1 February 21, 2021 Health, Job Precarity, Employment, Poverty

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February 21, 2021 Health, Job Precarity, Employment, Poverty, and Life Expectancy Daniel Gottlieb and Aviad Tur-Sinai1 Abstract Advances in medical knowledge and technology have helped to raise both general and healthy life expectancy (HLE), causing a secular upturn in the share of the elderly population and challenging PAYGO systems of Social Insurance (SI) by increasing their default risk. One way to tackle this problem is to raise the age of old-age-benefit entitlement, aka the retirement age. Such a policy, however, requires an unpopular decision to extend working life, thus creating an adverse policy bias. Several countries have implemented an automatic linkage of the entitlement age to life expectancy (LE) as a solution to increased default risk of SI and pension funds. Such an extension of employment presumes, at least implicitly, a steady improvement of people’s health in tandem with the increase in their life expectancy. Analyzing the determinants of self-perceived health (SPH) by use of the SHARE longitudinal multi-country database, combined with data on life expectancy and its healthy part, from EUROSTAT, and where missing, from WHO, we find that past and present employment improves health while the gender effect of job quality on SPH is detrimental for women and positive for men. We found that job precarity is particularly widespread among women and that its negative effect on health rises with age, whereas job quality among men is mainly positive and peaks in the mid-fifties. This empirical result has an important implication for the policy of automatically linking retirement age to healthy life expectancy: We argue that it justifies progressive reduction of the linkage, certainly for women, with increasing age. One way to achieve this is to attach weights to the existing and the linked retirement age—a weight increasing with age to the existing RA and a complementarily falling weight with age to the linked RA. This would obviate the front-loading of the linkage of RA to healthy life expectancy as occurs in current typical discretionary RA policies. We find health degraded by poverty and various disabilities, among other things. Longevity is found to raise self-perceived health, while SPH, employment, and job quality are found to affect each other simultaneously. Age dynamics and job quality are also found to differ substantively by gender. The negative effects of job quality for women need to be addressed in any suggested automatic balancing mechanism of the retirement age. Our findings show that for countries with an elasticity coefficient exceeding 1, HLE at age 65 rises faster than general life expectancy at a given age, implying that people’s ability to work until a higher age is improving over time, thus making the retirement age a potentially powerful tool to improve SI sustainability. We also find that LE and HLE raise SPH, the effect of HLE on SPH being dominant. We conclude that SI sustainability should be linked to healthy LE rather than to general LE. Finally, poverty rates are found to affect SPH negatively but there is no evidence of poverty feminisation with respect to this effect.

Keywords: Self-perceived health, self-assessed health, employment, job quality, job stress, job satisfaction, job security, job precarity, healthy life expectancy, retirement age, SHARE, poverty, social insurance sustainability

1 We thank participants of the conference on retirement age adjustment held on 24th February 2021 at Ben-Gurion University in the Negev for helpful comments, Noam Damri for preparing a literature survey for an early version of the paper and Michael Beenstock and Ofir Pinto for fruitful discussions.

