On group strategyproof and optimal object allocation


We consider a two-agent, single indivisible object allocation problem. We focus on continuous mechanisms that satisfy agent sovereignty, and investigate implications of group strategyproofness. In particular, we provide an explicit characterization of the strategyproof mechanisms and show that there are non-affine maximizer mechanisms that do not belong to the class characterized by Roberts (North-Holland, 1979). Further, we show that there are no budget-balanced strategyproof mechanisms. Also, we obtain an impossibility for existence of strong group strategyproof mechanism. We find that this impossibility goes away upon relaxing our notion of group strategyproofness, and consequently, present a class of weak group strategyproof mechanisms. Finally, we completely characterize the class of feasible strategyproof mechanisms satisfying individual rationality, and show that there are no optimal strategyproof expected revenue maximizing mechanisms under a general class of well behaved type distributions.

This is a preview of subscription content, log in to check access.


  1. 1.

    Individual rationality requires that participants of a mechanism always get non-negative utility irrespective of valuations reported.

  2. 2.

    Under certain regularity distributional conditions, Drexl and Kleiner (2015) show that the optimal strategyproof, feasible mechanism satisfying individual rationality must be budget balanced.

  3. 3.

    Hagerty and Rogerson (1987) interpret their cited result “as essentially negative”.

  4. 4.

    This premise has also been used by  Athey and Miller (2007), Miller (2011), Hagerty and Rogerson (1987), Drexl and Kleiner (2015) and Shao and Zhou (2016).

  5. 5.

    We often refer to this agent w(v) as the winner at profile v in the text.

  6. 6.

    Similar axioms have been used by Mishra and Marchant (2015) and Moulin and Shenker (2001).

  7. 7.

    That is, it characterizes the class of continuous mechanisms that satisfy AS and SP.

  8. 8.

    A mechanism \(\mu =(d,\tau )\) is a VCG mechanism if \(\forall \, v\in {\mathbb {R}}^N_+\), \(\forall \, i\in N\),

    $$\begin{aligned} d_i(v)=1 \implies v_i \ge v_j, \end{aligned}$$


    $$\begin{aligned} \tau _i(b) = \sum _{j\ne i} (d_j(v) -d_j(v_j)) v_j + h_i(v_j) \text{ where } h_i: {\mathbb {R}}^{N\setminus \{i\}}_+ \mapsto {\mathbb {R}} \text{ is } \text{ an } \text{ arbitrary } \text{ function } \text{ of } v_j. \end{aligned}$$
  9. 9.

    This stronger notion of strategyproofness has also been studied by Barberà et al. (2016), Bogomolnaia and Moulin (2004), Hatsumi and Serizawa (2009), Mitra and Mutuswami (2011), Serizawa (2006) and Pápai (2000).

  10. 10.

    A mechanism is said to be efficient if and only if at all type profiles, it allocates objects in a manner that maximizes aggregate welfare. That is, if a mechanism is efficient, then it allocates the object to a person who reports the highest valuation.

  11. 11.

    See Barbera et al. (2010), Barberà et al. (2012, 2016), Barbera and Jackson (1995), Hatsumi and Serizawa (2009), Mitra and Mutuswami (2011), Mukherjee (2013, 2014).

  12. 12.

    Jackson (2003) argues that in the absence of Pareto efficient and strategyproof mechanisms [as shown by Green and Laffont (1979)], budget balance should be treated as an equally important yardstick of efficient mechanisms as decision efficiency. A similar approach has been taken in Hagerty and Rogerson (1987) and Drexl and Kleiner (2015).

  13. 13.

    As argued in the previous paragraph, even if \(v_i=0, v_j=0\), i’s utility continues to be 0 irrespective of whether she is assigned an object or not.

  14. 14.

    They can be obtained by setting \(C_1,C_2\) and \(\eta \) equal to 0 in Theorem 3.

  15. 15.

    The result continues to hold if the lower bound of the support of distribution is positive.

  16. 16.

    See Elsgolts and Yankovsky (1973).

  17. 17.

