To evaluate how well economic models predict behavior it is important to have a measure of how well any theory could be expected to perform. We provide a measure of the amount of predictable variation in the data that a theory captures, which we call its "completeness." We evaluate the...

We propose a new way to quantify the restrictiveness of an economic model, based on how well the model fits simulated, hypothetical data sets. The data sets are drawn at random from a distribution that satisfies some application-dependent content restrictions (such as that people prefer more...

We use machine learning to uncover regularities in the initial play of matrix games. We first train a prediction algorithm on data from past experiments. Examining the games where our algorithm predicts correctly, but existing economic models don't, leads us to add a parameter to the best...

Economists often estimate models using data from a particular setting, e.g. estimating risk preferences in a specific subject pool. Whether a model’s predictions extrapolate well across settings depends on whether the estimated model has captured generalizable structure. We provide a tractable...