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...

We propose bootstrap implementations of the asymptotic Wald, likelihood ratio and Lagrange multiplier tests for the order of integration of a fractionally integrated time series. Our main purpose in doing so is to develop tests which are robust to both conditional and unconditional...

I derive a rigorous method to help determine whether a true parameter takes a value between two arbitrarily chosen points for a given level of confidence via a multiple testing procedure which strongly controls the familywise error rate. For any test size, the distance between the upper and...

This paper develops a specification test for the instrument validity conditions in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. A necessary testable implication for the joint restriction of instrument exogeneity and instrument monotonicity is given...

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...

In many economic applications, the variate of interest is non-negative and its distribution is characterized by a mass-point at zero and a long right-tail. Many regression strategies have been proposed to deal with data of this type. Although there has been a long debate in the literature on the...

Factor rotation is widely used to interpret the estimated factor loadings from latent variable models. Rotation methods embody a priori concepts of 'complexity' of factor structures, which they seek to minimise. Surprisingly, it is rare for researchers to exploit one of the most common and...

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that there are corresponding sufficient conditions for nonparametric models. A nonparametric rank...

Efficient computational algorithms for bootstrapping linear regression models with clustered data are discussed. For OLS regression, a new algorithm is provided for the pairs cluster bootstrap, and two algorithms for the wild cluster bootstrap are compared. One of these is a new way to express...