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...

The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques. However, the objective function in stage two of the method may not exists. We...

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...

The Box-Cox quantile regression model using the two stage method introduced by Chamberlain (1994) and Buchinsky (1995) provides an attractive extension of linear quantile regression techniques. However, a major numerical problem exists when implementing this method which has not been addressed...

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...

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...

The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques. However, the objective function in stage two of the method may not exists. We...