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arxiv: 2604.26443 · v1 · submitted 2026-04-29 · 💰 econ.TH

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Dynamic Cheap Talk without Feedback

Atulya Jain

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Pith reviewed 2026-05-07 12:31 UTC · model grok-4.3

classification 💰 econ.TH
keywords dynamic cheap talksender-receiver gamesBayesian persuasionpartial commitmentuniform equilibriaMarkov statesno feedback
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The pith

Dynamic interaction without feedback lets the sender reach any equilibrium payoff from a partial-commitment persuasion model, and the full Bayesian persuasion payoff when her payoff ignores the state.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper studies a repeated sender-receiver game in which the sender observes a Markov-evolving state but receives no information about the receiver's actions. It shows that the sender can attain every payoff that arises as an equilibrium in a static persuasion model with partial commitment, where she can switch only to signaling policies that keep the overall frequency of each message unchanged. The same holds for any convex combination of those payoffs taken across different message distributions. When the sender's payoff does not depend on the realized state, the dynamic game delivers exactly the payoff that full Bayesian persuasion would produce.

Core claim

Any equilibrium payoff of a persuasion model with partial commitment—defined by the sender's ability to deviate only to signaling policies that preserve the marginal distribution over messages—can be achieved as a uniform equilibrium payoff in the dynamic game. Any convex combination of such payoffs across message distributions can also be sustained. When the sender's payoff is state-independent, she achieves the Bayesian persuasion payoff.

What carries the argument

Uniform equilibrium in the infinite-horizon discounted dynamic game, which enforces consistency with marginal-preserving deviations and thereby maps the partial-commitment persuasion benchmark into repeated play.

If this is right

  • Senders attain every payoff possible under partial commitment defined by marginal-preserving deviations.
  • Convex combinations of those payoffs across message distributions remain attainable.
  • State-independent sender payoffs reach the full Bayesian persuasion level.
  • Absence of feedback does not prevent the dynamic interaction from partially substituting for commitment.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Repeated no-feedback play may serve as a practical substitute for commitment devices in information-design settings where full commitment is unavailable.
  • Laboratory experiments could test whether human subjects converge to the predicted uniform equilibria when actions remain unobserved.
  • The equivalence may carry over to finite horizons or non-Markov state processes under suitable strategy restrictions.

Load-bearing premise

Uniform equilibria exist and can be sustained in the infinite-horizon discounted game, and the partial-commitment benchmark is exactly captured by deviations that preserve message marginals.

What would settle it

A strategy profile in the dynamic game that produces a payoff lying outside the convex hull of all partial-commitment persuasion equilibria with marginal-preserving deviations.

Figures

Figures reproduced from arXiv: 2604.26443 by Atulya Jain.

Figure 1
Figure 1. Figure 1: Comparison of benchmarks and partial commitment Consider persuasion with partial commitment. The marginal λ ∈ ∆(M) restricts the set of feasible collections of posterior beliefs. Since M = {m1, m2}, we identify λ = P(m1) ∈ [0, 1]. For instance, let π = 1/2 and λ = 1/2. Then any feasible pair of posteriors must satisfy pm1 = 1/2 + x and pm2 = 1/2 − x for some x ∈ [−1/2, 1/2]. The think tank’s optimal equili… view at source ↗
Figure 2
Figure 2. Figure 2: Recursive decomposition of receiver’s beliefs under σ ∗ Receiver’s strategy: In each period n, the sender sends a message mn. If mn has not yet reached its quota, the receiver plays according to κ(· | mn), a best response given his posterior belief. Otherwise, he ignores mn and instead plays according to κ(· | m′ ) for some different message m′ whose quota has not yet been exhausted. Thus, the message sent… view at source ↗
read the original abstract

We study a dynamic sender-receiver game in which the sender observes a state evolving according to a Markov chain but does not observe the receiver's action. Despite the absence of feedback, dynamic interaction partially restores commitment. We show that any equilibrium payoff of a persuasion model with partial commitment, where the sender can deviate to signaling policies that preserve the marginal distribution over messages, can be achieved as a uniform equilibrium payoff in the dynamic game. Moreover, any convex combination of such payoffs across message distributions can also be sustained. When the sender's payoff is state-independent, she achieves the Bayesian persuasion payoff.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper analyzes a dynamic sender-receiver cheap-talk game in which the sender privately observes a Markov-evolving state but receives no feedback on the receiver's actions. It claims that any equilibrium payoff of a partial-commitment persuasion benchmark—defined by allowing the sender to deviate only to signaling policies that preserve the unconditional message marginal—can be attained as a uniform equilibrium payoff of the dynamic game. Convex combinations of such payoffs across different message distributions are also sustainable, and when the sender's payoff is state-independent the dynamic game delivers the full Bayesian-persuasion payoff.