    As stated in proof of Result 1, the characterization has been shown to be sufficient for SP by Nisan (2007)


  1. Ashlagi, I., Serizawa, S.: Characterizing vickrey allocation rule by anonymity. Soc. Choice Welfare 38, 531–542 (2012)

    Article  Google Scholar 

  2. Athey, S., Miller, D.: Efficiency in repeated trade with hidden valuations. Theor. Econ. 2, 299–354 (2007)

    Google Scholar 

  3. Barbera, S., Berga, D., Moreno, B.: Individual versus group strategyproofness: when do they coincide? J. Econ. Theory 145, 1648–1674 (2010)

    Article  Google Scholar 

  4. Barberà, S., Berga, D., Moreno, B.: Domains, ranges and strategy-proofness: the case of single-dipped preferences. Soc. Choice Welfare 39, 335–352 (2012)

    Article  Google Scholar 

  5. Barberà, S., Berga, D., Moreno, B.: Group strategy-proofness in private good economies. Am. Econ. Rev. 106, 1073–99 (2016)

    Article  Google Scholar 

  6. Barbera, S., Jackson, M.: Strategy-proof exchange. Econometrica 63, 51–87 (1995)

    Article  Google Scholar 

  7. Bogomolnaia, A., Moulin, H.: Random matching under dichotomous preferences. Econometrica 72, 257–279 (2004)

    Article  Google Scholar 

  8. De, P., Mitra, M.: Balanced implementability of sequencing rules, 2019. Working paper (2019)

  9. Drexl, M., Kleiner, A.: Optimal private good allocation: the case for a balanced budget. Games Econ. Behav. 94, 169–181 (2015)

    Article  Google Scholar 

  10. Elsgolts, L.E., Yankovsky, G.: Differential equations and the calculus of variations. Mir Moscow, Moscow (1973)

    Google Scholar 

  11. Green, J., Laffont, J.: Incentives in public decision making. (1979)

  12. Hagerty, K., Rogerson, W.: Robust trading mechanisms. J. Econ. Theory 42, 94–107 (1987)

    Article  Google Scholar 

  13. Hatsumi, K., Serizawa, S.: Coalitionally strategyproof rules in allotment economies with homogenous indivisible goods. Soc. Choice Welfare 33, 423–447 (2009)

    Article  Google Scholar 

  14. Jackson, M.: Mechanism theory. In Ulrich Derigs, editor, Encyclopedia of Life Support Systems. Oxford UK, (2003)

  15. Miller, D.: Robust collusion with private information. Rev. Econ. Stud. 79, 778–811 (2011)

    Article  Google Scholar 

  16. Mishra, D., Marchant, T.: Mechanism design with two alternatives in quasi-linear environments. Soc. Choice Welfare 44, 433–455 (2015)

    Article  Google Scholar 

  17. Mishra, D., Quadir, A.: Non-bossy single object auctions. Econ. Theory Bull. 2, 93–110 (2014). Forthcoming

    Article  Google Scholar 

  18. Mitra, M., Mutuswami, S.: Group strategyproofness in queueing models. Games Econ. Behav. 72, 242–254 (2011)

    Article  Google Scholar 

  19. Moulin, H., Shenker, S.: Strategyproof sharing of submodular costs:budget balance versus efficiency. Econ. Theor. 18, 511–533 (2001)

    Article  Google Scholar 

  20. Mukherjee, C.: Weak group strategy-proof and queue-efficient mechanisms for the queueing problem with multiple machines. Int. J. Game Theory 42, 131–163 (2013)

    Article  Google Scholar 

  21. Mukherjee, C.: Fair and group strategy-proof good allocation with money. Soc. Choice Welfare 42, 289–311 (2014)

    Article  Google Scholar 

  22. Myerson, R.: Optimal auction design. Math. Oper. Res. 6, 58–73 (1981)

    Article  Google Scholar 

  23. Nisan, N.: Algorithmic game theory. Cambridge University Press, Cambridge (2007)

    Google Scholar 

  24. Pápai, S.: Strategyproof assignment by hierarchical exchange. Econometrica 68, 1403–1433 (2000)

    Article  Google Scholar 

  25. Roberts, K.: The characterization of implementable choice rules. In Jean-Jacques Laffont, editor, Aggregation and Revelation of Preferences. Papers presented at the 1st European Summer Workshop of the Econometric Society. North-Holland, (1979)

  26. Serizawa, S.: Pairwise strategy-proofness and self-enforcing manipulation. Soc. Choice Welfare 26, 305–331 (2006)

    Article  Google Scholar 

  27. Shao, R., Zhou, L.: Optimal allocation of an indivisible good. Games Econ. Behav. 100, 95–112 (2016)

    Article  Google Scholar 

  28. Sprumont, Y.: Constrained-optimal strategy-proof assignment: beyond the groves mechanisms. J. Econ. Theory 148, 1102–1121 (2013)

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Conan Mukherjee.

