Project Abstract Project Abstract: This doctoral dissertation research is conducted by Nicole Bouchez under the supervision of Daniel Friedman. The economy is full of businesses buying and selling goods and services, but how do they know about their rivals' incentives? Little is known about how groups of people or businesses learn about each other's incentives when they are not directly observable. Several competing theoretical models have been suggested that show learning through economic interactions, however few empirical comparisons of these models have been made. This project conducts a series of computerized laboratory experiments to investigate group learning in three-choice bimatrix games. The bimatrix games allow players to see their own options and contingent payoffs, but do not allow them to see their opponents' payoffs. This structure is broadly applicable and is a key step towards general, multiple choice, strategic interactions. The data collected are used to compare how well the different models of learning predict individual actions.
