We introduce test statistics based on generalized empirical likelihood methods that can be used to test simple … hypotheses involving the unknown parameter vector in moment condition time series models. The test statistics generalize those in … the strength or weakness of identification. More precisely, we show that the statistics are asymptotically distributed as …

many moment inequalities. Building on results from the literature on multivariate one-sided tests, I show how to test the … test statistic has an asymptotic chi-bar-square distribution, and can be inverted to construct an asymptotic confidence set …

identification of parameters of interest in this context. Calculations of asymptotic local power and Monte Carlo evidence indicate …

the true value that are sufficient for local identification. These results are applied to obtain new, primitive … identification conditions in several important models, including nonseparable quantile instrumental variable (IV) models, single …

In this paper we consider the problem of inference on a class of sets describing a collection of admissible models as … inference procedures are also more powerful than the structured projection methods, which rely upon building confidence sets for …

embeds a specification test for nonemptiness of the identified set. A methodological contribution is to notice that the … difficulty of inference comes from a boundary problem regarding a nuisance parameter, clarifying the connection to other work on … partial identification. …

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

applicable, but it usually delivers set identification. Nonetheless it can be used to consistently estimate bounds on many …