Additional information

Publisher's Note

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

I would like to thank the associate editor and the anonymous referee, as well as Professors Tommy Andersson, Debasis Mishra and Manipushpak Mitra for their comments. I would also thank Parikshit De for discussions. Any remaining errors are mine.



Proof of Theorem 1

We first prove the following lemma that establishes two particular properties of \(T^\mu _i(.)\) functions for any strategyproof mechanism \(\mu \in \Gamma \).

Lemma 1

If a mechanism \(\mu =(d,\tau ) \in \Gamma \) satisfies SP, then

  1. (1)

    For all \(i\in N\), \(T_i^\mu (.)\)is a non-decreasing continuous function.

  2. (2)

    For all \(x,y \ge 0\), \(x=T^{\mu }_1(y) \Longleftrightarrow y=T^{\mu }_2(x)\).


To prove (1), fix \(y,y'\) such that \(0\le y<y'\). If \(T^\mu _1(y')<T^\mu _1(y)\), then for any \(x \in (T^\mu _1(y'), T^\mu _1(y))\) consider the profiles (xy) and \((x,y')\). By Result 1 and non-decreasingness of \(T_i^\mu (.)\) functions, \(d_2(x,y')=0\) and \(d_2(x,y)=1\), which contradict Result 1 itself. Arguing similarly for agent 2, we get that \(T_i^{\mu }(.)\) is a non-decreasing function for both \(i\in N\). Therefore, these functions must either be continuous or have jump discontinuities. Without loss of generality, consider the function \(T_1^\mu (.)\) and suppose that there exists a \(y\ge 0\) such that \(T^\mu _1(y) < \lim _{z \rightarrow y+} T^\mu _1(y)\). Fix an \(x \in \left( T^\mu _1(y) , \lim _{z \rightarrow y+} T^\mu _1(y) \right) \) and consider the sequence of profiles \(\{(x,y^r)\}\) such that for all r, \(y^r>y\) and \(\{y^r\} \rightarrow y\). By Result 1, \(d(x,y^r)=(0,1)\) for all r, but \(d(x,y)=(1,0)\). Since, \(\mu \in \Gamma \) and hence, continuous, we have \(u((1, \tau _1(x,y));x) = u((0, \tau _1(x,y));x)\), which implies that \(x=T^\mu _1(y)\). This contradicts our choice of x and so, \(T_i^\mu (.)\) functions must be continuous. Thus, condition (1) follows.

To prove (2), fix any \(x,y\ge 0\). There are two possibilities: (i) \(d_1(x,y)=1\) or (ii) \(d_2(x,y)=1\). If case (i) holds, then by Result 1, \(x\ge T^{\mu }_1(y)\) and \(y\le T^{\mu }_2(x)\). If \(x>T^{\mu }_1(y)\) and \(y=T^{\mu }_2(x)\), then choose \(\nu >0\) such that \(x>T^{\mu }_1(y+\nu )\) (by condition (1) established above, such a \(\nu \) exists). By Result 1, \(d_1(x,y+\nu )=d_2(x,y+\nu )=1\) and hence, a contradiction. Similarly, if \(x=T^{\mu }_1(y)\) and \(y<T^{\mu }_2(x)\), then choose \(\nu >0\) such that \(y<T^{\mu }_2(x-\nu )\). As before, Result 1 implies that \(d_1(x-\nu ,y)=d_2(x-\nu ,y)=0\) and hence, a contradiction. Arguing in similar manner, we can establish a contradiction in case (ii), and so, the result follows. \(\square \)

Using Lemma 1 above, we present the following proofs of necessity and sufficiency:

\({{\texttt {\textit{Only If:}}}}\)