1. Introduction Advances in medical knowledge and technology in recent decades have helped raise both life expectancy (LE) and healthy life expectancy2 (HLE). Secular trends of declining fertility and increased longevity have caused the share of the elderly population to rise. In a typical pay-as- you-go (PAYGO) setting of social insurance that does not adjust to such trends, they eventually lead to actuarial deficits that subject Social Insurance (SI) organisations and pension funds to steadily increasing default risk. This is caused, among other things, by too low adjustment of the retirement age (RA), the age after which a person is entitled to an old age benefit. As long as RA adjustment is slower than the increase in LE, such a development jeopardises SI sustainability (see also Hills, 2004, discussing threats on social insurance sustainability from both sides of the political spectrum). Therefore, a key policy tool for reducing default risk, adopted by at least 10 countries, is the steady prolongation of the official period of working life by some mechanism, be it LE, changes in the financial balance, or other.3 Such continuity, however, is difficult to implement by means of discretionary policy. The more frequently the RA needs to be adjusted, the more advantageous it is to adopt a rule-based approach, such as an automatic balancing mechanism (ABM), that changes RA and contribution rates automatically according to an optimal rule. The discretionary and the automatic approaches differ in two important ways: (1) Typically, the discretionary approach is front-loaded, raising retirement age immediately for people verging on that age and leaving out the younger generations, thereby improving actuarial deficit immediately. Usually, the increase in the retirement age for younger ages is left to future discretionary policy, if at all. An example is the UK’s decision to raise early RA in 1995 (Cribb and Emmerson, 2019); (2) Given the upward trend in life expectancy, the discretionary process must be repeated frequently. The inherent difficulty of performing such a repetitive process causes an implicit policy bias due to delays in completing the requisite change. Opposition to such change causes cohorts that successfully postpone the change to prolong benefit receipt while those affected by the change in RA see their planned and expected RA pushed into the future at the last moment. The more acute the SI crisis and the lower the balance of the SI reserve fund and, in turn, the nearer the dwindling and eventual depletion of the reserves, the more threatened

2 Sometimes abbreviated as HALE. 3 This includes Denmark, Estonia, Finland, Germany, Italy, Japan, Lithuania, Netherlands and Portugal (OECD, 2019, Table 1.1). The automatic mechanism has been temporarily suspended until 2023 or further notice in Spain and to 2026 by Italy.

younger workers will feel concerning their social security. In a rule-based approach of automatic RA adjustment, the mechanism can be planned such as to respect accumulated social rights and the existence of hazardous work conditions or gender biases that may degrade certain people’s (H)LE expectancy. Politicians accustomed to heavily discounting distant future achievements often prefer a discretionary approach because it yields a higher gain in the short- term actuarial position of pension funds and SI, thus creating an even stronger short-term policy bias. This paper focuses on the tension between two processes. One is systemic delay in adjusting the age of eligibility to old-age benefits, weakening the sustainability of SI organisations that at the last moment raise the age of eligibility for old-age benefits among people near retirement age by applying a gradual discretionary approach. The other is an increasingly hazardous situation of deteriorating job quality, especially for ageing women. The approach that we develop reconciles these two processes on the basis of careful analysis of the determinants of the self-perceived health (SPH) of individuals aged 50+. Our empirical analysis draws on surveys in the European countries that participate in the SHARE database, with special emphasis on the possible simultaneity of health and employment and the gender and dynamic age effects of employment and job quality on the SPH of persons around retirement age (RA) and eligibility for SI (old-age and other).4 The ultimate goal of our entire research project is to derive optimal rules for strengthening SI sustainability. A natural first step and, therefore, the subject of this paper is to study the ability of people around retirement age, in the sense of their SPH and the variables influencing it, to extend working life dynamically, as required within a framework of sustainable automatic balancing mechanisms that account for the secular increase in life expectancy. After briefly addressing the COVID- 19 pandemic, which seems to have dealt an apparently temporary shock to life expectancy, we focus on various variables related to socioeconomic, labour-market and health-related issues. We are also interested in understanding the co-movement of general life expectancy (LE) and its healthy part (HLE). LE measures are mainly statistical, calculated on the basis of objective data on the population’s health and trend analyses of longevity.5 To better understand the possibilities and limitations underlying the pursuit of SI sustainability, we ask how LE and

4 Throughout this paper, RA is the age at which a person becomes eligible for an old-age benefit. It is not necessarily coterminous with retirement from the labor force. 5 HLE measures the number of years that a person of a given age can expect to live in good health, adjusted for age-specific mortality, morbidity, and functional health status. By applying disability weights to health statuses, it computes the equivalent number of years in good health to be expected at any given age of interest, for any given birth year and location (country). This definition was originated by Sullivan (1971), who developed a single index of expected years of disability-free survival that captures mortality and morbidity.

