This paper applies semiparametric regression models to shed light on the relation-ship between body weight and labor market outcomes in Germany. We find conclusive evidence that these relationships are poorly described by linear or quadratic OLS specifications, which have been the main...

This paper applies semiparametric regression models using penalized splines to investigate the profile of well-being over the life span. Splines have the advantage that they do not require a priori assumptions about the form of the curve. Using data from the British Household Panel Survey (BHPS)...

This paper applies semiparametric regression models using penalized splines to investigate the profile of well-being over the life span. Splines have the advantage that they do not require a priori assumptions about the form of the curve. Using data from the British Household Panel Survey (BHPS)...

In this paper, we consider a model selection issue in semiparametric panel data models with fixed effects. The modelling framework under investigation can accommodate both nonlinear deterministic trends and cross-sectional dependence. And we consider the so-called "large panels" where both the...

In this paper we obtain bounds under weaker nonparametric assumptions and explore how the bounds with assumptions imposed.

This paper applies semiparametric regression models using penalized splines to investigate the profile of well-being over the life span. Splines have the advantage that they do not require a priori assumptions about the form of the curve. Using data from the British Household Panel Survey (BHPS)...

This paper estimates the long-term trends in the daily maxima of tropospheric ozone at six sites around the state of Texas. The statistical methodology we use controls for the effects of meteorological variables because it is known that variables such as temperature, wind speed and humidity...

This paper presnets a method for simultaneously estimating a system of nonparametric multiple regressions which may seem unrelated, but where the errors are potentially correlated between equations. We show that the prime advantage of estimating such a 'seemingly unrelated' system of...

A new regression based approach is proposed for modeling marketing databases. The approach is Bayesian and provides a number of significant improvements over current methods. Independent variables can enter into the model in either a parametric or nonparametric manner, significant variables can...

A semiparametric fixed effects model is introduced to describe the nonlinear trending phenomenon in panel data analysis and it allows for the cross-sectional dependence in both the regressors and the residuals. A pooled semiparametric profile likelihood dummy variable approach based on the...