Quantile ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ M V aM aV C11 C22 C33 C44 C21 C31 C32 C41 C42 C43 2.5% -2.44 -2.48 0.84 0.79 1.33 0.09 1.81 0.90 0.07 1.37 0.05 -0.93 0.10 -1.13 Table 7.1 Bootstrap results Table 7.1 gives an impression of the uncertainty in the parameters describing the time series for the European trend and the Dutch deviation. Because these values are obtained via simulations, the results from a new bootstrap could be slightly different. In general the medians of the bootstrap results are close to the parameter best estimates, but not in all cases. More specifically, it appears that somewhat lower values are found for parameters aM and aF, which describe the dynamics of the Dutch deviation from the European trend. Parameter uncertainty and Poisson noise are not included in the confidence intervals shown in chapter 9. If they were, the confidence intervals would widen. To determine – for instance- the 2.5% quantile of the combined uncertainties, one would not use the 2.5% quantile parameter values shown here, as this would result in a value that relates to the 2.5% times 2.5% equals 0.0625% quantile. 7.2 The effect of the choice of model Before the transition to a new stochastic model in 2014 the CSO and the working group of that time compared numerous models. Any model current in actuarial practice and scientific literature at the time that had a semblance of plausibility was included in this survey. This has resulted in the current model being chosen. The current model assumes that the gradual improvements in mortality probabilities observed in recent decades will continue in the future and that there will not be any sudden structural breaks in the trends. On the one hand, major successes have been achieved in the medical field and by our healthier lifestyles, while on the other hand very many additional lives were unfortunately lost to smoking. Despite all these major effects we still see a relatively steady pattern in the observed mortality frequencies. The CSO therefore opted not to explicitly model the structural breaks in the trends. Doing so would further complicate the model. Moreover, many additional subjective assumptions would need to be made about future medical and other potential developments. At the same time we would point out that our model represents a stochastic scenario generator. Anyone who wants to add scenarios to the model to include their own Projection Table AG2018 Uncertainty 20 25.0% -2.20 -2.16 0.91 0.91 1.88 0.15 2.69 1.26 0.18 2.05 0.19 -0.60 0.19 -0.67 50.0% -2.08 -1.99 0.94 0.95 2.23 0.18 3.23 1.47 0.25 2.48 0.27 -0.43 0.24 -0.45 75.0% -1.95 -1.82 0.96 0.97 2.61 0.21 3.85 1.70 0.32 2.95 0.36 -0.28 0.31 -0.25 97.5% -1.70 -1.49 0.99 0.99 3.43 0.29 5.12 2.19 0.47 3.96 0.54 0.01 0.44 0.13

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