Individual circumstances can make a decade of difference to how long we live after retirement. As Sarah Harper, Kenneth Howse and Steven Baxter observe, this makes simply raising the retirement age inequitable
State pensions are a form of social insurance, helping to provide protection against living long without an adequate income. Inevitably though, different individuals have different life expectancies and so benefit from state pensions for different lengths of time. A new-born girl in Kensington and Chelsea can currently expect to live some 16 years and 6 months longer than a new-born girl in Glasgow City. Part of these differences relate to mortality rates in younger life and child bearing years, and so the differences narrow as individuals reach state pension age. However, material differences persist. The women of Kensington and Chelsea can, having reached 65, expect to live nine years longer than women in Glasgow.
Looking down the latest list of life expectancies by different areas produced by the UK's Office for National Statistics (ONS), a number of patterns start to emerge - for example, while those at the very top and bottom might be more urban in nature, rural localities generally appear near the top of the list, and urban localities generally appear near the bottom. Similarly, areas near the top of the list tend to be associated with wealth, while those areas associated with greater deprivation occur near the bottom.
These patterns are not coincidental and are core to the challenges that differences in life expectancy pose to pensions reform. Any reform measures which are based upon life expectancies - and changes over time therein - of the population as a whole risk having a disproportionate effect on those with the shortest life expectancies, or for whom life expectancy is increasing at the slowest rate. For example, the same changes to state pension age (SPA) apply to those individuals with a life expectancy of 12 years to those with a life expectancy of 24 years. Those with the shortest life expectancies - namely, the poorest and so those with greatest reliance on the state pension - lose a greater proportion of their total benefit income.
In this article we seek to identify some of the key patterns and trends which could influence the current debate on the relationship between life expectancy and the state pension promise.
The rural and urban divide
A greater proportion of pensioners live on incomes below the national average in rural areas of the UK. Pensioners in rural communities also face higher costs of living, increasing their need for an adequate state pension safety net. Looking down the ONS' list, we also see that the places with highest life expectancies tend to be rural localities. This is supported by analysis of data collected by Club Vita on the longevity experience of pensioners within occupational pension schemes: as locations become increasingly rural so male life expectancy increases.
Deprivation and regional variation
The lowest life expectancies tend to be found in urban areas and in particular areas with significant concentrations of deprivation. It would be easy to assume that the differences in life expectancy between locations can be largely attributed to differences in levels of deprivation. However, joint research between Oxford Institute of Ageing and Club Vita has identified that the range seen between regions is widest among the most deprived parts of the UK and that there continues to exist significant regional variation in life expectancies for men and women in all bar the least deprived areas.
Our findings suggest that regional differences are due to more than differences in deprivation. This poses a challenge to any reforms. Is it desirable to avoid a disproportionate impact on individuals in certain deprived areas who are likely to be most reliant on the state? And, if so, can this be achieved? Before we can begin to answer this question, it is important that we understand more about the differences in life expectancy seen between individuals rather than regions.
Everyone is different
It is not just regional and deprivation factors that influence how long we live. Other factors such as health, genetic disposition to different diseases, lifestyle and education all have substantial bearing. Using detailed data collected on members of occupational pension schemes, Club Vita has identified the effects that a number of individual characteristics have on life expectancy in isolation.
For example, pensioners retiring in ‘normal health' can typically expect to survive between one-and-a-half and three-and-a-half years longer than pensioners who retire with a known health issue which means they are eligible for enhanced pension benefits.
The effect of retirement health on life expectancy is most pronounced for pensioners who have the healthiest lifestyles and highest levels of affluence. There is a difference of up to 4-5 years in life expectancy between the least healthy and healthiest lifestyles (estimated using data provided by commercial providers such as Experian and CACI on the likely lifestyles of individuals living in certain postcodes).
Affluence can have an additional impact on life expectancy comparable in magnitude with lifestyle. Men with a history of salaries of more than £40,000 (€46,500) a year have a life expectancy 3-4 years longer than those earning less than £15,000 a year in current terms. The effect is smaller among women today, but with increased labour force participation, and increased access to workforce pensions we might see personal income having a more material effect for future generations of women.
Finally, whether an individual has carried out a ‘manual' or ‘non-manual' role can account for up to 0.75 years' difference in life expectancy for men and up to 1.5 years for women. The effects described here are independent - to find the combined effect you can add the numbers together as illustrated in figures - and, in aggregate, they explain a spread in life expectancies of more than 11 years for men, and almost 10 years for women.
In the context of changes to the state pensions, it is insightful to consider that fewer than one in three poorer, less healthy men aged 65 will enjoy 15 years of state pension, compared with eight in 10 healthier, wealthier men. It is also worth highlighting that the data collected by Club Vita relates to individuals who have been members of occupational pension schemes. As such, the extremes described here may be lower than the extremes seen in the UK population as a whole, some of whom have never been able to work due to poor health.
Diversity in trends
Life expectancy has been steadily increasing over the twentieth century, and is projected to continue to increase - but has it been increasing in the same way for everyone? If not, then relying on national life expectancy trends to inform decisions on state pension reform could disproportionately impact some individuals.
Looking at the increase in life expectancy since 1991 for different regions, we see a considerable range - and it is noticeable that (wealthy) Kensington and Chelsea and Westminster top the lists for both highest life expectancy and largest increases. This pattern has been more widely repeated - there is a positive correlation between those regions where there were the largest increases in life expectancy and those with the highest life expectancies.
Club Vita's data also highlights that the pattern of changes in mortality rates among pensioners has been significantly different for former manual workers compared with former non-manual workers. Another difference is how life expectancy appears to have increased slightly faster in recent years among the less affluent. While over the longer term increases in life expectancy have been lower for those in the lower socio-economic classes than for the higher socioeconomic classes, between 1993 and 2008 life expectancy for men earning below £25,000 a year in current terms has increased by almost three years compared with less than 2.5 years for men earning over £25,000.
Reflecting diversity in pensions policy
Since insurance serves to pool risk of adverse outcomes (in the case of the state pension, living long without an adequate income) for protection (ie, income) there will always be some winners and some losers when SPA changes. As a society are we comfortable with the inequity that applying averages can lead to?
If the answer to this is no, then we should ask ourselves whether it is possible to design a system where state pension age directly reflects diversity in life expectancy. By doing so, we would also reduce the ‘substitution risk' whereby state pension age rises, yet many individuals who would previously have collected state pension have it replaced in part or in full by payment of disability benefits instead.
One way to address this could be to allow SPA to increase differently for different broad groups, perhaps based on the predictors of individual life expectancy identified here. Not all of these predictors are practical to use. For example, regional or postcode-based factors would be open to individuals selecting against the state, by moving to a different part of the country for a short period of time in order to benefit from a lower state pension age. However, one possible predictor which could potentially be used is an individual's earnings.
One possible framework for linking state pension age to lifetime earnings could be carried out using national insurance records: different SPAs could apply to different earnings bands - say,