Fix any mechanism \(\mu =(d,\tau ) \in \Gamma \) that satisfies SP. Result 1 and Lemma 1 imply the conditions (2) and (3) trivially. Further, condition (3) implies that \(T^{{\mu }^{-1}}_i(.)\) functions must be well defined for all i, and so, by Lemma 1, \(T_i^\mu (.)\) functions must be strictly increasing. Thus, condition (4) follows, and so, by Result 1, condition (1) follows. Finally, if \(T^\mu _1(0)>0\), then by conditions (3) and (4), \(T_1^\mu ( T^\mu _2(0))> T_1^\mu (0) \implies 0>T_1^\mu (0)\) which implies that there exists \(\nu >0\) such that \(0>T^\mu _2(\nu )\) which contradicts Result 1. Arguing similarly for \(T^\mu _2(.)\), condition (5) follows.

\({{\texttt {\textit{If:}}}}\)

Consider any mechanism \(\mu = (d,\tau )\) that satisfies the conditions (1)–(5) stated in the theorem. By Result 1, \(\mu \) satisfies SP.Footnote 17. Also, since \(T_i^\mu (x) \in [0,\infty ), \forall \, x\ge 0, \forall \, i\), \(\mu \) satisfies AS. To show continuity, consider, without loss of generality, a sequence of profiles \(\{v^r\}\) converging to \({\bar{v}}\) such that the allocation decisions are \(d(v^r)=(1,0)\) for all r. Therefore, by Result 1, \(v^r_1 \ge T^\mu _1(v^r_2)\) and \(v^r_2\le T^\mu _2(v^r_1)\) for all r. By condition (4), in limit \({\bar{v}}_1 \ge T^\mu _1({\bar{v}}_2)\) and \({\bar{v}}_2\le T^\mu _2({\bar{v}}_1)\). Now, if the allocation decisions are not preserved in limit, that is, \(d({\bar{v}})=(0,1)\); then \({\bar{v}}_1=T^\mu _1({\bar{v}}_2)\) and \({\bar{v}}_2=T^\mu _2({\bar{v}}_1)\), which implies that for both \(j\in N\), \(u(0,\tau _j({\bar{v}});{\bar{v}}_j)=u(1,\tau _j({\bar{v}});{\bar{v}}_j) = K_j^\mu (v_i)\), where \(i \ne j\). Hence, continuity of \(\mu \) follows and so, we can infer that \(\mu \in \Gamma \). \(\square \)

Proof of Theorem 2

There can be only two types of deviations by the pair \(\{1,2\}\): (1) decision-preserving deviations where the allocation decision remains same before and after deviation and (2) decision-changing deviations where the allocation decision changes after deviation. Note that for all \(i\in N\) and all \(z \ge 0\), if \(\eta =0\), then \(K^\mu _i(z)=C_i\); and if \(\eta =\infty \) then \(K^\mu _i(z)=C_i + T^\mu _i(z)\). Now if \(\eta =0\), it is easy to see that at any original type profile \(v=(v_1,v_2)\), no possible misreport that any agent \(j\in N\) can make, would affect the \(K^\mu _i(.)\) value for the other agent \(i\ne j\). So, any \(\{1,2\}\) deviation \(v'\) that violates WPGS must be decision changing. However, given that \(K^\mu _i(.)\) functions are constant functions for both i when \(\eta =0\), the winner at v would become strictly worse off by becoming loser at \(v'\), which contradicts our supposed violation of WPGS. Further, if \(\eta =\infty \), any decision preserving \(\{1,2\}\) deviation would leave the winner’s utility unchanged, and so, any such deviation that violates WPGS must be decision changing. Now, when \(\eta =\infty \), for any decision changing \(\{1,2\}\) deviation from v to \(v'\), the utility of w(v) at profile v (that is, \(v_{w(v)} + C_{w(v)})\) is, less than her utility at \(v'\) (that is, \(C_{w(v)}\)); which implies that no such \(\{1,2\}\) deviation can violate WPGS.

