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Road to Efficiency: Avoyan & Ramos (2023)

Distilled by claude-sonnet-4-6 · extracted Jun 24, 2026, verified Jun 24, 2026

JEL (IAR-assigned): C73, C92, D83 · assigned from the abstract, not the journal

Full structured metadata (methods, scope, relatesTo, topics, datasets): raw Markdown (.md)

paper-summarygame-theoryexperimentalcoordinationmechanism-designpeer-reviewedunreplicated

What this is. The paper’s core results, the game-theoretic model of the minimum-effort game and the asynchronous revision mechanism, and the experimental design with its estimating comparisons: enough to understand what it found and how, without reading all 27 pages. To replicate or extend it, read the full source at the original.

Avoyan and Ramos run a laboratory experiment in the minimum-effort game, a canonical coordination game where groups chronically fail to reach the payoff-efficient outcome. They introduce a pre-play institution: an asynchronous revision mechanism (RM) in which each player posts a prepared effort choice that is publicly observable, but can be revised only when a stochastic revision opportunity is awarded. This incremental commitment makes prepared actions credible in a way that one-shot cheap-talk communication, as in Blume and Ortmann (2007), cannot. RM achieves 82.1 percent efficiency, versus 47.8 percent with no communication (Baseline) and 64.1 percent with one round of cheap-talk messages (S-CT). The efficiency gain requires all three components simultaneously: commitment (removing it via R-CT drops to 67.2%), asynchronicity (S-RM drops to 67.1%), and frequent revision opportunities (I-RM drops to 69.6%). The dynamic behavior within the pre-play phase also matches the theory: early revisions are forward-thinking (upward moves to lead others toward the efficient effort), while late revisions are myopic payoff-improving down-moves. Rich pre-play communication without commitment, as in Deck and Nikiforakis (2012), does not improve on one-shot cheap talk.

Magnitudes and significance as reported; \*\*\* = 1%. Locators point to the source PDF.

#ResultLocatorMagnitude
R1RM significantly increases efficiency over Baseline and cheap talk (S-CT)Figure 2, p. 2370; Result 1, p. 2371RM = 82.1%; Baseline = 47.8% (+34 pp, p < 0.01 MWU); S-CT = 64.1% (+18 pp, p < 0.01 MWU)
R2RM efficiency (82.1%) and initial efficient-effort rate (85.7%) are both significantly below the 100% theoretical prediction§IV.B, pp. 2371-2372; Result 2, p. 2372Both p < 0.01; exact point predictions of Calcagno et al. (2014) rejected
R3RM performance is invariant to exogenous initial choices (R-RM) and to Van Huyck, Battalio, and Beil (1990) payoff parameters (RM-VHBB)pp. 2372-2373; Result 3, p. 2373R-RM = 77.8% (MWU p = 0.173 vs RM); RM-VHBB = 82.2% (MWU p = 0.447 vs RM)
R4Reducing revision frequency (I-RM) or making revisions synchronous (S-RM) each reduces efficiency by 12-15 pppp. 2373-2374; Result 4, p. 2374I-RM = 69.6% (-12.5 pp, p < 0.001 MWU); S-RM = 67.1% (-15 pp, p < 0.001 MWU)
R5Removing commitment (R-CT) reduces efficiency by 15 pp to cheap-talk levelsp. 2374; Result 5, p. 2374R-CT = 67.2% vs RM = 82.1%, p < 0.001 MWU
R6Early revisions are forward-thinking; late revisions are myopic payoff-improvingFigure 3, p. 2375; Result 6, p. 2376First 10 s: 91.6% forward-thinking, 2.9% myopic-down; last 10 s: 12.5% forward-thinking, 84.4% myopic-down
R7Groups converging to a common effort profile implement it significantly more often under commitmentpp. 2376-2377; Result 7, p. 237787.6% follow-through in RM vs 51.1% in R-CT when a common profile is reached
R8Substantial gap between final pre-play message and implemented effort in R-CT causes 10.7% payoff lossp. 2377; Result 8, p. 2377Payoff at 60th-second message = 10.18; payoff-relevant choice = 9.19; p < 0.001 (MWU) for min effort and freq efficient effort
R9Richer normative cheap-talk messages (R-R-CT) do not improve efficiency over simple cheap talk (R-CT)p. 2378; Result 9, p. 2378R-R-CT = 68.2% vs R-CT = 67.2%; MWU p >= 0.385

