We analyze identification of nonseparable models under three kinds of exogeneity assumptions weaker than full …

unobserved variables allows identification analysis under mean and quantile independence restrictions on the distributions of …

. We use tools from random set theory to study identification in such models and provide a sharp characterization of the …

. We use tools from random set theory to study identification in such models and provide a sharp characterisation of the …

random sets defined on the space of unobserved variables. This allows identification analysis under mean and quantile …

identification results and to fast, easy to implement, and tuning-free estimators that do not require the availability of high …

average counterfactual outcomes are bounded under different treatments. We obtain a set of new partial identification results … the existing literature using our identification results and illustrate its usefulness by applying one of our … identification results to the Job Corps Study dataset. Our empirical results show that there is strong evidence of the gender and …

regression. Some examples illustrate the wide applicability and utility of our identification result, including bounds and a new … identification condition for point-evaluation functionals. The main ideas are illustrated with an empirical application of the effect …