@techreport{eprints3518,
           month = {July},
            year = {2016},
           title = {A continuous-time stochastic model for the mortality surface of multiple populations},
            type = {EIC working paper series},
     institution = {IMT School for Advanced Studies Lucca},
       publisher = {IMT School for Advanced Studies Lucca},
          author = {Petar Jevti{\'c} and Luca Regis},
        keywords = {Keywords: multi-population mortality, mortality surface, continuous-time
stochastic mortality, Kalman filter estimation, centralized data fusion.
JEL classification: C13, C38, G22, J11.},
        abstract = {We formulate, study and calibrate a continuous-time model for
the joint evolution of the mortality surface of multiple populations. We model
the mortality intensity by age and population as a mixture of stochastic latent
factors, that can be either population-specific or common to all populations.
These factors are described by affine time-(in)homogenous stochastic processes.
Traditional, deterministic mortality laws can be extended to multi-population
stochastic counterparts within our framework. We detail the calibration pro-
cedure when factors are Gaussian, using centralized data-fusion Kalman filter.
We provide an application based on the mortality of UK males and females.
Although parsimonious, the specification we calibrate provides a good fit of
the observed mortality surface (ages 0-99) of both sexes between 1960 and
2013.},
             url = {http://eprints.imtlucca.it/3518/}
}