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Evaluating non-clairvoyant dynamic mechanisms: Theory and experiment

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  • Gui, Shan
  • Houser, Daniel

Abstract

We study dynamic mechanism design in non-clairvoyant environments, where sellers cannot forecast future demand and buyers hold private information. Using two laboratory experiments, we evaluate two non-clairvoyant mechanisms: the dynamic maximin-optimal non-clairvoyant mechanism (DM, Mirrokni et al., 2020) and the repeated static optimal mechanism (RS, Myerson, 1981). Experiment 1 compares DM and RS between demand-distribution scenarios and shows that non-clairvoyant mechanisms perform as intended: DM either outperforms or underperforms RS depending on the scenario, consistent with theory. Building on these results, Experiment 2 examines the optimal clairvoyant mechanism (OC) and a different implementation of DM. In surprising contrast to theory, OC using full information performs no better than the non-clairvoyant mechanisms, while DM performs equally well across implementation forms. Our results highlight the practical importance of non-clairvoyant mechanisms as implementable approaches to dynamic auction design in uncertain markets.

Suggested Citation

  • Gui, Shan & Houser, Daniel, 2026. "Evaluating non-clairvoyant dynamic mechanisms: Theory and experiment," Games and Economic Behavior, Elsevier, vol. 158(C), pages 1-34.
    • Handle: RePEc:eee:gamebe:v:158:y:2026:i:c:p:1-34
    DOI: 10.1016/j.geb.2026.02.009
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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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