Showing 1 - 10 of 14
We develop a method to estimate and assess uncertainty in the total fertility rate over time. Our estimates are based on multiple imperfect observations from different data sources including surveys and censuses. We take account of measurement error by decomposing it into bias and variance and...
Persistent link: https://www.econbiz.de/10010711726
In this paper models for claim frequency and claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a...
Persistent link: https://www.econbiz.de/10010266163
Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...
Persistent link: https://www.econbiz.de/10011755371
Persistent link: https://www.econbiz.de/10003715380
In this paper models for claim frequency and claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a...
Persistent link: https://www.econbiz.de/10003310005
In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model allowing for overdispersion in different...
Persistent link: https://www.econbiz.de/10003310097
Persistent link: https://www.econbiz.de/10008665740
Persistent link: https://www.econbiz.de/10011312070
Mortality projections are major concerns for public policy, social security and private insurance. This paper implements a Bayesian log-bilinear Poisson regression model to forecast mortality. Computations are carried out using Markov Chain Monte Carlo methods in which the degree of smoothing is...
Persistent link: https://www.econbiz.de/10002638737
In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. Besides the inclusion of covariates, spatial effects are incorporated and modelled using a proper Gaussian conditional autoregressive prior based on Pettitt et al. (2002). Apart from...
Persistent link: https://www.econbiz.de/10002753399