【AEW webinar】Predictable Effects of Visual Salience in Experimental Decisions and Games & Temporal Instability of Risk Preference Among the Poor: Evidence from Payday Cycles

  • 研討會日期 : 2022-01-20
  • 時間 : 08:30
  • 主講人 : Professor Colin Camerer & Hitoshi Shigeoka
  • 地點 : Register and join online
  • 演講者簡介 : Professor Camerer received his Ph.D. in decision theory from University of Chicago in 1981. He is the Robert Kirby Professor of Behavioral Finance and Economics at the California Institute of Technology. His research fields are Social and Decision Neuroscience; Business, Economics and Management; Experimental Social Science. Professor Shigeoka received his Ph.D. in Economics from Columbia University in 2012. He is currently a Professor at University of Tokyo and an Associate Professor at Simon Fraser University (on leave). His research interests are Health, Labor, Public, and Behavioral Economics.
  • 演講摘要 : Bottom-up stimulus-driven visual salience is largely automatic, effortless, and independent of a person’s “top-down” perceptual goals; it depends only on features of a visual stimulus. Algorithms have been carefully trained to predict stimulus-driven salience values for each pixel in any image. The economic question we address is whether these salience values help explain economic decisions. Our first experimental analysis shows that when people pick be-tween sets of fruits that have artificially induced value, predicted salience (which is uncorrelated with value by design) leads to mistakes. Our second analysis uses evidence from games in which choices are locations in images. When players are trying to co-operatively match locations, predicted salience is highly correlated with the success of matching (r=.57). In competitive hider-seeker location games, players choose salient locations more often than predicted by the unique Nash equilibrium. This tendency creates a disequilibrium “seeker’s advantage” (seekers win more often than predicted in equilibrium). The result can be explained by level-k models in which predicted stimulus-driven salience influences level-0 choices and thereby influences overall perceptions, beliefs, and choices of higher-level players. The third analysis shows that there is an effect of visual salience in matrix games, but it is small and statistically weak. Applications to behavioral IO, price and tax salience, nudges and design, and visually-influenced beliefs are suggested.