Someone’s life expectancy is the expected number of years he or she will remain alive. It is an average that is computed for several groups of people of varying specificity, such as the entire global population, newborns in Ghana, or 15-year-old women in Europe. It is a statistic used in many debates, especially in those concerning a country’s (under)development. The statistic is always presented with much confidence, that is, no-one really doubts the accuracy and reliability, which becomes clear in thousands of articles, but let’s pick one:

In the two decades to 2010, men’s life expectancy increased by 4.7 years and women’s by 5.1 years – but the extra years of good health were only 3.9 years and 4 years respectively.

Or even more specific:

New Yorkers who are 70 saw their life expectancy increase 1.5 years, to 86.9, compared with 0.7 years, to 85.1, for the same age group nationwide.

I find such statements truly remarkable, since it is not at all straightforward that we can compute life expectancy statistics with great confidence and accuracy. A great deal of uncertainty enters the calculations in several ways, of which I would like to discuss a few: picking indicators, large prediction horizons, and lacking backtesting.

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