Lee (2003) develops a √ n-consistent estimator of the parametric component of a partially linear quantile regression model, which is used to obtain his one-step semiparametric efficient estimator. As a result, how well the efficient estimator performs depends on the quality of the initial √ n-consistent estimator. In this paper, we aim to improve the small sample performance of the one-step eff...

We consider functional measurement error models where the measurement error distribution is estimated non-parametrically.We derive a locally efficient semiparametric estimator but propose not to implement it owing to its numerical complexity. Instead, a plug-in estimator is proposed, where the measurement error distribution is estimated through non-parametric kernel methods based on multiple me...

This paper addresses the problem of nonparametric estimation of the conditional expected shortfall (CES) which has gained popularity in financial risk management. We propose a new nonparametric estimator of the CES. The proposed estimator is defined as a conditional counterpart of the sample average estimator of the unconditional expected shortfall, where the empirical distribution function is ...

In two-phase sampling, the second-phase sample is often a stratified sample based on the information observed in the first-phase sample. For the total of a population characteristic, either the double-expansion estimator or the reweighted expansion estimator can be used. Given a consistent first-phase replication variance estimator, we propose a consistent variance estimator that is applicable ...

This paper compares the finite sample performance of the canonical correlation regression estimator (CCR) and Stock and Watson's (A simple estimator of cointegration vectors in higher order integrated systems, Econometrica, 1993, 61(4), 783-820) dynamic ordinary least squares estimator (DOLS) using the models proposed by Inder (Journal of Econometrics, 1993, 57, 53-68). The CCR estimator shows ...