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Dynamic communication mechanism design


We consider dynamic communication mechanisms in a quasi-linear environment with single-dimensional types. The mechanism designer gradually identifies agents’ valuations by iteratively offering prices to agents at different stages. Agents pay the maximum price they accepted if their desirable decision is made. We show that within weakly tight mechanisms, if a communication mechanism is ex-post incentive compatible, then it is a monotone-price mechanism. English auctions are characterized as a class of mechanisms that satisfy ex-post incentive compatibility and efficiency.

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  1. See Rothkopf et al. (1990) for example.

  2. The strategic equivalence holds in a private value setting.

  3. We use female pronoun for the mechanism designer and male pronoun for an agent.

  4. Integer valuation is not crucial in our analysis. When valuation is bounded as we assume, it guarantees that the mechanism designer identifies the state of the world in finitely many steps.

  5. We discuss the case in which \(X_i\) is private information of agent i in Sect. 3.4.

  6. We will consider mechanisms such that \(V_i (h^t)\) is well defined and non-empty.

  7. See Appendix A for a formal definition as an extensive form game.

  8. We assume that a negative response against \(p_i\) implies a strict preference so that the mechanism designer can certainly identify \(v_i\).

  9. We do not argue the formal notion of the simplicity of a transfer rule or the commitment issue. Akbarpour and Li (2019) show that the credibility of a mechanism induces the pay-as-bid transfer rule.

  10. See Van Zandt (2007).

  11. Note that subgame perfection is not required for DSIC or OSP.

  12. The original “Ausubel auction” in Ausubel (2004) was not precisely ex-post perfect incentive compatible. Okamoto (2018) and Ausubel (2018) modify it to hold the property.

  13. Ties are broken not randomly, but in an arbitrary predetermined way. The efficient allocation rule is not unique.

  14. There is an exception when two or more agents respond yes at \(p_i^t={\bar{v}}\). In such cases, one agent is chosen as the winner and pays \({\bar{v}}\).

  15. Due to the perfect information assumption, actions of agents are made sequentially.

  16. Note that these mechanisms use more than two actions in a single round. Such auctions that iteratively offer prices and ask demands are common in dynamic multi-object auction designs. See Ausubel (2004, 2006), Ausubel and Milgrom (2002) and Mishra and Parkes (2007) for example.

  17. For a general case of dichotomous preferences, Mishra and Roy (2013) characterize DSIC in terms of cutoff valuations.

  18. See the main text for the conditions on p.

  19. For any round \(s<t\) such that agent i is asked, he always responds yes and \(p_i^s \le v_i\).


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Correspondence to Ryuji Sano.

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This paper was formerly entitled “Iterative Revelation Mechanisms”. I am grateful to Hitoshi Matsushima, Atsushi Kajii, Yuji Fujinaka, Yuta Nakamura, two referees, and an Associate Editor for their comments and suggestions. This research was supported by Grant-in-Aid for Young Scientists (KAKENHI 25780132 and 17K13698) from the Japan Society for the Promotion of Sciences (JSPS). All errors are mine.


Definition of extensive form games

In this appendix, we formally define DCM as extensive form games with perfect recall. A DCM is a tuple \(\Gamma =( {\mathcal {H}}, \prec , J, p, A, (Q_i)_{i \in I}, g, m)\), where

  1. 1.

    \({\mathcal {H}}\) is a set of all histories or nodes, and \(\prec\) is a partial order on \({\mathcal {H}}\) that represents precedence.

    1. (a)

      The initial node is denoted by \(h^0 \in {\mathcal {H}}\).

    2. (b)

      The set of terminal histories is denoted by \(H \equiv \{ h \in {\mathcal {H}} | \not \exists h', h \prec h' \}\).

    3. (c)

      We suppose that \(({\mathcal {H}}, \prec )\) is a binary tree. For every non-terminal history \(h \in {\mathcal {H}} {\setminus } H\), there are two immediate successors.

    4. (d)

      Let \(H^t \subset {\mathcal {H}}\) be the set of histories with depth t. That is,

      $$\begin{aligned} H^t \equiv \{ h \in {\mathcal {H}} \mid |\{ h' \in {\mathcal {H}} | h' \prec h \} | =t \}. \end{aligned}$$
    5. (e)

      \(({\mathcal {H}}, \prec )\) has finite depth. Hence, there exists a number \(K \in {\mathbb {N}}\) and

      $$\begin{aligned} {\mathcal {H}} = \bigcup _{t=0}^{K} H^t . \end{aligned}$$
    6. (f)

      In the main text, a non-terminal history is often denoted by \(h^t\) (using superscript), while a terminal history is denoted by h.

