Two sided analysis of variance with a latent time series

Many real life regression problems exhibit some kind of calender time dependency and it is often of interest to predict the behavior of the regression function along this calender time direction. This can be formulated as a regression model with an added latent time series and the task is to be able to analyse this series. In this paper we engage this through a two step procedure, firstly we treat the time dependent elements as parameters and estimate them in the two-sided analysis of variance setup, secondly we use the estimated time series as predictor of the latent time series. An application to risk theory is discussed.regression, time series, risk theory

Nonparametric Regression with a Latent Time Series

In this paper we investigate a class of semiparametric models for panel datasetswhere the cross-section and time dimensions are large. Our model contains alatent time series that is to be estimated and perhaps forecasted along with anonparametric covariate effect. Our model is motivated by the need to be flexiblewith regard to functional form of covariate effects but also the need to be practicalwith regard to forecasting of time series effects. We propose estimation proceduresbased on local linear kernel smoothing; our estimators are all explicitly given. Weestablish the pointwise consistency and asymptotic normality of our estimators. Wealso show that the effects of estimating the latent time series can be ignored incertain cases.Kernel Estimation, Forecasting, Panel Data, Unit Roots

The vulnerability of beach tourism to climate change—an index approach

The attractiveness of a region for touristic activities depends strongly on the local weather and climate. This paper analyses the vulnerability of the beach tourism sector towards climate change by means of an index approach on a country level. A vulnerability framework for the tourism sector is developed and on its basis, indicators are defined for exposure, sensitivity and adaptive capacity. A transparent index approach, including a robustness analysis with multiple transformation methods and weighting sets, yields an assessment of the overall relative vulnerability of the beach tourism sector in 51 countries. Aggregate results on an annual level are presented as a starting point for a more detailed comparison of countries based on the individual indicators. The important limitations regarding the availability of accurate indicators as well as the concept of vulnerability itself are discussed. Despite these limitations, the present study contributes to integrating the numerous direct as well as indirect effects climate change may have on beach touris

Kernel Density Estimation of Actuarial Loss Functions.

No abstractLoss models; Transformation; Skewness; Weighted integrated squared error

Asymmetric information, self-selection and pricing of insurance contracts: the simple no-claims case

This paper presents an optional bonus-malus contract based on a pri-ori risk classification of the underlying insurance contract. By inducing self-selection, the purchase of the bonus-malus contract can be used as a screening device. This gives an even better pricing performance than both an experience rating scheme and a classical no-claims bonus system. An application to the Danish automobile insurance market is considered