Stephanie W. Wang

Curriculum Vitae [PDF]

Research interests

  • Experimental Economics; Behavioral Economics/Game Theory; Information Economics

  • Stephanie W. Wang


  • Speculative Overpricing in Asset Markets with Information Flows (with Thomas R. Palfrey) [PDF]
    Econometrica, in press

  • Shared Visual Attention Reduces Hindsight Bias (with Daw-An Wu, Shin Shimojo, and Colin Camerer)
    Psychological Science, in press

  • Belief Updating in Sequential Games of Two-Sided Incomplete Information: An Experimental Study of a Crisis Bargaining Model (with Dustin H. Tingley) [PDF] [Supplementary Materials]
    Quarterly Journal of Political Science, 5(3), 243-255 (2010)

  • Incentive Effects: The Case of Belief Elicitation from Individuals in Groups [PDF]
    Economic Letters, 111, 30-33 (2011)

  • Does Recession Reduce Global Health Aid? Evidence from 15 High-Income Countries, 1970-2007 (With David Stuckler, Sanjay Basu, and Martin McKee)
    Bulletin of the World Health Organization, 89(4), 252-257 (2011)

  • On Eliciting Beliefs in Strategic Games (with Thomas R. Palfrey) [PDF]
    Journal of Economic Behavior and Organization, 71, 98-109 (2009)

  • What Kind of Memory Supports Visual Marking? (With Yuhong Jiang) [PDF]
    Journal of Experimental Psychology: Human Perception & Performance, 30(1), 79-91 (2004)

  • Working papers

    Imperfect Choice or Imperfect Attention? Understanding Strategic Thinking in Private Information Games (with Isabelle Brocas, Juan D. Carrillo, and Colin F. Camerer) [PDF]
    Revised and Resubmitted, Review of Economic Studies


    In experiments, people do not always appear to infer the information of other players from their choices. To understand this thinking process further, we use "Mousetracking" to record which game payoffs subjects look at, and for how long, in games of private information with three information states, which vary in strategic complexity. Subjects often deviate from Nash equilibrium choices, converge only modestly toward equilibrium across 40 trials, and often fail to look at payoffs which they need to in order to compute an equilibrium response. When cluster analysis is used to group subjects according to lookup patterns and choices, the clusters appear to correspond approximately to level-3, level-2 and level-1 thinking in level-k cognitive hierarchy models. Deviations from Nash play are associated with failure to look at the necessary payoffs. The connection between looking and choices is strong enough that the time durations of looking at key payoffs can predict choices, to some extent, at the individual level and at the trial-by-trial level.

    Dynamically Optimized Sequential Experimentation (DOSE) for Estimating Economic Preference Parameters (First author, with Colin F. Camerer and Michelle Filiba) [PDF]
    Revise and Resubmit, American Economic Review


    Dynamically optimized sequential experiments (DOSEs) for estimation of risk preferences start with a distribution of beliefs about risk preference parameters, and a set of questions, then dynamically choose the question that maximizes information gain considering previous answers. Applying the method to the 10-question set of Holt and Laury (2002) and the 140-question set of Sokol-Hessner et al. (2009) to measure risk-aversion and loss-aversion shows that DOSE sequences create a 50-70% increase in speed of inference about parameter from fewer questions. Simple DOSE designs could be useful in complex environments with highly-distractible groups like internet groups, children, CEOs and monkeys.

    Patience Auctions: The Impact of Time vs. Money Bidding on Elicited Discount Rates (with Christopher Y. Olivola) [PDF]

    Prediction in Networks

    Visual Eavesdropping: Shifting Attention and Changing Expressed Social Preferences (First author, with Colin F. Camerer)

    Not All Nudges are Created Equal: Moral Sentiments and Contribution to Public Goods (with Margaret A. McConnell)