Overall (paper’s conclusion). The three key ingredients of the revision mechanism (commitment, asynchronicity, and frequent revisions) are all necessary to achieve 82 percent efficiency. Removing any one reduces efficiency to the level of standard cheap talk. The paper’s summary efficiency ordering is (equation (4), p. 2378):

RM>S-CTR-CTI-RMS-RM>Baseline.(4)\text{RM} > \text{S-CT} \approx \text{R-CT} \approx \text{I-RM} \approx \text{S-RM} > \text{Baseline}. \tag{4}

The stage game is a normal-form game (I,(E)iI,(πi)iI)(I, (E)_{i \in I}, (\pi_i)_{i \in I}), where I={1,,n}I = \{1, \ldots, n\}, EE is a finite effort set common to all players, and πi(e)\pi_i(\mathbf{e}) is the payoff to player ii for profile eEn\mathbf{e} \in E^n (p. 2360). The highest effort is eˉ\bar{e}, the lowest e\underline{e}. In the minimum-effort game (equation (1), p. 2360):

πi(e)=γ+αminjIejβei,(1)\pi_i(\mathbf{e}) = \gamma + \alpha \cdot \min_{j \in I} e_j - \beta \cdot e_i, \tag{1}

where α>β>0\alpha > \beta > 0. Laboratory parameters: γ=0.18\gamma = 0.18, α=0.20\alpha = 0.20, β=0.04\beta = 0.04, E={1,2,3,4,5,6,7}E = \{1, 2, 3, 4, 5, 6, 7\}, groups of n=6n = 6. Every profile where all players choose the same effort ee^* is a strict Nash equilibrium, Pareto-ranked by effort level. The efficient profile eˉ=(7,,7)\bar{e} = (7,\ldots,7) is uniquely Pareto dominant, yet laboratory groups routinely play far below it (Baseline efficiency: 48%).

K-coordination games. Following Calcagno et al. (2014) (Definition 1, p. 2361), a component game is a KK-coordination game if for any pair of players i,jIi, j \in I and any profile e\mathbf{e}:

πj(eˉ)πi(e)πi(eˉ)πi(e)Kπj(eˉ)πj(e)πj(eˉ)πj(e).(2)\frac{\pi_j(\bar{e}) - \pi_i(\mathbf{e})}{\pi_i(\bar{e}) - \pi_i(\underline{e})} \leq K \frac{\pi_j(\bar{e}) - \pi_j(\mathbf{e})}{\pi_j(\bar{e}) - \pi_j(\underline{e})}. \tag{2}

The constant KK measures payoff similarity: K=1K = 1 is pure coordination. For the minimum-effort game, condition (2) reduces to α/(αβ)K\alpha / (\alpha - \beta) \leq K. At the laboratory parameters, K=0.20/(0.200.04)=1.25K = 0.20/(0.20 - 0.04) = 1.25.

The asynchronous revision game. The pre-play phase uses discrete time t{T,,1,0}t \in \{-T, \ldots, -1, 0\}. At t=Tt = -T, an initial effort profile is set simultaneously. During t<0t < 0, at each instant a revision opportunity arrives for the group with probability p(0,1]p \in (0,1]; if it arrives, it is allocated to one of the nn players with equal probability. At t=0t = 0 (the deadline), the most recently posted efforts are implemented. All past events are publicly observable, so the natural solution concept is subgame perfect equilibrium, called a revision equilibrium (p. 2362).

