This paper considers the problem of estimation and inference in semiparametric varying coefficients partially linear models when the response variable is subject to random censoring. The paper proposes an estimator based on combining inverse probability of censoring weighting and profile least...

The efficient bootstrap methodology is developed for overidentified moment conditions models with weakly dependent observation. The resulting bootstrap procedure is shown to be asymptotically valid and can be used to approximate the distributions of t-statistics, the J-statistic for...

This paper shows how the generalised empirical likelihood method can be used to obtain valid asymptotic inference for the finite dimensional component of semiparametric models defined by a set of moment conditions. The results of the paper are illustrated using three well-known semiparametric...

In this paper we use the empirical Cressie-Read discrepancy function to obtain a class of nonparametric likelihood statistics for smooth functions of means of [alpha]-mixing processes both in the finite- and infinite-dimensional case.

This article considers empirical likelihood in the context of efficient semiparametric estimators of average treatment effects. It shows that the empirical likelihood ratio converges to a nonstandard distribution, and proposes a corrected test statistic that is asymptotically chi-squared. A...