HLE, past and present employment, and employment quality as perceived by the individual interact with the individual’s SPH. We set these questions within a more general framework that incorporates additional variables into the analysis, such as various health conditions, income and assets, and other economic and demographic variables. A crucial issue for policy design that we address here concerns the dynamics of the relationship between some of these variables and the process of ageing. All these questions are posed within a gender and a general frame. By analysing them, we will be able at a later stage to suggest whether and how automatic balancing mechanisms can accommodate solutions to the problems raised. We hypothesise that the higher the quality of past employment and the stronger the job security, the more positive will be the overall effect of employment on SPH. Indeed, in some cases, women’s empowerment organisations have opposed initiatives to raise women’s RA due to gender discrimination in employment. This raises the question whether a sophisticated ABM that accounts for the correction of such labour-market discrimination in view of its importance for the determination of SPH and HLE has been empirically established for any given country. The repeated political and legal action that the discretionary approach entails creates a policy bias against timely and adequate RA adjustment. A rule-based approach can counteract to such a political bias by facilitating automatic gradual adjustment based on an optimal rule. This solves two problems: the need to adjust for the secular increase in LE over time and the need to account for gender (and possibly other) job-quality discrepancies that degrade HLE and SPH. Since this bias is often ignored in the policy discussion of SI sustainability, our empirical investigation estimates the information necessary for the reformulation of an optimal ABM of retirement age.6 One of the early contributors to the discussion of SI sustainability, Brown (1992), combines an active contribution policy with the creation of a reserve fund in order to maintain balance in an ageing population environment. Some countries have responded to the risks of pension crises by making discretionary adjustments of pension parameters such as retirement age, contribution rates or ceilings, or lowering and/or adjusting the pension level over time. Given the steady increase in life expectancy, policymakers’ refusal to adjust the retirement age continuously seemingly prolongs the period of old-age benefits for today’s young because their retirement period expands as the adjustment is deferred. In reality, however, SI actuarial deterioration makes it less likely that younger generations will enjoy the fruits of SI for the

6 Such an analysis will be pursued in a separate article.

simple reason that the continued depletion of reserves despite continued contributions by the young reflects a serious time inconsistency for them.7 Once they become aware of this disadvantage, their willingness to continue contributing is expected to decline, furnishing a strong reason to initiate a reform. A key instrument that has been suggested to alleviate the problem is to link the onset of old-age pension payment to life expectancy (Denton and Spencer, 2011; Godinez et al., 2016; Turner, 2009). Valdés-Prieto (2006) argue for the necessity of periodic adjustments due to demographic and economic uncertainty, in order to maintain long-term sustainability of PAYGO pension systems. Turner (2009) suggests linking the retirement age to life expectancy as a tool for optimizing SI sustainability. Milevsky (2010) views PAYGO in its pure form as a high-risk funding method that provides beneﬁts to retirees when they are due and payable without allowing a real reserve fund to accumulate. Denton and Spencer (2011) emphasise the consequences of rising life expectancy on the growth of the inactive population. Godinez et al. (2016) develop a model suggesting various ABMs that may overcome the sustainability challenge effectively in order to guarantee adequate liquidity in partially funded PAYGO pension systems and deal with the main risks of the system. A positive relationship among HLE, employment, and job quality provides a natural policy for strengthening social security.8 The prolongation of earnings from work and strengthened sustainability of the SI and pension system can effectively prevent or mitigate future poverty and inequality in old age. For those who face the unplanned deferral of expected early retirement as is typical in discretionary retirement policy, however, poverty may actually increase substantially, as the UK experience shows (Cribb and Emmerson, 2019). Still, such a policy delivers the important bonus of improving younger generations’ trust in the ability of SI to assure their future social rights. This conclusion is supported by pension-reform simulations carried out in Fehr et al. (2012). Such strategies, however, make sense only if the share of HLE in LE increases over time. If the opposite occurs, labour supply will be more difficult to adjust and demand for old-age pensions and long-term care will probably rise more rapidly than in

