A time-varying quantile can be fitted to a sequence of observations by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. It is shown that such time-varying quantiles satisfy the defining...

This paper investigates features of credit risk using non-parametric techniques, studying determinants of risk premia using a non-parametric term-structure model of the corporate spread. The model, which measures the extra return of defaultable corporate bonds on their government counterparts,...

A time-varying quantile can be fitted to a sequence of observations by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. It is shown that such time-varying quantiles satisfy the defining...

The intention is to provide a Bayesian formulation of regularized local linear regression, combined with techniques for optimal bandwidth selection. This approach arises from the idea that only those covariates that are found to be relevant for the regression function should be considered by the...

It is generally agreed that respiratory disease is closely related to ambient air quality and weather conditions. Besides, hygiene related factors such as the public health measures by the government and possible personal awareness in the community can also affect the spread of infectious...

The paper considers the problem of estimating the parameters in a continuous time regression model with a non-Gaussian noise of pulse type. The vector of unknown parameters is assumed to belong to a compact set. The noise is specified by the Ornstein–Uhlenbeck process driven by the mixture of...

We simulate the impact of food inflation between June 2006 and June 2008 on poverty across different areas and between agricultural and non-agricultural households. We explicitly treat the spatial heterogeneity in food inflation and the differences in consumption and production patterns across...

We consider the estimation of nonparametric regression models with the explanatory variable being measured with Berkson errors or with a mixture of Berkson and classical errors. By constructing a compact operator, the regression function is the solution of an ill-posed inverse problem, and we...