Keywords

2.1 Introduction

Population ageing has triggered a series of reforms in public pension systems across the globe in recent years. This increase in life expectancy, in combination with the reduction in fertility rates – below the population replacement rate of 2.1 children per woman – has called into question the sustainability of public pension systems, especially for pay-as-you-go defined-benefit schemes, which are highly conditioned by demographic conditions. The most common measure implemented in these recent reforms in the OECD countries has been to increase the statutory retirement age. Additional measures introduced into public pension systems across the OECD have sought to promote active ageing, working longer and the tightening of early retirement provisions (OECD 2015).

However, these reforms have all been based on projected expenditures that depend solely on population projections (Actuarial Association of Europe 2016). These institutional population projections are, in turn, founded on assumptions about the evolution of conventional demographic measures. Traditional demographic indicators – based on chronological ages, such as life expectancy, the old-age dependency rate and median age – are expected to increase in future decades because of the increase in longevity. However, various authors have developed new measures based on prospective ages. In 2005, Sanderson and Scherbov introduced a new concept of age founded on remaining years of life rather than on the years that a person has already lived. Using this concept, they have rescaled certain measures related to population ageing – including old-age dependency rates and median ages – concluding that conventional measures typically extrapolate projections and, so, create concern about the sustainability of public pension schemes (Disney 2000). When rescaling these indicators to remaining lifetimes, however, the results obtained do not foresee such increases in longevity and, in some cases, they even remain stable. Thus, concerns regarding the long-term sustainability of pension systems need to be treated with caution and take into consideration different approximations of population projections (Sanderson and Scherbov 2005).

However, the goal of pension policies is not only to guarantee the long-term financial sustainability of the system but also to improve pension adequacy. Public pensions are the main source of income for the elderly across the OECD countries accounting, on average, for around 59% of their budget (OECD 2015). Elderly women are, on average, more exposed to risks of poverty than their male counterparts, owing to their longer longevity and lower pension entitlements (European Commission 2016). Their longer longevity, in turn, means they will live more years in old age, making them more likely to live alone (Lodovici et al. 2015; Alaminos and Ayuso 2015; Uribe et al. 2015; Chuliá et al. 2016). As such, female budgets are more vulnerable to pension indexation because they are paid for a longer period (Määttänen et al. 2014; Lodovici et al. 2015; European Commission 2016). Moreover, women are more likely than men to face daily limitations – either physical or mental – and, therefore, to have to meet the associated long-term care costs (WHO 2011; Guillen and Comas-Herrera 2012; Alaminos et al. 2016; Piulachs et al. 2016).

The lives of individuals are directly affected by the socio-demographic changes that societies have undergone in recent decades. Family structures have been modified by the reduction in fertility rates and by changes in life priorities. Lower fertility rates mean fewer children per woman and, hence, smaller families. Moreover, with a higher female participation in labour markets, individuals tend to postpone the moment of starting a family until their working career is secure (OECD 2011a).

Changes in family structure are also associated with subjective well-being in old age (Pinquart and Sörensen 2000). Elderly people enjoying a good social network are more likely to live healthier than their lone counterparts. Indeed, active ageing would seem to be the best medicine for happy ageing (Holzmann 2013b).

The aim of this chapter is to present evidence of the new challenges that public pension schemes have to face both today and tomorrow. In so doing, we focus on issues related both to demographics and to society. The chapter is structured as follows. In Sect. 2.2, we review the main demographic indicators, highlighting new measures specifically adjusted to remaining years of life. In Sect. 2.3, we present our analysis of the European population in terms of marital status, family structure and household composition. Finally, Sect. 2.4 analyses different indicators of well-being among the elderly.

2.2 New Demographic Indicators on Which to Base Pension Reforms

2.2.1 Traditional Indicators of Population Ageing

Population ageing can be measured in terms of the evolution of four indicators: (i) number of older people; (ii) share of older people over the total population, old-age share; (iii) demographic old-age dependency ratio; and (iv) median age (Ayuso et al. 2015). All these traditional ageing measures are predicted to rise over the next few decades, especially among those aged 80 and above.

