The paper analyses the potential impact of stock market developments on lending behaviour from different perspectives. First we scrutinize the impact of stock market movements on the banks’ and on the borrowers’ balance sheets. Subsequently we estimate aggregate credit supply and demand...

In many econometric applications it is unclear from the very beginning whether a parametric functional of a continuous regressor should be specified as a linear, as a higher order polynomial or as a piecewise linear. Nonparametric estimators can provide relevant information as they are a...

We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator...

Consumption based equivalence scales are estimated by applying the extended partially linear model (EPLM) to the 1998 Income and Consumption Survey (EVS) carried out in Germany. In this model the equivalence scales are identified by virtue of nonlinearities in household demand. Therefore, the...

This paper considers the shape invariant modelling approach in semiparametric regression estimation. Nonparametric functions of similar shape are linked by parametric transformations with unknown parameters. A computationally convenient estimation procedure is suggested. √N- consistency of the...

In this paper we derive nonparametric bounds for the cumulative incidence curve within a competing risks model with partly identified interval data. As an advantage over earlier attempts our approach also gives valid results in case of dependent competing risks. We apply our framework to...

In this paper we derive nonparametric bounds for the cumulative incidence curve within a competing risks model with partly identified interval data. As an advantage over earlier attempts our approach also gives valid results in case of dependent competing risks. We apply our framework to...