7 This issue was discussed in Kydland and Prescott (1977), for example, with respect to the trade-off between inflation and unemployment. Jacobs and Schindler (2012) applied the concept to SI policy. 8 This, of course, implies sufficient supply of general jobs by employers and no ageism in hiring. Most empirical findings support the conclusion that older workers do not crowd out young workers. Both national-level and cross- national analyses reject the argument that the increasing proportion of older workers reduces younger workers’ employment. The evidence points to the opposite: greater labor-force participation of older people is associated with stronger youth employment. Munnell and Wu (2013), expanding on Gruber and Wise (2010) by including work hours and wage rates as well as employment rates and labor-force participation as dependent variables, look at both time-series and cross-state variation in the context of the United States and China, employing state-level regressions and instrumental variable (IV) models. Their estimates show no evidence that increasing older persons’ employment reduces either the job opportunities or wage rates of younger persons.

the case of a rising HLE share in LE, thus putting pressure on SI finances on both the revenue and the expenditure sides.

2. Life expectancy, healthy life expectancy, and self-perceived health Generalife expectancy (LE) has been rising throughout the twentieth century and the beginning of the twenty-first century. In many countries, LE at birth has doubled since the 1900s (Kinsella, 1992; Wilmoth, 2000). The upturn in life expectancy has surpassed researchers’ and specialists’ predictions to the point that a discussion of the limits to human life expectancy has developed (Crimmins, 2015; Dong, Milholland, and Vijg, 2016; Oeppen and Vaupel, 2002; Wilmoth, 2000). The swift rise in LE in the twentieth century is attributed, among other things, to a sharp decline in infant mortality in the first half of the century and a downturn in mortality from acute infectious diseases among the elderly (Wilmoth, 2000). The former allows more people to reach adulthood; falling death rates among the elderly extent the longevity of adults. Although gains in life expectancy have slowed, projections have it that life expectancy will continue to rise. This process, together with the decline in fertility, is causing the share of the elderly to grow. The European Commission’s 2012 White Paper foresees increases in life expectancy at birth for males and females of 7.9 and 6.5 years, respectively, from 2010 to 2060. The European population aged 60+ is estimated to nearly double by 2060, implying rapid escalation of the share of pension expenditure in EU GDP to more than 10% by then. The biggest worldwide study on the co-movement of LE and HLE was carried out by a large group of scientists under the auspices of the Bill & Melinda Gates Foundation. Including 187 countries (Salomon et al., 2013, Chatterji et al., 2015, Murray et al., 2015), this research effort was intended to advance evidence-based policy choices that depend on how morbidity changes as mortality decreases (see detailed summary in Salomon et al., 2013). Between countries and over time, life expectancy was strongly and positively related to the number of years lost to disability. This relation was consistent between sexes, in both cross-sectional and longitudinal analysis, and when assessed—at birth or at age 50. Changes in disability had small effects on changes in HLE compared with changes in mortality. Two juxtaposed hypotheses have been raised concerning the effect of rising life expectancy on morbidity in old age. The ‘Failures of Success’ hypothesis (Gruenberg, 1977) argues that the increase in LE will be accompanied by increased incidence of disease and disabilities; the ‘Compression of Morbidity’ hypothesis (Cai and Lubitz, 2007; Fries, Bruce, and Chakravarty, 2011; Cutler, Ghosh, and Landrum, 2014) traces the increase in HLE to the

reduction of risks in young age, such as smoking and overweight, and improvements in medical technology.