Thus, according to Eurostat’s population projections (EUROPOP2013), the EU-28 population aged 80 years or more is expected to increase from 3,255,964 in 2015 to 5,003,773 in 2080, reaching a peak in 2050 with 5,535,357 individuals (Eurostat 2016d). The proportion of elderly people in the EU-28, above all those aged 80 years and above, is expected to increase from 5.30% in 2015 to 12.30% in 2080 (Fig. 2.1). The old-age dependency ratio – defined as the proportion of the population aged 65 and over in relation to the population aged 15–64 years – is also expected to increase from 28.80% in 2015 to 51.00% in 2080 (Fig. 2.1). Finally, the median age of the population – the age which divides a population into two groups of equal size, one of them being younger than this age and the other older – is also projected to rise from 42.40 years in 2015 to 46.40 years in 2080.

Fig. 2.1
A line graph of increasing trends plots the projected proportions of ageing traditional indicators from 2015 to 2080. Old-age dependency ratio has the highest peak in 2018 at 55. Data is approximated.

Projected proportions of people aged 65 and above and 80 and above (%). Projected old-age dependency ratio. EU-28. (Source: proj_13ndbims, Eurostat database (last update 08.12.16))

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Adopting Eurostat’s methodology, life expectancy can be calculated for any age. However, in line with the specific purpose of this chapter, we focus on life expectancy at older ages, that is, at 65 and 85. Figure 2.2 shows life expectancy at these two ages by gender in the European Union (EU-28 average). Over the last decade, not only has life expectancy at birth increased but it has also increased at advanced ages.Footnote 1 This represents the great advances made by society, indicative of the improvement in living standards, in lifestyle and in socio-economic levels, and of the advances in medicine and healthcare, which have reduced mortality rates in both genders.

Fig. 2.2
A line graph of increasing trends plots the life expectancy at the age of 65 and 85 by gender from 2002 to 2014. Females of 65 age have the highest peak in 2014 at 24. Data is approximated.

Life expectancy at the age of 65 and 85 by gender for the EU-28 average (in years), 2002–2014 series. (Source: demo_mlexpec, Eurostat database (last update 01.12.16))

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Figure 2.2 shows that while the life expectancy of the elderly has increased for both genders, women always present longer life spans. Over the 12-year series, the gender gap at 65 has fallen slightly (from 3.7 years in 2002 to 3.4 in 2014); however, the gender gap at 85 years has risen slightly (from 0.9 years in 2002 to 1.1 years in 2014).

2.2.2 Alternative Indicators of Population Ageing

The traditional measures of population ageing described in the previous section are based on the individual’s chronological age and assume that their age-specific characteristics do not change over time or from one location to another (Sanderson and Scherbov 2007, 2010, 2015). However, these characteristics are known to vary over time and space, which led Sanderson and Scherbov to suggest reformulating traditional ageing measures so that they are based on prospective age as opposed to chronological age. Thus, while chronological age is based on the number of years that an individual has lived, prospective age is concerned with the individual’s remaining life expectancy. For instance, conventional indicators measure the number of individuals getting older at ages 65 or 85, whereas prospective indicators consider people becoming old when they are expected to live for 10 or 20 more years. Figure 2.3 shows the differences between conventional and prospective median ages in Western Europe between 1960 and 2050. As can be seen, the conventional median age presents a growing trend, but Sanderson and Scherbov seek to demonstrate that when using a prospective measure the result is not the same. Indeed, the prospective median age is expected to have fallen by 2050. Likewise, in the case of the old-age dependency ratio (Fig. 2.4), the prospective indicator is not expected to grow as fast as the conventional measure.

Fig. 2.3
A line graph of fluctuating trends plots the median age for Western Europe from 1960 to 2050. The conventional median age has the highest peak in 2050 at 48. Data is approximated.

Median age and prospective median age for Western Europe, 1960–2050. (Source: Sanderson and Scherbov 2015. Figures based on data produced by the United Nations for the 2012 volume of World Population Prospects)

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Fig. 2.4
A line graph of fluctuating trends plots the old-age dependency ratio from 2000 to 2050. The conventional old age dependency ratio has the highest peak in 2050 at 0, 70. Data is approximated.

