Stuetzle and Mittal (1979) for ordinary nonparametric kernel regression and Kauermann and Tutz (1996) for nonparametric generalized linear model kernel regression constructed estimators with lower order bias than the usual estimators, without the need for devices such as second derivative...

A particular semiparametric model of interest is the generalized partial linear model (GPLM) which allows a nonparametric modeling of the influence of the continuous covariables. The paper reviews different estimation procedures based on kernel methods and test procedures on the correct...

The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between...

East-West migration in Germany peaked at the beginning of the 90s although the average wage gap between Eastern and Western Germany continues to average about 25%. We analyze the propensity to migrate using microdata from the German Socioeconomic Panel. Fitting a parametric Generalized Linear...