We establish the consistency and asymptotic normality for a class of estimators that are linear combinations of a set of √n– consistent estimators whose cardinality increases with sample size. A special case of our framework corresponds to the conditional moment restriction and the implied...

In this paper the interest is in testing whether a regression function is polynomial of a certain degree. One possible approach to this testing problem is to do a parametric polynomial fit and a nonparametric fit and to reject the null hypothesis of a polynomial function if the distance between...

This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in which unknown coefficients are permitted to be nonparametric functions of some contextual variables to allow for potential nonlinearities and parameter heterogeneity in the spatial relationship....

Rating variables indicate the extent to which a quality is present, or absent, in a unit of observation. In this paper, we discuss a class of non-linear regression models for rating dependent variables and their estimation by parametric and semi-parametric methods. An application to life...

This article proposes a new class of rating scale models, which merges advantages and overcomes shortcomings of the traditional linear and ordered latent regression models. Both parametric and semi-parametric estimation is considered. The insights of an empirical application to satisfaction data...

This paper compares a nonparametric generalized least squares (NPGLS) estimator to parametric feasible GLS (FGLS) and variants of heteroscedasticity robust standard error estimators (HRSEs) in an applied setting. Given myriad alternative HRSEs, a clear consensus on which version to use does not...

Let (X,Y) be a pair of random variables with supp(X) \subseteq [0,1]?I and EY?2 \infinity. Let m* be the best approximation of the regression function of (X,Y) by sums of functions of at most d variables (formula). Estimation of m* from i.i.d. data is considered. For the estimation interaction...

We develop a new test of a parametric model of a conditional mean function against a nonparametric alternative. The test adapts to the unknown smoothness of the alternative model and is uniformly consistent against alternatives whose distance from the parametric model converges to zero at the...

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for possibly discrete or mixed discrete-continuous random variables. The construction is generic and does not depend on the nature of the underlying problem. It works in conjunction...

We provide an overidentification test for a nonparametric treatment model where individuals are allowed to select into treatment based on unobserved gains. Our test can be used to test the validity of instruments in a framework with essential heterogeneity (Imbens and Angrist 1994). The...