Conventional and prospective old-age dependency ratio for Germany, 2000–2050. (Source: Sanderson and Scherbov 2007)

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It is not the intention for prospective measures to replace conventional indicators; rather, they should complement each other. Traditional measures based solely on chronological age do not assume that life expectancy is influenced by factors such as disability rates or remaining life expectancy. Moreover, conventional measures foresee an increase in longevity. Prospective indicators, in contrast, seek to slow down the ageing process by making more moderate, or even decreasing, predictions, which need to be taken into account when making political decisions linked to the future evolution of population ageing.

2.2.3 Other Indicators of Population Ageing

In this section, we describe the evolution of other indicators based on disability rates and remaining life expectancy: namely, healthy life years and expected number of years in retirement.

Since the publication of the Stiglitz-Sen-Fitoussi Report (2009), new indicators of well-being have been used in policymaking, and GDP is no longer the sole measure of social progress. For example, from the perspective of the individual, health status is an indicator of quality of life (OECD 2011c), but the increase in life expectancy (Fig. 2.2) does not include any evidence as to how many years an individual lives in good health. An indicator of the relative health status of a population is that of healthy life years (or disability-free life expectancy), which seeks to measure the number of years an individual lives in good health rather than measuring the length of life until death – as is the case of life expectancy (Eurostat 2016a). In the case of the EU-28, this measure is calculated using data from mortality statistics (Eurostat demographic database) and from the European Union Statistics on Income and Living Conditions (EU-SILC)Footnote 2 (Fig. 2.5).

Fig. 2.5
A stacked bar graph compares the aging life expectancy at the age of 65 by gender. Sweden females have a maximum of 16.7 in good health and Sweden males have a minimum of 3.7 in bad health.

Life expectancy at the age of 65 by gender in 2014 shown as the number of years lived in ‘good’ (healthy life years) and ‘bad’ health. Data for the EU-28 average and for countries with the minimum and maximum results at this age. (Source: hlth_hlye, Eurostat database (last update 22.04.16))

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Eurostat uses three indicators of healthy life years: healthy life years at birth, healthy life years at 50 and healthy life years at 65. In the EU-28 in 2014, healthy life years at birth was 61.40 years for men and 61.80 years for women (Eurostat 2016a), which as percentages of total life expectancy represent 78.60 and 73.90%, respectively. At the age of 50, healthy life years for men stood at 17.40 and at 17.80 for women, which in relative percentage terms of total life expectancy was 57.70 and 50.90%, respectively. At the age of 65, the healthy life year’s indicator was the same for both genders (8.60 years); however, in relative percentage terms of total life expectancy, the gender gap was notorious with elderly women being expected to live 39.81% of their total life expectancy in good health and men 47.25%.

Figure 2.5 shows, in the case of total life expectancy at 65, the number of years lived in ‘good’ (healthy life years) or ‘bad’ health in 2014. The EU-28’s average by gender shows that women have a higher life expectancy at 65 than men; however, as noted, the proportion of those years lived in good health stands at 39.81% compared to 47.25% in the case of men. Thus, the additional years that women live are lived in poor health conditions (Crimmins et al. 2011; Thorslund et al. 2013; Lindahl-Jacobsen et al. 2013), in what the literature has called the ‘male-female health-survival paradox’ (Case and Paxson 2005; OECD 2011a; Alberts et al. 2014; among others). The EU member state that presents the lowest number of healthy life years is Slovakia in the case of women and Latvia in the case of men. Slovakian women aged 65 live 18.85% of their remaining lives in good health, while men in Latvia aged 65 live 28.99% of their remaining lives in good health. Note that in these extreme cases, the gender gap is higher than that of the EU-28 average. In contrast, Sweden presents a higher number of healthy life years for both genders. In the case of females, total life expectancy at 65 is the same as that for the EU-28 average; however, Swedish women live more years in good health than the women in the rest of Europe (16.7 vs. 8.6 years), giving a relative percentage of total life expectancy of 77.31%. Swedish men aged 65 live 80.42% of their remaining lives in good health. In all cases, men enjoy more years without health limitations than women, despite the fact that the latter always present a higher life expectancy at 65.