Main theoretical result (Proposition 1, p. 2362). In a discrete-time asynchronous revision game with symmetric arrival rate, if the component game is a KK-coordination game with strict Pareto-dominant profile eˉ\bar{e} and the condition

(n2)K<(n1)(n-2)K < (n-1)

holds, then for any ε>0\varepsilon > 0 there exists T>0T' > 0 such that for all T>TT > T', all revision equilibria have e(0)=eˉ\mathbf{e}(0) = \bar{e} with probability at least 1ε1 - \varepsilon.

The proof proceeds by induction (following Calcagno et al. (2014), online Appendix A): (i) eˉ\bar{e} is absorbing once reached; (ii) far enough from the deadline it is optimal to revise up to eˉ\bar{e} regardless of others’ current choices, since the cost of being alone at eˉ\bar{e} temporarily is small when the deadline is far. The condition (n2)K<(n1)(n-2)K < (n-1) ensures the induction goes through in finite time. At the laboratory parameters, the condition is satisfied ((62)(1.25)=5=61(6-2)(1.25) = 5 = 6-1, boundary case), and backward induction in online Appendix B confirms that the unique revision equilibrium prescribes choosing effort 7 from the start. The paper extends the Calcagno et al. (2014) theory from continuous to discrete time and derives two additional numerical insights: if players can choose effort before the pre-play phase, all should choose 7 from the outset; and far from the deadline, revising to eˉ\bar{e} is dominant regardless of the current profile.

Sessions ran at the Center for Experimental Social Science (CESS) at New York University (NYU) and the Interdisciplinary Experimental Laboratory (IELAB) at Indiana University (IU), using z-Tree (Fischbacher 2007), from December 2015 through April 2021 (p. 2365). Participants are randomly assigned to groups of six; each session consists of 10 rounds of the minimum-effort game.

Revision mechanism (RM) treatment. Each round starts with all six group members simultaneously choosing an integer in E={1,,7}E = \{1,\ldots,7\}. A 60-second countdown then begins. A real-time graph displays each player’s currently posted effort, visible to all. At each second a revision opportunity arrives for the group with probability 0.8; if it arrives, it is allocated to one member uniformly at random (probability 1/61/6). A player can change their cursor selection at any time, but the posted graph value updates only upon receiving a revision opportunity. At t=0t = 0 only the posted choice matters for payoffs. Each player expects approximately eight revision opportunities per round (p. 2367).

Nine treatments (Table 1, p. 2369):

TreatmentCommunicationCommitmentSubjectsGroups
BaselineNoneN/A488
Standard cheap talk (S-CT)One-shot messageNone488
Revision mechanism (RM)RevisionsGradual9616
Random revision (R-RM)RevisionsGradual488
RM-VHBBRevisionsGradual488
Infrequent RM (I-RM)RevisionsAbrupt488
Synchronous RM (S-RM)RevisionsGradual488
Revision cheap talk (R-CT)RevisionsNone9616
Richer R-CT (R-R-CT)RevisionsNone488

S-CT follows Blume and Ortmann (2007): before the effort choice, subjects simultaneously send a public number message; subjects then see all messages for 60 seconds before making their payoff-relevant effort. R-CT follows the RM protocol for the pre-play graph but, unlike RM, the choice at the end of the countdown is not payoff-relevant; subjects choose payoffs on a separate screen after. RM-VHBB uses Van Huyck, Battalio, and Beil (1990) payoff parameters (α=0.2\alpha = 0.2, β=0.1\beta = 0.1, γ=0.6\gamma = 0.6). I-RM reduces the group revision probability from 0.8 to 0.1. S-RM makes all revisions synchronous (all six group members receive the revision simultaneously at each opportunity). R-RM has initial effort choices assigned randomly from EE.

Efficiency measure (equation (3), p. 2369):

Efficiency=ActualMinMaxMin,(3)\text{Efficiency} = \frac{\text{Actual} - \text{Min}}{\text{Max} - \text{Min}}, \tag{3}

where Actual is the average amount earned, and Min (Max) is the average minimum (maximum) possible earnings. Normalization enables comparison across payoff specifications.

