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...

This paper examines methods of inference concerning quantile treatment effects (QTEs) in randomized experiments with matched-pairs designs (MPDs). Standard multiplier bootstrap inference fails to capture the negative dependence of observations within each pair and is therefore conservative....

This paper proposes a novel method to select an experimental design for interpolation in random simulation. (Though the paper focuses on Kriging, this method may also apply to other types of metamodels such as linear regression models). Assuming that simulation requires much computer time, it is...