decision model, (b) moving from the decision model to a moment inequality model, (c) choosing a test statistic and critical … "why", and then illustrate how to take these steps to practice in an empirical application that studies identification of …

We generalize the seminal Gibbons-Ross-Shanken test to the empirically relevant case where the number of test assets … far exceeds the number of observations. In such a setting, one needs to use a regularized estimator of the covariance … matrix of test assets, which leads to biases in the original test statistic. Random Matrix Theory allows us to account for …

future outcomes that accounts for strategic misreporting. Misreporting may invalidate existing point-identification …

We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp … judge leniency design assumptions. The proposed sharp test is asymptotically valid and consistent and will not make …) estimand can recover the Marginal Treatment Effect. Simulation studies show our test outperforms existing non-sharp tests by …

effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters … additively and interacts with treatment variables. We present identification and estimation methods for parameters of interest in … this model under both strict and weak exogeneity assumptions. The key identification insight is that other periods …