3. Has life expectancy been stagnating recently?

Marois et al. (2020) attempt a worldwide early assessment of the potential impact of COVID- 19 on life expectancy. They find that the COVID-19 pandemic, after causing massive mortality worldwide and continuing to spread in early 2021, may have a significant direct impact on life expectancy depending on certain assumptions that they analyse in a microsimulation model. Using bias-adjusted age-specific infection fatality rates in Hubei (China) and six prevalence- rate assumptions ranging from 1% to 70%, they simulate the number of people infected by COVID-19, the number dying from it, and the number of deaths from all causes week-by-week for a one-year period. Applying the simulation to North America and Europe, Latin America and the Caribbean, Southeast Asia, and sub-Saharan Africa, they conclude that if the prevalence rate does not exceed 1% or 2%, life expectancy will not be affected. At higher prevalence rates, however—say 10%—the loss of life expectancy at birth may exceed one year in North America, Europe, Latin America, and the Caribbean, and less in Southeast Asia and sub-Saharan Africa. At prevalence rates higher than 10%, the downturn in life expectancy would be several times greater. Given the importance of life expectancy as a key indicator of human development and the increase in mortality, especially among vulnerable population, they conclude that the pandemic may subject many countries to a setback on their path of human development. Shortly before the breakout of the Covid-19 pandemic, a stagnation in life expectancy at birth, and in some cases even a small decline, had been observed in some countries, e.g., in the United States in 2014–2016 (Ho and Hendi, 2018). Rising mortality rates among low- educated non-Hispanic whites, due mainly to drug and alcohol abuse and suicide, were large enough to depress overall life expectancy in the U.S. even though the older population’s life expectancy continued to increase (Case and Deaton, 2015, 2017; Ho and Hendi, 2018). In contrast to the U.S. and the UK, life expectancy in other developed countries has continued to rise (Ho and Hendi, 2018; Muennig, Reynolds, Fink, Zafari, and Geronimus, 2018). After the COVID-19 pandemic erupted, Trias-Llimós and Bilal (2020) estimated its effect on mortality in Spain, parsed by regions, on a weekly basis. Life expectancies at birth in Spain were lower in Weeks 11–20 of 2020 than in the same weeks in 2019. The decline was especially strong in Weeks 13 and 14 (23 March–5 April), with national declines of 6.1–7.6

years and maximum regional weekly downturns of up to 15 years in Madrid. Annual life- expectancy differences between 2019 and 2020 also reflected a 0.9-year overall drop in annual life expectancy among both men and women, with a range of 0 years in several regions (e.g., the Canary and Balearic Islands) to 2.8 years among men in Madrid, which is considered the most affected region in Spain. Moreover, the significant medium-term impact of the disruption of the healthcare system was expected from the beginning of the pandemic to yield a higher death toll in the following months due to difficulty in controlling chronic conditions during the various peaks of the pandemic. However, Trias-Llimós and Bilal also noted the possibility of an eventual decline in the mortality rate due to a harvesting effect, such as that observed after severe flu seasons. The relative strength of both phenomena will eventually determine the severity of the decline in life expectancy. Andrasfaya and Goldman report on the huge COVID-19 death toll in the U.S.: over 215,000 by mid-October 2020, according to the Centers for Disease Control and Prevention, with a disproportionate burden of morbidity and mortality in the Black and Latino communities, reflecting persistent structural inequalities that amplify the risk of COVID-19 exposure and the mortality risk for those infected. They estimated life expectancy at birth and at age 65 in 2020 for the U.S. population and by race and ethnicity, using four scenarios—one counterfactual, assuming that the COVID-19 pandemic had not occurred, and three including variants of COVID-19 mortality projections. Their estimates indicate a 1.13-year decrease in U.S. life expectancy at birth, to the lowest point since 2003. At age 65, their estimate is equivalent to a 10.44-month contraction of. The Black and Latino populations are estimated to experience much bigger declines at birth—2.10 years and 3 years, respectively.

4. Employment, job quality, and health

Healthy life expectancy may not always increase in tandem with employment (Magnusson Hanson et al., 2015): if jobs are precarious, as in the event of severe 'job strain' or job stress, HLE may contract. Using of an indicator of SPH, Magnusson Hanson et al. calculate HLE as life expectancy free of four chronic diseases (cardiovascular disease, cancer, respiratory disease, and diabetes) on the basis of an analysis of 64,934 individuals aged 50–75. They derive their data from four cohorts, with repeat data from the Finnish Public Sector Study, the French GAZEL, the Swedish Longitudinal Occupational Survey of Health, and the Whitehall study (UK). Job strain (high demands at work combined with low employee control) was consistently related to shorter HLE (overall 1.7 years difference). The difference in HLE was more

