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Life expectancy forecasting is usually based on two different approaches:
* Forecasting the life expectancy directly, generally using [[ARIMA]] or other time series extrapolation procedures: that has the advantage of simplicity, but it cannot account for changes in mortality at specific ages, and the forecast number cannot be used to derive other [[life table]] results. Analyses and forecasts using this approach can be done with any common statistical/mathematical software package, like [[EViews]], [[R (programming language)|R]], [[SAS (software)|SAS]], [[Stata]], [[Matlab]], or [[SPSS]].
* Forecasting age specific [[death rates]] and computing the life expectancy from the results with life table methods: that is usually more complex than simply forecasting life expectancy because the analyst must deal with correlated age-specific mortality rates, but it seems to be more robust than simple one-dimensional time series approaches. It also yields a set of age specific-rates that may be used to derive other measures, such as survival curves or life expectancies at different ages. The most important approach within this group is the [[Lee-Carter Model|Lee-Carter model]],<ref>{{cite web|url=http://www.soa.org/library/journals/north-american-actuarial-journal/2000/january/naaj0001_5.pdf|title=The Lee-Carter Method for Forecasting Mortality, with Various Extensions and Applications - SOA|publisher=}}</ref> which uses the [[singular value decomposition]] on a set of transformed age-specific mortality rates to reduce their dimensionality to a single time series, forecasts that time series and then recovers a full set of age-specific mortality rates from that forecasted value. Software includes Professor [[Rob J. Hyndman]]'s [https://web.archive.org/web/20100822170736/http://robjhyndman.com/software/demography/ R package called `demography`] and [http://lcfit.demog.berkeley.edu/ UC Berkeley's LCFIT system].
==Policy uses==
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Life expectancy is also used in describing the [[physical quality-of-life index|physical quality of life]] of an area or, for an individual when the value of a life settlement is determined a life insurance policy sold for a cash asset.
Disparities in life expectancy are often cited as demonstrating the need for better medical care or increased social support. A strongly associated indirect measure is [[income inequality]]. For the top 21 industrialized countries, if each person is counted equally, life expectancy is lower in more unequal countries (r = −0.907).<ref>''[http://jech.bmj.com/content/59/2/158/F2.expansion Has the relation between income inequality and life expectancy disappeared? Evidence from Italy and top industrialised countries] {{webarchive|url=https://web.archive.org/web/20150109080429/http://jech.bmj.com/content/59/2/158/F2.expansion |date=January 9, 2015 }}'' J Epidemiol Community Health 2005;59:158–162.</ref> There is a similar relationship among states in the US (r = −0.620).<ref>''[http://www.bmj.com/content/312/7037/999 Inequality in income and mortality in the United States: analysis of mortality and potential pathways]'' BMJ 1996, 312:999.</ref>
==Life expectancy vs. life span==
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