  2. 2.

    \(J: {\mathcal {H}} {\setminus } H \rightarrow I\) is a player function, which assigns a player at each non-terminal history.

    1. (a)

      For each \(i \in I\), let \({\mathcal {H}}_i \equiv \{ h \in {\mathcal {H}} {\setminus } H \mid J(h) = i \}\) be the set of non-terminal histories that belong to i.

    2. (b)

      In the main text, a mover at a non-terminal history \(h^{t-1} \in H^{t-1}\) is often denoted by \(J^t (h^{t-1})\).

  3. 3.

    \(p: {\mathcal {H}} {\setminus } H \rightarrow {\mathbb {Z}}\) is a price function, which assigns a price offered to the mover \(J (h^{t-1})\) at each non-terminal history.Footnote 18

  4. 4.

    In each non-terminal history \(h^t \in {\mathcal {H}} {\setminus } H\), the set of available actions at \(h^t\) is given by \(A = \{ yes, no \}\).

  5. 5.

    \(Q_i\) is an information partition on \({\mathcal {H}}_i\).

    1. (a)

      An information set is denoted by \(q_i \subset {\mathcal {H}}_i\).

    2. (b)

      We suppose that if \(h, h' \in q_i\), then there exists some \(t >0\) and \(h,h' \in H^t\).

  6. 6.

    \(g: H \rightarrow X\) is an allocation function, and \(m: H \rightarrow {\mathbb {Z}}^n\) is a monetary transfer function.

Given a mechanism \(\Gamma\), a pure strategy for agent i is a mapping \(\sigma _i : V_i \rightarrow \{ yes, no \}^{{\mathcal {H}}_i}\) such that \(\sigma _i (h) = \sigma _i (h')\) if h and \(h'\) are in the same information set.


Proof of Lemma 1

Suppose that a DCM is EPIC. The associated direct allocation rule is denoted by f. Suppose that there is an agent \(i \in I\) and for some \(v \in V\), \(f(v) \in X_i\). The associated sincere history under v is denoted by h. Because of sincere reporting and the definition of the payment rule, the agent’s payment must be \(m_i (h) \le v_i\).

Suppose that there exists \({\tilde{v}}_i >v_i\) and \(f({\tilde{v}}_i, v_{-i}) \not \in X_i\). When agent i of type \({\tilde{v}}_i\) behaves as if his type is \(v_i\), then the associated allocation is \(f(v) \in X_i\) and the payment is \(m_i (h)\). Hence, agent i’s deviating payoff is \({\tilde{v}}_i -m_i (h) >0\), which is a contradiction. \(\square\)

Proof of Lemma 2

Suppose that a DCM is EPIC. To have a contradiction, suppose that there exists a history h, and for some \(i \in I(g(h))\) and some round t, \(a_i^t =no\). Let t be the earliest such round, and consider \(p_i^t\). For any state \(v \in V(h)\), sincere reporting indicates \(v_i <p_i^t\). Suppose \({\tilde{v}}_i \ge p_i^t\). By Lemma 1, \(f({\tilde{v}}_i,v_{-i}) \in X_i\). By the construction of round t, the truthful history up to t is the same between v and \(({\tilde{v}}_i,v_{-i})\).Footnote 19 Hence, under the state \(({\tilde{v}}_i,v_{-i})\), agent i is offered \(p_i^t\) at round t and responds yes under sincere reporting. Thus, agent i pays at least \(p_i^t\), and the payoff under sincere reporting is at most \({\tilde{v}}_i -p_i^t\). If agent i deviates and pretends to have \(v_i\) under the state \(({\tilde{v}}_i,v_{-i})\), the corresponding outcome is \(f(v) \in X_i\) and the payment is strictly less than \(p_i^t\), which contradicts EPIC. \(\square\)

Proof of Proposition 1

Suppose that there is a history such that agent i reports no at round s and is asked at a later round \(t >s\). By the weak tightness, there exists a state \(v \in V(h^{t-1})\) and \(f(v) \in X_i\). However, this contradicts Lemma 2, which requires \(f(v) \not \in X_i\). \(\square\)