pronounced among men than among women (2.0 years vs. 1.5 years) and among holders of lower occupational positions (2.5 years among ‘low-grade’ men compared with 1.7 years among ‘high-grade’ men). While somewhat smaller differences in HLE were observed among those in intermediate or high occupational positions, job strain was also associated with shorter HLE but in a weaker and less consistent way. One expects the effect of employment on HLE to be positive overall although, obviously, if employment is stressful or precarious and job security is low, then the basically positive effect will be mitigated or even reversed. Such effects may also work the other way around—from SPH to employment, with, say, a depressive disorder shortening employment spans or the chances of finding continued successful employment. Appropriate treatment of such simultaneity is important for the design and planning of SI sustainability by adjusting the retirement age. Several studies have found a relationship between income (or socioeconomic status) and longevity (e.g., Rogot et al., 1992, for the U.S., and Bosworth, Burtless, and Zhang, 2016; Neumayer and Pluemper, 2016; Gottlieb et al., 2018, for Israel). Rogot et al. (1992), basing their analysis on data from a household and telephone survey with a high response rate (96%) conducted by the U.S. Bureau of the Census (the U.S. National Longitudinal Mortality Study) for 1979–85, estimated life expectancies for 822,347 white men and women by education, family income, and employment status. Life expectancy was found to vary positively with schooling and family income. Differences in life expectancy at age 25 between the highest and the lowest levels of education completed were about six years for white men and five for white women. In family income, differences between the highest and the lowest income groups were about ten years for white men and 4.3 years for white women. The largest differences in life expectancy were between employment categories. At age 25, white men in the labour force lived about 12 more years on average than those not in the labour force, and white women about 9 more years. Among those unable to work compared with those in the labour force, the difference in favor of working people was about 20 years for white men and 29 for white women. These education-based differentials resemble those found in an earlier study (Kitagawa and Hauser, 1973). Blöndal and Scarpetta (1999), examining the main determinants of the decision to retire from the labour market in OECD countries, argue that the role of SI labour-supply disincentives have been damping elders’ labour-force participation in recent decades. They note in particular the implicit work disincentive in OECD countries’ old-age pension systems in the mid-1990s, which made working after age 55 financially unattractive. The financial disincentives, they add, were amplified by early-retirement programs including

unemployment-related and disability schemes. In most countries, it was believed necessary to revise both the old-age pension system and the various income-support programs to mitigate these disincentives. The disincentives to work in the old-age pension system, they advise, may be eliminated or weakened in various ways: Given that incentives are typically lowered before the earliest age at which old-age pensions become available, a direct way to encourage people to work longer would be to raise the pensionable age. Combining neutrality with flexibility, they argue, the most appropriate reform would be to let people choose their retirement age and to adjust the pension level such as to leave the pension system neutral on average. Under such a system, the increase in pensions due to an additional year of work would make up for both the additional year of pension contributions and the one-year delay in pension takeup. This, Blöndal and Scarpetta conclude, would eliminate the early- retirement incentives embedded in current arrangements. Under a neutral system of this type, those choosing to retire early could do so at the cost of a permanently lower pension stream whereas those choosing to work until advanced age would be financially rewarded. However, due to myopia and generally suboptimal saving, such a system risks an increase in old-age poverty. Importantly, it also unduly punishes low-income disadvantaged persons and those whose employment is hazardous because since their exit from work may not reflect a choice. If these disadvantages shorten LE and HLE, as suggested in some of the sources mentioned above and as tested empirically in this paper, poverty and hazardous work conditions may have the same effects. As mentioned above, Blöndal and Scarpetta argue that the elimination of work disincentives would significantly increase the supply of older workers in the labour market, placing a burden on countries with high structural unemployment. The adjustment would be easier if reforms of pensions and other income-support systems for the elderly were to be accompanied by measures to increase job opportunities in general, including elimination of ageist measures and practices. The reforms themselves could help to broaden job opportunities for older workers by inducing, inter alia, changes in setting their wages, participation in training, mobility, and working-hour arrangements. The OECD Jobs Study (1995) and the OECD Jobs Strategy (2020) also suggest that broader reforms in labour and product markets along the lines advocated there would make the transition to increased labour-market participation of older workers easier and quicker. Cutler et al. (2011) argue that the simultaneous growth in U.S. longevity and budget deficits have spurred enhanced interest in raising the age of eligibility for public health and retirement benefits. The consequences of this policy depend on the health of the near-elderly

