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...

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 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 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 the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted...

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...