This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and...

For a Lévy process X having finite variation on compact sets and finite first moments, u (dx) = xv (dx) is a finite signed measure which completely describes the jump dynamics. We construct kernel estimators for linear functionals of u and provide rates of convergence under regularity...

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 semiparametric methods. An application to life...

This paper proposes a powerful alternative to the t-test of the null hypothesis that a coefficient in linear regression is equal to zero when a regressor is mismeasured. We assume there are two contaminated measurements of the regressor of interest. We allow the two measurement errors to be...

The aim of this study is to analyse how research and innovation activities, funded by the Nanosciences and Nanotechnologies, Materials, New Production Technologies (NMP) and the Industrial Biotechnology (B) themes in the Seventh Framework Programme for Research (FP7) (together: FP7 NMBP), are...

We reconsider the efficiency bound for the semi-parametric Mixed Proportional Hazard (MPH) model with parametric baseline hazard and regression function. This bound was first derived by Hahn (1994). One of his results is that if the baseline hazard is Weibull, the efficiency bound is singular,...

Elbers and Ridder (1982) identify the Mixed Proportional Hazard model by assuming that the heterogeneity has finite mean. Under this assumption, the information matrix of the MPH model may be singular. Moreover, the finite mean assumption cannot be tested. This paper proposes a new...