Non-Strategic Econometrics (for Initial Play)

Daniel Chui, Jason Hartline, James R. Wright

Research output: Contribution to journalConference articlepeer-review


Modelling agent preferences has applications in a range of fields including economics and increasingly, artificial intelligence. These preferences are not always known and thus may need to be estimated from observed behavior, in which case a model is required to map agent preferences to behavior, also known as structural estimation. Traditional models are based on the assumption that agents are perfectly rational: that is, they perfectly optimize and behave in accordance with their own interests. Work in the field of behavioral game theory has shown, however, that human agents often make decisions that are imperfectly rational, and the field has developed models that relax the perfect rationality assumption. We apply models developed for predicting behavior towards estimating preferences and show that they outperform both traditional and commonly used benchmark models on data collected from human subjects. In fact, Nash equilibrium and its relaxation, quantal response equilibrium (QRE), can induce an inaccurate estimate of agent preferences when compared against ground truth. A key finding is that modelling non-strategic behavior, conventionally considered uniform noise, is important for estimating preferences. To this end, we introduce quantal-linear4, a rich nonstrategic model. We also propose an augmentation to the popular quantal response equilibrium with a non-strategic component. We call this augmented model QRE+L0 and find an improvement in estimating values over the standard QRE. QRE+L0 allows for alternative models of non-strategic behavior in addition to quantal-linear4.

Original languageEnglish (US)
Pages (from-to)634-642
Number of pages9
JournalProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
StatePublished - 2023
Event22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023 - London, United Kingdom
Duration: May 29 2023Jun 2 2023


  • Behavioral Game Theory
  • Bounded Rationality
  • Econometrics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering


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