no code implementations • 10 Feb 2022 • Isaiah Andrews, Drew Fudenberg, Lihua Lei, Annie Liang, Chaofeng Wu
Economists often estimate models using data from a particular domain, e. g. estimating risk preferences in a particular subject pool or for a specific class of lotteries.
no code implementations • 3 Jan 2022 • Daniel Clark, Drew Fudenberg, Kevin He
Learning models do not in general imply that weakly dominated strategies are irrelevant or justify the related concept of "forward induction," because rational agents may use dominated strategies as experiments to learn how opponents play, and may not have enough data to rule out a strategy that opponents never use.
no code implementations • 13 Nov 2020 • Drew Fudenberg, Ying Gao, Harry Pei
We analyze situations in which players build reputations for honesty rather than for playing particular actions.
no code implementations • 17 Jul 2020 • Drew Fudenberg, Wayne Gao, Annie Liang
We propose a restrictiveness measure for economic models based on how well they fit synthetic data from a pre-defined class.
no code implementations • 15 Oct 2019 • Drew Fudenberg, Jon Kleinberg, Annie Liang, Sendhil Mullainathan
We use machine learning to provide a tractable measure of the amount of predictable variation in the data that a theory captures, which we call its "completeness."