In the scientific literature methods are provided for formalising parameter and model uncertainty. In relation to parameter uncertainty, it can be noted that due to the enormous quantity of data (more than 100 million deceased with a total exposure of more than 11 billion) this may be expected to be small for a given model. Including model uncertainty requires the specification of a class of alternative models. There is only limited literature on this and for this reason it has been decided for the time being not to include this in this publication. 7.3 Distinction between uncertainty in mortality probabilities and uncertainty in mortality figures The above means that the uncertainty in the observed mortality figures will also be small. In addition to the uncertainty in the mortality probabilities, after all, there is also uncertainty in the actual number of people deceased in the light ofthese mortality probabilities. If, for instance, we consider a group of 100,000 people with a mortality probability of exactly 1% (on the basis of the assumption we have made of a Poisson distribution for individual mortality) the expected number of deceased is 1,000 and the symmetrical 95% confidence interval [938;1062]. This does not mean that the underlying mortality probability has suddenly become uncertain and has changed from 1% to an unknown value somewhere between 0.938% and 1.062%. It only means that we were not able to observe the mortality probability without measurement noise due to the small number of observations. The volatility in the mortality figures reported by Statistics Netherlands cannot therefore simply be used to make statements about uncertainty in the underlying mortality probabilities. The AG2016 model explicitly takes this into account in the estimation method. However, whoever wishes to estimate the future uncertainty in the pension or insurance portfolio must also take into account the uncertainty in individual cases of mortality after simulating the possible parts for future mortality probabilities. As a result, the distribution in portfolio results will increase. Projection Table AG2016 Uncertainty 18
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