We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series availableat time t − 1. We discuss sieve estimates which are a nonparametric versions ofthe Koenker-Bassett regression quantiles and do not...

We present in this paper the asymptotic properties of two-stage quantile regressionestimators. These results permit valid inferences in structural models estimated using quantileregressions, in which the possible endogeneity of some explanatory variables is treated viaancilliary predictive...

For both deterministic or stochastic regressors, as well as parametric nonlinear or linear regression functions, we prove the weak consistency of the coefficient estimators for the Type I censored quantile regression model under different censoring mechanisms with censoring points depending on...

This paper derives the asymptotic normality of the nonlinear quantile regression estimator with dependent errors. The required assumptions are weak, and it is neither assumed that the error process is stationary nor that it is mixing. In fact, the notion of weak dependence introduced in this...

Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the functional relationship and of the error...

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...