Cognitive hierarchy modelling of lab, field and neural data

Cognitive hierarchy and level-k models assume players use steps of reasoning iteratively. Precision comes from making (and testing) various assumptions about the step distribution, beliefs of players at each step, and responsiveness to expected payoff. I describe several empirical examples of these models applied to lab experiments and two field settings. In addition, eyetracking and some neural evidence are supportive of the concept of limits of iterated thinking and suggest some interesting research directions.