In terms of life expectancy, women usually live longer than men (5.50 years, on average, in 2014 if we consider life expectancy at birth and 3.40 years if considered at 65). However, as seen, these additional years of life are typically marked by some kind of activity limitation. Gender gaps in healthy life years are not as great as they are in terms of life expectancy. In relative terms, the number of healthy life years as a percentage of total life expectancy indicates that women enjoy fewer years of healthy life than men (Fig. 2.6). Despite the fact that the gender gap in healthy life years as a percentage of total life expectancy has remained steady over the last decade, the percentage has followed a slightly downward trend. This can be explained by the fact that although life expectancy has increased, the number of years lived in good health has remained constant, even falling slightly in some cases.

Fig. 2.6
A line graph of decreasing trends plots the healthy life years from 2005 to 2014. H L Y at birth males have the highest value in 2005 at 83. Data is approximated.

Healthy life years (HLY) as a percentage of total life expectancy (%), time series 2005–2014. (Source: hlth_hlye, Eurostat database, (last update 22.04.16). EU-27: 2005–2009; EU-28: 2010–2014)

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The fact that the additional years of life women live are accompanied by some type of daily limitation means governments not only have to consider the adequacy of their public pensions for the elderly (including, retirement and survivors’ pensions), but they also need to implement long-term care systems that cover all the requirements of the population with some degree of dependency. However, the healthy life year’s indicator cannot yet provide a proper time series to describe the trend followed by this measure over the last few decades.

A further indicator based on remaining life expectancy is that of the expected number of years in retirement, as used by the OECD. This indicator measures the number of years an individual is expected to live between exiting the labour market and death (OECD 2015). The OECD average increased between 1970 and 2014 (Fig. 2.7) due to two factors: first, the effective labour market exit age has fallen over recent decades (in males from 68.73 in 1970 to 64.46 in 2014, and in females from 66.59 to 63.16) and, second, life expectancy has increased (Fig. 2.2). Both genders have experienced an increase in their retirement life span, although there is evidence of a gender gap here too. For women, the average retirement span is 22 years, while for men it is around 18 years. This longer retirement life span makes women, in particular, more vulnerable, as it means they will probably have to live longer with an associated disease and with less income than their male counterparts. Note that the effective retirement age for both males and females experienced a sharp fall during the 1990s and early 2000s for a number of reasons. Some policies targeted a reduction in labour supply, e.g. the promotion of early retirement; others a reduction in labour demand, e.g. reducing incentives for maintaining low-skilled older workers in the labour market (Duval 2003).

Fig. 2.7
A graph of expected year of retirement and effective retirement age from 1970 to 2014. Male E R A is high in 1970 at 53 and female E Y R is high in 2010 at 68. Data is approximated.

Expected number of years in retirement (EYR) and effective retirement age (ERA) by gender. OECD average, 1970–2014 series. (Source: OECD 2015. Left y-axis: EYR; right y-axis: ERA)

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2.3 New Family Structures

2.3.1 Changes in Family Patterns

Family structures have been in a constant process of change since the 1960s (OECD 2011b). From the vantage point of society, the role played by women has been crucial. The gains in female educational attainment and the increase in the female workforce have delayed the age at which mothers have their first child and increased the childlessness rate. Today, women have the opportunity to fulfil their professional aspirations; thus, there have been changes in life priorities, with women postponing the age at which they form a family. From the demographic perspective, the fall in fertility rates combined with the increase in longevity has led to societies with fewer children and more elderly individuals than a few decades ago (OECD 2011a).

In recent decades, there have also been changes in partnership patterns (Fig. 2.8). Marriage rates have fallen and divorce rates have risen. In the EU-28, the average crude marriage rate has dropped from 6.3 marriages per 1000 persons in 1990 to 4.2 in 2011. In the case of crude divorce rates, the European average has increased from 1.6 divorces per 1000 persons in 1990 to 2.0 in 2011. Moreover, the average age at which first marriage occurs has been delayed, rising to over 30 for men (32.10 years) and almost 30 for women (29.50 years) in 2014. Both series have followed a growing trend over the last few decades.

Fig. 2.8
A line graph of fluctuating trends plots the marriage and divorce rates from 1990 to 2011. The crude marriage rate has its highest peak in 1990 at 7, 0. Data is approximated.

