We propose a semi-structural discrete-choice model that can be used to estimate static or dynamic decision rules. It is particularly useful in strategic contexts when games involve a rich set of choices, when private information is correlated, and when one wants to uncover the effect of historic behavior (on, for example, prices, sales, and profits). We apply our discrete-choice estimator to study decision rules for a dynamic game of price and advertising competition, and we evaluate the long-run consequences of those rules.
