Data resource profile: the Human Mortality Database (HMD)
Insurance companies and pension funds are affected by many different kinds of risks. In life insurance there are two main risks: the demographic risk and the investment risk. The demographic risk can be dividing into insurance risk and longevity risk. The first risk associated with the random deviation of the number of deaths from its expected value, the second deriving from the improvement in mortality rates. Numbers of actuarial stochastic models have been developed to analyse the mortality changes. This work focuses on Lee-Carter, Cairns-Blake-Dowd models and their extended versions with the inclusion of the cohort effect. We construct 6 stochastic actuarial models on Russian data at the first time. For modelling we use age-specific mortality rates and the probability of dying between 1959 and 2014 for the population aged 20 to 88 years from the Human Mortality Database. We consider age range from 20 to 88. Using the "StMoMo" package in the R software environment, code was written for modelling and predicting mortality with the help of actuarial stochastic models. For comparison of models, information criteria (Bayesian information criterion and Akaike criterion) were used, as well as sensitivity to changing the time range.
This article is talking about state management and cultural policy, their nature and content in term of the new tendency - development of postindustrial society. It mentioned here, that at the moment cultural policy is the base of regional political activity and that regions can get strong competitive advantage if they are able to implement cultural policy successfully. All these trends can produce elements of new economic development.