Main treatment comparisons (R1, R4-R5, R8-R9). The primary test is a two-sample Mann-Whitney U (MWU) test with the group’s round average as the unit of observation (one group = one independent observation, since standard errors are clustered at the group level). Treatment sizes range from 8 groups (80 group-round observations) to 16 groups (160 group-round observations). Five outcome variables are compared: (i) subject payoffs, (ii) minimum effort of the group, (iii) frequency of efficient effort choice (fraction of group members choosing 7), (iv) fraction of fully coordinated groups (all six members choose the same effort), and (v) equilibrium deviation (average distance between a subject’s effort and the group minimum).

OLS regression (R1 core, Table 2 p. 2372). Payoffs and the four group-level coordination measures are regressed on treatment dummies (baseline = S-CT treatment) and demographic controls, with standard errors clustered at the group level:

yig=β0+β11[Baseline]g+β21[RM]g+Xigγ+εig,y_{ig} = \beta_0 + \beta_1 \cdot \mathbf{1}[\text{Baseline}]_g + \beta_2 \cdot \mathbf{1}[\text{RM}]_g + \mathbf{X}_{ig}' \gamma + \varepsilon_{ig},

where yigy_{ig} is the outcome for subject ii in group gg, X\mathbf{X} includes quiz score and demographics, and errors are clustered by group. The RM coefficient β^2=0.21\hat{\beta}_2 = 0.21 (SE = 0.012) in the payoffs regression confirms significantly higher payoffs in RM relative to S-CT (Table 2, p. 2372).

Exact theoretical predictions (R2). The fraction of subjects initially choosing effort 7 is tested against 100 percent using the group average as unit. Average initial choice of 7 is 85.7 percent (93.8% in round 10); both are significantly below 100 percent (p < 0.01). RM efficiency of 82.1 percent is similarly tested against 100 percent.

Dynamic behavior classification (R6). Using the R-RM treatment (which introduces initial choice variation), each revision move is classified as: forward-thinking (increases effort even though this would decrease payoff if the game ended immediately, because it initiates a chain reaction when there is enough time); myopic-down (decreases effort toward the group minimum, payoff-improving if the game ended immediately); or other. The proportion of each type is plotted by 10-second interval across the 60-second pre-play phase (Figure 3, p. 2375).

Communication credibility (R7). All rounds in which a group converges to a homogeneous message profile during the 60-second pre-play are identified. The fraction of such rounds in which the communicated effort profile is also the payoff-relevant outcome (at t=0t = 0 for RM, at the separate payoff screen for R-CT) is then compared between RM and R-CT. The 87.6% vs 51.1% gap quantifies the credibility gain from commitment (pp. 2376-2377).

DatasetRole in paperWiki page
Original laboratory data (CESS/NYU and IELAB/Indiana University, 2015-2021)Primary experimental observations: effort choices, revision timing, group-level coordination outcomes across 9 treatmentsno page yet

Sample: 528 subjects across 9 treatments, 6 per group, 10 rounds each; 88 groups total.

Read the original if you are: designing or studying pre-play communication institutions in coordination games; testing or extending the Calcagno et al. (2014) theoretical framework to new environments; building laboratory experiments for the minimum-effort game (the online Appendix provides full instructions, backward induction numerical solutions, and complete robustness tables); studying the separate roles of commitment, asynchronicity, and revision frequency in coordination; or comparing against richer real-time communication benchmarks as in Deck and Nikiforakis (2012). The replication data are at the ICPSR archive (https://doi.org/10.3886/E185662V1).

Source: peer-reviewed, American Economic Review 113(9), September 2023, pp. 2355-2381. Copyright American Economic Association 2023. No CC license; redistribution is extract-only. This distillation was extracted by an LLM on 2026-06-24 and is not human-verified or independently reproduced.

Avoyan, Ala, and João Ramos. “A Road to Efficiency through Communication and Commitment.” American Economic Review 113, no. 9 (September 2023): 2355-2381. DOI: 10.1257/aer.20171014.

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