Average crude marriage and divorce rates (per 1000 inhabitants), EU-28, 1990–2011 (Source: Marriage (demo_nind) and divorce (demo_ndivind) statistics (Eurostat 2016c))

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Furthermore, new family patterns have emerged in European and OECD countries. The decline in marriage has been accompanied by new partnership types, including civil partnerships, cohabitation (or consensual unions) – a situation in which a couple live together in the same household but neither as a married couple nor in a registered partnership – ‘living apart together’ and ‘weekend relationships’Footnote 3, the last two relationships being characterised by the fact that each partner maintains their own residence. These new forms of partnership are emerging primarily among younger generations, who are more likely to cohabit than previous cohorts (OECD 2011a; European Union 2015).

The European 2011 Population and Housing Census (Eurostat 2012) classifies families according to the following types: household composed of married couple, household composed of couple in registered partnership, household composed of couple in consensual union,Footnote 4 household composed of lone father living with at least one child and household composed of lone mother living with at least one child.

Figure 2.9 shows the proportion of each partnership type for the European countries for which data are available on all types. The data show that marriage is the most frequent of the unions with registered partnerships being the least frequent. The number of single parents living with at least one child has increased in recent decades – most notably in the case of lone mothers – accounting for more than 10% of household types. These families present the greatest risk of finding themselves in vulnerable situations (Bauman 2002; Gornick and Jäntti 2009; Bradshaw and Chzhen 2011; OECD 2011a; Kramer et al. 2016). Of the two, mother-only families are more likely to be below the poverty line than father-only families (Lewis 1997; Christopher 2005; Kramer et al. 2016).

Fig. 2.9
A horizontal stacked bar graph compares the partnership types in %. Greece has a maximum of households of married people at 82 and a minimum of couples in a consensual union at 2. Data is approximated.

Partnership types in selected EU member states, 2011. (Source: cens_11fts_r3, European Population and Housing Census 2011 (Eurostat 2012))

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Despite the changes in the living arrangements of Europeans, the distribution of the population aged over 20 by marital status shows that marriage is the most frequent arrangement (Fig. 2.10). In 2011, 55.10% of the European population aged over 20 was married, followed by those that were single (i.e. those that had never been married), representing 27.97% of the population over the age of 20. Widows/widowers and divorcees represent 8.85 and 7.46%, respectively, of the total population.

Fig. 2.10
A pie chart compares marital status distribution in %. Married are high at 55,11 and divorced are low at 7,46.

Marital status distribution among European population over the age of 20, EU-28, 2011. (Source: cens_11mr_r3, European Population and Housing Census 2011 (Eurostat 2012). Note that the total sum does not add up to 100% as we do not consider those who are unclassified)

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As for the distribution of the population by gender and age group (Fig. 2.11), there is no notable difference between genders aged between 20 and 64. Among the total population, married couples constitute the largest group (53.26% for men and 56.82% for women), followed by singles (38.63 and 30.22%, respectively). Note that there are more widows than widowers (3.61% vs. 0.90%). However, in the cohorts aged 65 and over, there is a marked difference between genders. Elderly men are mostly married (75.23%), there being considerably fewer widowers (13.21%) and singles (5.90%). However, elderly women are mainly widows (44.81%) or married (42.64%). Note that in this case, widows constitute the largest group because of the higher life expectancy of women at advanced ages. These figures indicate that women are more likely to live alone in old age than men (Oeppen and Vaupel 2002; Vaupel and Kistowski 2005; Ayuso and Holzmann 2014; Alaminos and Ayuso 2015).

Fig. 2.11
A bar graph compares marital status among the European population by gender and age group in %. Married men of 65 + years are high at 75,23 and widowed men of 20 to 64 years are less at 0,90.

Marital status distribution among European population by gender and age group, 2011. (Source: cens_11mr_r3, European Population and Housing Census 2011 (Eurostat 2012))

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2.3.2 Household Composition

Among Europeans, the most common types of private households by size are those composed of a single individual or by two persons, each of which accounts for a third of the total (Fig. 2.12). Households formed by five or more individuals are the least frequent, accounting for 6.30% in 2015. Between 2007 and 2015, there has been an increase in the proportion of individuals living alone, rising from 30.00% to 32.20%, respectively. Households made up of two individuals have also grown, but at a slower rate than one-person households (from 30.10% in 2007 to 31.30% in 2015). However, while one- and two-person households are becoming more common in Europe, larger households are becoming less frequent. Three-person households have decreased their share in recent years (from 17.20% to 16.40% during the time series analysed); however, greater reductions have been suffered by households with more occupants, in particular those comprising four individuals. In 2015, the average household size in the EU-28 was 2.3 persons. Household size has fallen or remained steady in all European countries over the last decade (2005–2015 series, Eurostat 2016b). In Belgium, Croatia,Footnote 5 Demark and Poland, for example, household size has remained stable at 2.3, 2.8, 2.0 and 2.8 persons, respectively. In contrast, Bulgaria has experienced the sharpest fall, from 2.9 persons in 2005 to 2.5 in 2015.

