An asymptotic theory is developed for a weakly identified cointegrating regression model in which the regressor is a nonlinear transformation of an integrated process. Weak identification arises from the presence of a loading coefficient for the nonlinear function that may be close to zero. In...

In this paper, we derive a rate of convergence of the Lasso estimator when the penalty parameter Lambda for the estimator is chosen using K-fold cross-validation; in particular, we show that in the model with Gaussian noise and under fairly general assumptions on the candidate set of values of...

Correct specification of a conditional quantile model implies that a particular conditional moment is equal to zero. We nonparametrically estimate the conditional moment function via series regression and test whether it is identically zero using uniform functional inference. Our approach is...

Errors-in-variables (EIV) biases plague asset pricing tests. We offer a new perspective on ad-dressing the EIV issue: instead of viewing EIV biases as estimation errors that potentiallycontaminate next-stage risk premium estimates, we consider them to be return innovationsthat follow a...