Conventional theory predicts that productivity gains lead to pay hikes. Pay increases, however, can influence labor productivity. But what about in a corporatist economy? Focusing on Germany, we use an innovative technique developed by Geweke to disentangle the relationship between pay and...

Positive assortative matching implies that high productivity workers and firms match together. However, there is almost no evidence of a positive correlation between the worker and firm contributions in two-way fixed-effects wage equations. This could be the result of a bias caused by standard...

Positive assortative matching implies that high productivity workers and firms match together. However, there is almost no evidence of a positive correlation between the worker and firm contributions in two-way fixed-effects wage equations. This could be the result of a bias caused by standard...

Conventional theory predicts that productivity gains lead to pay hikes. Pay increases, however, can influence labor productivity. But what about in a corporatist economy? Focusing on Germany, we use an innovative technique developed by Geweke to disentangle the relationship between pay and...

Business climate indicators are used to receive early signals for turning points in the general business cycle. Therefore methods for the detection of turning points in time series are required. Estimations of slopes of a smooth component in the data can be calculated with local polynomial...

Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...

This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a...

We consider two semiparametric models for the weight function in a bias sample model. The object of our interest parametrizes the weight function, and it is either Euclidean or non Euclidean. One of the models discussed in this paper is motivated by the estimation the mixing distribution of...

Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...