This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in Bugni...

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in Bugni...

This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isolated structural parameter points that are observationally equivalent under the imposed restrictions. Although the...

This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isolated structural parameter points that are observationally equivalent under the imposed restrictions. Although the...

In a landmark contribution to the structural vector autoregression (SVARs) literature, RubioRam'ırez, Waggoner, and Zha (2010, 'Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference,' Review of Economic Studies) shows a necessary and sufficient condition for...

This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment (in)equality model. As a special case, our method yields marginal confidence sets for individual coordinates of this parameter vector. Our inference method controls asymptotic size...

This paper studies the problem of specification testing in partially identified models defined by a finite number of moment equalities and inequalities (i.e., (in)equalities). Under the null hypothesis, there is at least one parameter value that simultaneously satisfies all of the moment...

In this paper we introduce a new approach to estimating a differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in...

This paper introduces a new hypothesis test for the null hypothesis H0 : f(Ø) = Y0, where f(.) is a known function, Y0 is a known constant, and Ø is a parameter that is partially identified by a moment (in)equality model. The main application of our test is sub-vector inference in moment...

This paper studies the problem of specification testing in partially identified models defined by a finite number of moment equalities and inequalities (i.e. (in)equalities). Under the null hypothesis, there is at least one parameter value that simultaneously satisfies all of the moment...