i\) is smaller than that of \(\theta _i\)) and \(\varrho _1 =\frac{i''}{i''-i'}\), \(\varrho _2 = - \frac{i'}{i''-i'}\), and \(a_1 = (\Psi )^{\phi _i}\), \(a_2 = 1^{\phi _i}\) in the above reverse Jensen inequality directly yields equation (K.6). Therefore, condition (K.4) follows, which concludes the proof of part c) of the proposition. \(\square\)

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Kolmar, M., Rommeswinkel, H. Group size and group success in conflicts.
*Soc Choice Welf* (2020). https://doi.org/10.1007/s00355-020-01264-0

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