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A new uniform expansion is introduced for sums of weighted kernel-based regression residu-als from nonparametric or semiparametric models. This result is useful for deriving asymptotic properties of semiparametric estimators and test statistics with data-dependent bandwidth, random trimming, and estimated weights. An extension allows for generated(More)
Let r (x, z) be a function that, along with its derivatives, can be consistently estimated nonpara-metrically. This paper discusses identification and consistent estimation of the unknown functions is strictly mono-tonic. An estimation algorithm is proposed for each of the model's unknown components when r (x, z) represents a conditional mean function. The(More)
The paper introduces a √ n–consistent estimator of the probability density function of the response variable in a nonparametric regression model. The proposed estimator is shown to have a (uniform) asymptotic normal distribution, and it is computationally very simple to compute. A Monte Carlo experiment confirms our theoretical results, and an empirical(More)
Let H 0 (X) be a function that can be nonparametrically estimated. Suppose E [Y |X] = F 0 [X ⊤ β 0 , H 0 (X)]. Many models fit this framework, including latent index models with an endogenous regres-sor, and nonlinear models with sample selection. We show that the vector β 0 and unknown function F 0 are generally point identified without exclusion(More)
A numerical approximation of the critical values of Cramér-von Mises (CvM) tests is proposed for testing the correct specification of general conditional location parametric functionals. These specifications include conditional mean and quantile models. The method is based on the estimation of the eigenelements of the covariance operator associated with the(More)
A new way of constructing efficient semiparametric instrumental variable estimators is proposed. The method involves the combination of a large number of possibly inefficient estimators rather than combining the instruments into an optimal instrument function. The consistency and asymptotic normality is established for a class of estimators that are linear(More)
For most students, freshmen-level introductory economic courses represent their first exposure to the science of economics and its powerful tools of reasoning. These tools are the greatest benefits afforded to students who gain at least a principle level understanding of economics. However, here is the problem: for most universities and colleges, students(More)
We propose a functional principal components method that accounts for stratified random sample weighting to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK). We apply the method to publicly available monthly data on individual-good prices collected in retail stores by the UK Office for National(More)
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