Parameter shrinkage applied optimally can always reduce error and projection variances from those of maximum likelihood estimation. Many variables that actuaries use are on numerical scales, like age or year, which require parameters at each point. Rather than shrinking these towards zero,...

The paper gives an overview on generalized linear models and its application in different branches of science. We introduce semiparametric extensions of the generalized linear model. One particular model of interest is the generalized partially linear model which allows a nonparametric modeling...

In this paper, I study identification of a nonseparable model with endogeneity arising due to unobserved heterogeneity. Identification relies on the availability of binary proxies that can be used to control for the unobserved heterogeneity. I show that the model is identified in the limit as...

High-frequency data can provide us with a quantity of informa- tion for forecasting, help to calculate and prevent the future risk based on extremes. This tail behaviour is very often driven by ex- ogenous components and may be modelled conditional on other vari- ables. However, many of these...

Mortality is different across countries, states and regions. Several empirical research works however reveal that mortality trends exhibit a common pattern and show similar structures across populations. The key element in analyzing mortality rate is a time-varying indicator curve. Our main...

Based on the Lee-Carter (LC) model, the benchmark in population forecasting, a variety of extensions and modifications are proposed in this paper. We investigate one of the extensions, the Hyndman-Ullah (HU) method and apply it to Asian demographic data sets: China, Japan and Taiwan. It combines...

In this paper, we consider a class of time-varying panel data models with individual-specific regression coefficients and common factors where both the serial correlation and cross-sectional dependence among error terms can be present. Based on an initial estimator of factors, we propose a...

Demonstration of nonlinear nonparametric regression technique using R-package "NNS" and comparison to kernel based regression methods in goodness of fit, partial derivative estimation, and out-of-sample extrapolation

Mortality is different across countries, states and regions. Several empirical research works however reveal that mortality trends exhibit a common pattern and show similar structures across populations. The key element in analyzing mortality rate is a time-varying indicator curve. Our main...

High-frequency data can provide us with a quantity of information for forecasting, help to calculate and prevent the future risk based on extremes. This tail behaviour is very often driven by exogenous components and may be modelled conditional on other variables. However, many of these...