Are you saying the assumption that the curve will change significantly is questionable or that the effects of the assumed change in the curve change are immaterial?
IE, if we accept an assumption that the curve will shift such that average life expectancy at birth is 110 50 years from today, how is this immaterial for a 30 year old today? My common sense understanding is that their chance of kicking it in the 30-35 age bracket is locked in, but once they get to 65, the curve will have shifted enough that their chance of kicking it between 65-70 (a more substantial risk) have meaningfully decreased.
Take this extreme scenario.. say we accept Aubrey De Grey's most optimistic (and probably misquoted) prediction that "the first person to live to 1,000 will be born in the next two decades," then that seems to obviously affect people alive today materially, especially if they are young.
> Are you saying the assumption that the curve will change significantly is questionable or that the effects of the assumed change in the curve change are immaterial?
Sorry, that's not quite what I am saying.
My point was that "given the purpose of this analysis, mortality factors are immaterial."
If the purpose of this analysis was to give some quantitative answers that were going to be used as the basis for decisions - then it's highly likely that you would want to build in mortality improvement.
However, in this case the analysis is just a simple illustration to convey a simple idea (actual lifespan vs life expectancy), and I would say that building in mortality improvement would muddy the waters and make it just that little bit harder for the audience to understand.
Mortality improvements are important, but immaterial in this context ;)
I think that this should be taken as more of a qualitative illustration of the uncertainty of life, as opposed to a quantitative measurement.