Now, we focus on mechanisms with a finite and positive \(\eta \in (0, \infty )\), and show the sufficiency with respect to each possible kind of deviation as a separate case. First, we define for all possible \(\{1,2\}\) deviations from the original valuation profile (xy) to a misreported valuation profile \((x',y')\);

$$\begin{aligned} \Delta _1:= u_1(d_1(x,y), \tau _1(x,y);x)- u_1(d_1(x',y'),\tau _1(x',y');x), \end{aligned}$$


$$\begin{aligned} \Delta _2:= u_2(d_2(x,y),\tau _2(x,y);y)- u_2(d_2(x',y'),\tau _2(x',y');y). \end{aligned}$$

Case(i) Decision preserving Suppose there exists a decision preserving deviation from (xy) to \((x',y')\) that violates WPGS, that is, \(\Delta _i <0\) for both i. Consider the possibility where \(d(x,y)=d(x',y')=(1,0)\), that is, \(\min \{x,x'\} \ge \max \{T^\mu _1(y),T^\mu _1(y')\}\) and \(\max \{y,y'\} \le \min \{T_2^\mu (x),T_2^\mu (x')\}\). Note that given the structure of \(K_i^\mu (.)\) functions, \(\Delta _2 <0\) is possible only if \(x <x'\), and \(T_2^\mu (x) < \eta \). Similarly, \(\Delta _1 <0\) is possible only if \(y' <y\), and \(\eta <T_1^\mu (y)\). Therefore, under this possibility of violation of WPGS, we can infer that \(\mathbf {(I)}\;\; 0\le y' \le y\le T^\mu _2(x)<\eta <T^\mu _1(y) \le x \le x'\). However, by condition (4) of Theorem 1 and construction of \(\eta \) such that \(T^\mu _i(\eta )=\eta \) for all \(i\in N\); we get that

$$\begin{aligned} \left\{ T^\mu _2(x)<\eta<T^\mu _1(y)\right\} \implies x<\eta < y, \end{aligned}$$

and hence, a contradiction to (I).

Arguing in a similar manner for the possibility where \(d(x,y)=d(x',y')=(0,1)\), we get that \(({{\mathbf {I}}}{{\mathbf {I}}})\;\; 0\le x' \le x< T^\mu _1(y)<\eta <T^\mu _2(x) \le y \le y'\). As before, by Theorem 1 and construction of \(\eta \), we get that \(y<\eta <x\), which contradicts (II). Therefore, we conclude that there can be no decision preserving \(\{1,2\}\)-deviation that violates WPGS when \(\eta \in (0,\infty )\).

Case(ii) Decision changing Suppose there exists a decision changing deviation from (xy) to \((x',y')\) that violates WPGS, that is, \(\Delta _i<0\) for all \(i\in N\). Without loss of generality, suppose that \(d(x,y)=(1,0)\) and \(d(x', y')=1\). Now, if \(\Delta _1 = x+K^\mu _1(y) - T^\mu _1(y) - K^\mu _1(y') <0\), then by Result 1, \(y'>y\), \(T^\mu _1(y)<\eta \) and \(x<\eta \). By Theorem 1 and construction of \(\eta \),

$$\begin{aligned} x< \eta \implies \left\{ T^\mu _2(x)<T^\mu _2(\eta )=\eta \right\} , \end{aligned}$$

and so, \(K^\mu _2(x)= T^\mu _2(x)+C_2\).

Now, if \(x' \le \eta \), then by the same logic, \(K^\mu _2(x')= T^\mu _2(x')+C_2\), which implies that \(\Delta _2 = K^\mu _2(x) - \{y+K^\mu _2(x') - T^\mu _2(x')\} = T_2^\mu (x) - y\). Now, by supposition \(d_2(x,y)=0\), and so, \(y \ge T_2^\mu (x)\) implying that \(\Delta _2 \ge 0\), which contradicts our supposition. On the contrary, if \(x'>\eta \), then arguing as before, \(T^\mu _2(x')>\eta \) and so \(K^\mu _2(x')=\eta +C_2\). Therefore, by Result 1, \(\Delta _2=(T^\mu _2(x)-y)+(T^\mu _2(x') - \eta ) > 0\) and so, a contradiction to our supposition. Thus, there can be no decision changing \(\{1,2\}\)-deviation that can violates WPGS when \(\eta \in (0,\infty )\). \(\square \)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mukherjee, C. On group strategyproof and optimal object allocation. Econ Theory Bull 8, 289–304 (2020). https://doi.org/10.1007/s40505-020-00184-7

Download citation


  • Group strategyproofness
  • Budget balance
  • Optimal mechanism

JEL classification

  • C72
  • C78
  • D71
  • D63