Fig. 2.12
A vertical stacked bar graph compares the household composition in Europe by the number of persons from 2007 to 2015. The households with 2 persons are high between 30 to 60 in 2014. Data is approximated.

Household composition in percentage (%) in Europe by number of persons, 2007–2015. (Source: ilc-lvph03, EU-SILC, Eurostat 2016b. EU-27: 2007–2009; EU-28: 2010–2015)

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Figure 2.13 shows the distribution of the EU-28 population aged 65 and over by household type in 2015. Given the importance of the elderly to the discussion conducted here, and as they are the main recipients of social security benefits, the study of these cohorts is of particular relevance. According to EU-SILCFootnote 6 data, in 2015 Europe’s elderly members lived primarily in couples (48.30%) or alone (32.20%). This distribution however shows a gender difference. Men aged over 65 lived mainly with a partner (59.70%). The proportion of men living alone represented one fifth of the total (21.30%), while households comprising more than two individuals accounted for 14.10%.

Fig. 2.13
A horizontal stacked bar graph compares the distribution of the population aged 65 and over by household in %. Male couples without other persons are high at 59,70 and males with other households are less at 4,90.

Distribution of the population aged 65 and over by type of household, EU-28, 2015. (Source: ilc_lcps30, EU-SILC, Eurostat 2016b)

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In contrast, a predominance of elderly females lived alone (40.50%), in a proportion that is almost twice that of elderly males. As seen above, the distribution of the elderly population by marital status (Fig. 2.11) indicated that women tend to live on their own,Footnote 7 whereas men are mostly married. Studies on this subject present evidence indicating that elderly women often prefer to live alone on becoming widows rather than moving into the home of a relative (Kramarow 1995; Chandler et al. 2004). Moreover, many women who never married and became emancipated continued to live with their ascendants until they died, at which point they became one-person households (López Doblas 2005). Elderly women living with a spouse constitute 39.60% of households across the EU, while those living with their spouse and more persons are less than half that of their male counterparts (6.40 vs. 14.10%, respectively).

In the final category, that of other households, these represented 13.50% in the case of elderly females and just 4.90% in that of males. The higher share among females can be attributed to the elderly living with their extended family. The EU-SILC data show that Southern and Eastern European and the Baltic countries present higher shares of this kind of household (e.g. 29.60% in Poland, 29.60% in Latvia, 27.80% in Croatia, 26.20% in Slovakia and 24.90% in Spain). Indeed, Iacovou and Skew (2011) report that in Southern and Eastern European countries extended-family households made up of a multigenerational family, in which a couple live with both children and parents, are more typical than in other European cultures. Thus, elderly widows are likely to end up living in their children’s households (Fokkema and Liefbroer 2008).

2.4 Well-Being Indicators Among the Elderly Population

2.4.1 Heterogeneity in Longevity by Marital Status

Following the recommendations of the Stiglitz, Sen and Fitoussi Report (2009), the OECD established a framework for measuring individual well-being in 2011 (OECD 2011c). This framework comprises a series of indicators based on different dimensions of people’s well-being, which can be classified in two general areas: quality of life (health status, work-life balance, education and skills, social, connections, civic engagement and governance, environmental quality, personal security and subjective well-being) and material conditions (income and wealth, jobs and earnings, and housing).

The quality of the social network in old age is associated with subjective well-being (Pinquart and Sörensen 2000). Different social networks, such as marital status – marriage – and family ties, are positively linked to life satisfaction and happiness and have an influence on health status (Helliwell and Putnam 2004). Since health perception is considered a predictor of mortality (Menec et al. 1999), an association can be found between marital status and longevity.