Significance. If the central equivalence is established, the result would be a meaningful contribution to the literatures on dynamic information design and commitment in cheap talk. It shows that repeated interaction without action feedback can partially substitute for commitment power, and it supplies a concrete link between uniform equilibria in discounted infinite-horizon games and a well-defined partial-commitment persuasion model. The state-independent case recovering the Bayesian-persuasion value is particularly clean and falsifiable.

major comments (2)
  1. [Proof of the main equivalence theorem] The uniform-equilibrium construction (main theorem) must verify that, for every state and every δ sufficiently close to 1, the continuation-value loss from any marginal-preserving deviation strictly exceeds the one-shot gain. Because the receiver observes only the public message sequence and the sender observes the current state, a deviation that leaves the unconditional message distribution unchanged can be statistically indistinguishable from equilibrium play in finite samples; the manuscript therefore needs to exhibit explicit history-dependent punishment strategies and derive the required lower bound on the continuation loss.
  2. [Section on convex combinations of message distributions] The claim that convex combinations across message distributions are sustainable requires that the receiver can credibly switch between distinct response rules while deterring the sender from choosing a different marginal in any period. The construction must show that the induced per-period payoff vector remains an equilibrium payoff of the partial-commitment benchmark for every convex weight; otherwise the convex-hull statement does not follow from the single-distribution result.
minor comments (2)
  1. [Abstract] The abstract and introduction should state the precise range of discount factors for which the uniform-equilibrium property holds (e.g., for all δ ≥ δ̄ or in the limit as δ → 1).
  2. [Notation and definitions] Notation for message marginals, state-transition kernels, and the partial-commitment deviation set should be introduced once and used consistently; currently the same symbol appears to denote both the equilibrium marginal and the set of allowable deviations.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful and constructive report. The comments correctly identify areas where the equilibrium constructions require additional explicit verification and elaboration to ensure full rigor. We will revise the manuscript accordingly by expanding the relevant proof sections with the requested details on punishment strategies and convex-combination incentives. These changes strengthen the paper without altering its main claims or results.

read point-by-point responses
  1. Referee: [Proof of the main equivalence theorem] The uniform-equilibrium construction (main theorem) must verify that, for every state and every δ sufficiently close to 1, the continuation-value loss from any marginal-preserving deviation strictly exceeds the one-shot gain. Because the receiver observes only the public message sequence and the sender observes the current state, a deviation that leaves the unconditional message distribution unchanged can be statistically indistinguishable from equilibrium play in finite samples; the manuscript therefore needs to exhibit explicit history-dependent punishment strategies and derive the required lower bound on the continuation loss.

    Authors: We agree that the proof of the main theorem must explicitly verify incentive compatibility for all marginal-preserving deviations, including a lower bound on continuation losses that dominates one-shot gains for δ close to 1. The current construction uses a block-based strategy in which the sender commits to a fixed signaling policy with the target marginal for T periods (with T large but finite), after which the receiver updates beliefs on the empirical message frequencies and applies a continuation equilibrium. To address the concern, we will add a dedicated lemma in the revised proof that specifies the history-dependent punishment: upon observing an empirical marginal deviating by more than ε from the target (detectable asymptotically via the law of large numbers, which applies uniformly because the message process is i.i.d. conditional on the marginal), the receiver switches permanently to a myopic best response that imposes a per-period loss L > 0 on the sender. The one-shot gain from any such deviation is bounded above by some G independent of δ; choosing δ > 1 - L/G then ensures the discounted continuation loss strictly exceeds the gain for every state. This bound holds because the Markov state evolution does not affect the message marginal under the deviation, preserving statistical distinguishability in the limit. revision: yes

  2. Referee: [Section on convex combinations of message distributions] The claim that convex combinations across message distributions are sustainable requires that the receiver can credibly switch between distinct response rules while deterring the sender from choosing a different marginal in any period. The construction must show that the induced per-period payoff vector remains an equilibrium payoff of the partial-commitment benchmark for every convex weight; otherwise the convex-hull statement does not follow from the single-distribution result.

    Authors: We thank the referee for highlighting the need to connect the convex-hull result directly to the partial-commitment benchmark. The manuscript achieves convex combinations via public randomization (or an initial public draw) that selects a weight λ and corresponding marginal at the beginning of each block; the players then play the single-distribution equilibrium associated with the realized marginal, with the receiver's action rule conditioned on the selected marginal. We will revise the section to include a supporting lemma proving that, for any convex weight λ, the resulting per-period payoff vector is itself an equilibrium payoff of the partial-commitment model: any unilateral deviation by the sender to a non-selected marginal triggers the same punishment as in the single-distribution case (switch to a punishing action), and the linearity of the benchmark payoffs in the marginal ensures that the mixture remains incentive-compatible. This establishes that the convex hull is attainable without requiring additional credibility constraints beyond those already verified for each component. revision: yes

Circularity Check

0 steps flagged

No circularity: dynamic-game payoffs derived from game structure, not presupposed

full rationale

The paper analyzes a sender-receiver game with Markov state evolution, no receiver-action feedback, and public messages. It shows that payoffs from the partial-commitment persuasion benchmark (sender deviations preserving message marginals) are attainable as uniform equilibria, including convex combinations, and that state-independent sender payoffs recover the Bayesian persuasion value. No quoted step reduces the target result to a self-definition, a fitted input renamed as prediction, or a load-bearing self-citation chain. The equivalence is obtained by constructing strategies in the discounted infinite-horizon game whose continuation values deter marginal-preserving deviations, without the construction presupposing the target payoffs. The derivation remains self-contained against the stated game primitives.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard game-theoretic assumptions including rational play, common knowledge of the Markov state process, and the existence of uniform equilibria in discounted infinite-horizon games. No free parameters, new entities, or ad-hoc axioms are introduced in the abstract.

axioms (2)
  • domain assumption The state evolves according to a Markov chain.
    Explicitly stated in the model description.
  • standard math Players are rational and select uniform equilibria.
    Standard assumption in dynamic game theory required for the equilibrium payoff claims.

pith-pipeline@v0.9.0 · 5374 in / 1427 out tokens · 79722 ms · 2026-05-07T12:31:00.692526+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

6 extracted references · 2 canonical work pages · 2 internal anchors

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