Proof of Theorem 1

If part. Because an English auction is a monotone-price mechanism, it is EPIC. We will confirm that an English auction chooses the efficient outcome for every \(v \in V\) under sincere reporting. To have a contradiction, suppose there exists a state \(v \in V\) and an agent not having the highest valuation wins the auction. Let \(I^* \subset I\) be the set of agents having the highest value under v. Let h be the associated terminal history. Because every agent \(i \in I^*\) loses the auction, i is asked a price \(p_i^t \ge v_i +1\) at some round t and responds no. Let agent i be the last agent who responds no among \(I^*\) under h. By the properties of the auction rule, there exists an active agent \(j \ne i\) and \(p_j^{t-1} ={\bar{p}}_Y^{t-1} \ge p_i^t-1\) at round \(t-1\). Because every agent in \(I^*\) except for i is inactive after round \(t-1\), agent j does not have the highest value. Hence, we have \(v_j < v_i \le p_i^{t} -1 \le p_j^{t-1}\), which contradicts sincere reporting of agent j. Hence, the auction is efficient.

Only if part. Suppose that a DCM is EPIC and weakly tight. Then, it is a monotone-price mechanism. It is easy to see that the third property of the auction rule holds. When two or more agents remain at the termination, it is clear that the efficient outcome cannot be identified. So \(|Y(h)| \le 1\) for all terminal history h. In addition, if \(Y (h^t) = \{i \}\) and the designer asks agent i at round \(t+1\), then the object is not allocated to anyone when i responds no. Hence, the mechanism terminates immediately if \(|Y(h^t)|=1\).

Now, suppose that the first property does not hold for some \(h^{t-1}\). Agent i is the unique active agent facing the highest current price of round \(t-1\) and the mover at round t. Then,

$$\begin{aligned} p_i^t> p_i^{t-1} = {\bar{p}}_Y^{t-1} > p_j^{t-1} \end{aligned}$$

for all \(j \in Y (h^{t-1}) {\setminus } \{ i \}\). Then a state v such that \(v_i = p_i^{t-1}\), \(v_j = p_j^{t-1}\) for each \(j \in Y (h^{t-1}) {\setminus } \{ i \}\), and \(v_k <p_k^{t-1}\) for each \(k \in I {\setminus } Y(h^{t-1})\) is in the revealed state set \(V(h^{t-1})\). The efficiency implies that agent i wins the auction, but he responds no at round t and loses, which is a contradiction. Hence, the first property holds.

Next, suppose that the second property does not hold for some \(h^{t-1}\). Suppose that agent i is the mover at round t and \(p_i^t \ge {\bar{p}}_Y^{t-1} +2\). Because \(p_i^{t-1} \le {\bar{p}}_Y^{t-1}\), a state v such that \(v_i = {\bar{p}}_Y^{t-1}+1\), \(v_j = p_j^{t-1}\) for each \(j \in Y (h^{t-1}) {\setminus } \{ i \}\), and \(v_k <p_k^{t-1}\) for each \(k \in I {\setminus } Y(h^{t-1})\) is in the revealed state set \(V(h^{t-1})\). The efficiency implies that agent i wins the auction, but he responds no at round t and loses, which is a contradiction. Hence, the second property holds. \(\square\)

Proof of Theorem 2

By Lemma 2 and \(I(x) \in \{ \emptyset , I \}\), the allocation \(g(h) =1\) only if no agent reports no in the history h. By definition of DCM, a terminal history such that no agent reports no is uniquely determined and denoted by \(h^*\). Let \(J \subseteq I\) be the set of agents making a report in \(h^*\) and let \({\bar{p}}_j\) be the maximum price offered to i in \(h^*\). Then, the direct allocation rule is described as

$$\begin{aligned} f(v) ={\left\{ \begin{array}{ll} 1 &{} \text {if } (\forall j \in J), v_j \ge {\bar{p}}_j \\ 0 &{} \text {otherwise} \end{array}\right. }. \end{aligned}$$

This allocation rule is clearly obtained by a unanimous voting among J with offered prices \(({\bar{p}}_j)_{j \in J}\). \(\square\)

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Sano, R. Dynamic communication mechanism design. Soc Choice Welf 57, 163–180 (2021).

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