Recent studies have established marital status as one of the most important factors affecting individual welfare in old age (European Union 2014). Furthermore, among the socio-economic indicators, marital status is considered an influence on longevity (Ayuso et al. 2016). The positive links that married individuals develop, thanks to social interactions, produced mostly by family ties, help them to live in better health. According to survival theories, marriage is associated with greater longevity (Kaplan and Kronick 2006). At old ages, in particular, being married translates into broader social connections and, therefore, more positive feelings (Holzmann 2013a) that have a positive influence on health status (Robards et al. 2012). In old age, the probability of being alone increases (Abellán García and Pujol Rodríguez 2016). Lone elderly people present higher probabilities of death than their peers living in a couple (Manzoli et al. 2007; Ng et al. 2015; Alaminos and Ayuso 2015). On occasions, the feelings of loneliness experienced by the elderly that live alone would appear to account for these higher probabilities of death (Gove 1973).

The probabilities of death for the elderly Spanish population by age, gender and marital statusFootnote 8 are shown in Fig. 2.14. Regardless of gender, married couples present lower death probabilities than those that live alone. Among this latter group, single people present higher death probabilities than widows/widowers until the age of 90, at which point the latter begin to show higher probabilities. By gender, probabilities of death among men are higher among widowers and those that are married (Alaminos and Ayuso 2015), whereas single women present higher death rates than single men.

Fig. 2.14
3 line graphs of increasing trends plot the total, male, and female populations. It plots single, married, and widowed. The widower is high in the male population at (95, 0.40). Data is approximated.

Estimated death probabilities by marital status, age and gender in 2011. Total, male and female Spanish population aged 65 and over. (Source: Alaminos and Ayuso (2015, 2019))

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2.4.2 Active Ageing

The subjective well-being of the elderly can be enhanced by promoting their active ageing. In this regard, policymakers should target the individual’s welfare rather than the system as a whole. Among the key factors identified for ensuring happiness in old age, two stand out: having an objective in life and maintaining social interactions (Holzmann 2013b). Since retirement is a transition between two stages in life, conceiving retirement as a specific, punctual event (rather than a gradual process) is perhaps not the best way to achieve well-being in old age.

Workers who remain in the workforce beyond their official retirement age present higher levels of life satisfaction and report better well-being than their retired peers (Graham 2014). Furthermore, later-life work contributes to maintaining and enhancing an individual’s social network and providing a sense of purpose in life (Holzmann 2013a; Nikolova and Graham 2014). Indeed, some researchers report that elderly individuals who extend their working life increase their well-being, while those pressed into involuntary retirement suffer a fall in their levels of well-being (Calvo 2006; Bonsang and Klein 2012; Nikolova and Graham 2014).

Aside from benefitting workers, the concept of gradual retirement may also be propitious for employers and governments (Derviş 2013; Nikolova and Graham 2014). In the context of high levels of unemployment and an ageing population, public pension systems face obvious problems of sustainability. One way of addressing this could be to offer phase-in retirement programs so that employees gradually stop working and do not leave the labour market (and so continue to pay their taxes) until the age of 70. An additional advantage is that older employees are an excellent source of experience and can help train younger employees. However, the attitude of employers towards later-time workers is often blind to these benefits. Employers tend to consider older workers as a burden rather than as an opportunity, hence the low rates of old-age employment in Europe and labour markets that do not promote the hiring of the elderly (van Dalen et al. 2010). However, some studies suggest that later-life employees present higher levels of productivity than workers in other cohorts (Burtless 2013; Holzmann 2013b). Overall, the evidence seems to show that the active elderly present lower death probabilities and less likelihood of suffering mental and physical illnesses (Everard et al. 2000; Siegrist et al. 2004; Calvo 2006).

An alternative form of employment after reaching the statutory retirement age is offered by the so-called bridge jobs, carried out by elderly workers once they have retired (Ruhm 1990). Working part-time may also be considered the equivalent of bridge employment (Beehr and Bennett 2014). Bridge jobs help retirees achieve a better work-life balance during retirement and to stay active both socially and productively. Furthermore, such employment can bolster the individual’s public retirement pension by providing an extra source of income (Hébert and Luong 2008). All in all, partial retirement can help cushion the consequences retirement may have on a retiree’s well-being, improving his or her degree of life satisfaction (Dingemans and Henkens 2015).

However, the positive levels reached by indicators of well-being among elderly workers may be biased for a various reasons (Graham 2014). First, healthier workers are more likely to remain active after the statutory retirement age. Second, more highly skilled and motivated workers tend to remain in the labour force until more advanced ages. Finally, individuals that are happiest in their work are more likely to continue working into retirement. An example of this last point can be found in the Spanish population. Figure 2.15 shows the average job satisfaction by age and gender, according to the Life Conditions Survey (Spanish Statistical Office 2014). Employees aged 65 and over reported higher levels of satisfaction than the mean for all other age cohorts (7.40 vs. 6.90, respectively). By gender, elderly men reported a higher degree of satisfaction than the mean for all other cohorts (7.90 vs. 6.80) and then women of the same age (7.90 vs. 6.70). Note that elderly women reported lower levels of job satisfaction than women at any other age. This might be attributable to the fact that women are likely to be entitled to less money in terms of public pension payments than men of a similar age (Alaminos and Ayuso 2015) and, as such, are obliged to remain in the workforce after passing the statutory retirement age. The European average – regardless of gender – presents similar levels of satisfaction to those presented by the Spanish population (Eurostat 2013). Thus, workers aged 65–74 in Europe report a level of job satisfaction of 7.3 compared to a mean of 7.1 at younger ages.

Fig. 2.15
A bar graph compares job satisfaction by age and gender. Males of 65 + years old are high at 8,0 and females of 65 + years old are less at 6,6. Data is approximated.

Average job satisfaction by age and gender. Spain, 2013. (Source: Life Conditions Survey (Spanish Statistical Office 2014). Average satisfaction scales from 0 to 10, being 0 the worst score and 10 the better one. Only people in employment were surveyed)

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2.5 Conclusions and Discussion

Recent reforms to public pension systems have been implemented in order to tackle the problems of ageing. These reforms have employed traditional measures of ageing based on chronological ages; however, various studies, most notably Sanderson and Scherbov (2007), have introduced new measures of remaining lifetimes to show that population ageing is unlikely to be as rapid as predictions based on traditional indicators claim. These new prospective indicators seek to complement traditional measures, so that policymakers need to consider both when making population projections on which to base long-term pension policy design.

There is little doubt that the increase in the number of those aged 65 and over (or whatever the corresponding retirement age might be) together with higher levels of female workforce participation will raise the number of individuals entitled to public retirement pensions in the future. Moreover, in some countries, such as Spain, greater longevity is associated with an increase in the number of beneficiaries, especially among females, with entitlement to a survivor’s pension. Thus, we can expect an increase in the number of beneficiaries of more than one public pension (Alaminos and Ayuso 2015). From the point of view of the sustainability of the pension system, this means paying more pension entitlements for longer. From the perspective of the individual, this situation flouts the principle of actuarial equity. The fall in the number of marriages, combined with the rise in the number of people living alone, will mean that a greater number of people in the future will only be entitled to their own retirement pension. Survivors’ pensions might therefore be inequitable for elderly singles – especially in the case of women – who can only depend on their own retirement pensions (Arza 2015; Alaminos and Ayuso 2019). Elderly people living alone are more likely to be at risk of poverty than those that live in a couple (OECD 2014), because of their lower pension entitlement, lack of family ties and worse health (OECD 2011b). Hence, new policies need to target individuals rather than the population as a whole.

In the last few decades, there has been an increase in the number of one-person households. In part, this increase appears to be a consequence of an ageing population, and the share of people living alone seems set to grow even more over the next few decades according to OECD projections (OECD 2011a). Moreover, elderly women are more likely to live alone than men. Given that in some countries (e.g. Spain) older women are entitled to lower pensions than men (as a result of their shorter labour careers) and are more likely to suffer disabilities, special policies need to be pursued.

The emergence of new family structures also needs to be taken into consideration in formulating new social policies. Legislation governing public pension schemes needs to reflect these changes by introducing new ways of accessing benefits (Mattil 2006).

Finally, well-being in old age plays a vital role among the elderly, with social networks – constituted by family members and/or work colleagues – being the most important variable affecting their levels of subjective well-being. In this regard, active ageing appears to be crucial for happy ageing (Calvo 2006; Holzmann 2013b).