(aged 62–64) and the distribution of health among demographic groups. Parsing HLE at age 62 by sex, race, and education, Cutler et al. show that HLE varies widely within and across gender and racial groups, the best-off groups enjoying nearly four more years of healthy life than the worst-off. They simulate the working capacity of near-elderly individuals based on the work, disability, and retirement status of people aged 57–61 who report the same level of health. Their estimates point to substantial working capacity, suggesting that the health status of people aged 62–64 may boost their labour-force participation by over 15 percentage points. Disability rates, in turn, would increase modestly overall but more sizably among less advantaged and less educated groups. Milligan and Wise (2012) argue that despite substantial increases in health and longevity in the past fifty years, older men’s labour-force participation has declined in most developed countries. Tracking twelve OECD countries, they find much variation in older workers’ employment rates across countries, and over time within countries, at a given level of mortality. They also find a scanty relation across countries between improvements in mortality and change in employment at older ages, implying the existence of unused potential for higher employment. Cutler et al. (2006) predict that acceleration in the production of new knowledge and treatments may steepen the health gradient, with increasing gaps among educational and social classes, occupational groups, and races.

Lumsdaine and Mitchell (1999) try to understand why people leave their jobs at relatively young ages and spend lengthy periods living on public and private retirement benefits. They try to understand the forces that drive retirement behavior, focusing on retirement trends and retiree wellbeing. They also look at models that allow for worker heterogeneity and uncertainty about health and productivity shocks. Reviewing empirical analyses of retirement patterns undertaken in the 1990s, they look at natural experiments and longitudinal datasets that provide insights about demand for and supply of older workers. They also examine employers’ responses to an ageing workforce and question the rationale of government programs that induce job-leaving. One of their conclusions is that retirement decisions should be analysed by taking into consideration a range of issues such as personal health, other household members’ needs, and saving and consumption decisions. Evidence from the U.S. National Long-Term Care Survey shows that younger cohorts of elderly live longer and in better health than do older cohorts (Manton, Gu, and Lowrimore, 2008). Further findings from the U.S. in support of the compression hypothesis show an increase in HLE and a decreasing probability of severe disability among the elderly (Cai and

Lubitz, 2007), with similar findings for other countries (Australian Institute of Health and Welfare, 2012). Chatterji et al. (2015) report coterminous increases in HLE and morbidity in old age in some developed countries and several low- and middle-income countries. However, they relate to SHARE data without accounting for labour-supply endogeneity and use specific disability indicators that explain only part of HLE. Jagger (2015) finds evidence from some countries (UK, the Netherlands, France, U.S., Japan) of an increase in HLE over time, although its elasticity compared with general LE appears to be less than 1. Evidence from the 1970– 2010 period in the U.S. that squares with our results is found in Crimmins et al. (2016), who show that while the overall increase in years free of disability was outpaced by the rise in years of life with disability or equal to it, the opposite occurred at age 65. Although job precarity has increased considerably in recent decades, relatively little is known about its health consequences, international pattern, and potentially mitigating factors. In this paper, we investigated the association between job precarity and self-rated health and asked whether the relationship differs by country or by individual-level characteristics. Cross- sectional data from three population-based studies on job precarity, SPH, demographic, socioeconomic, work-related and behavioural factors, and lifetime chronic diseases among 23,245 working persons aged 45–70 in sixteen European countries were analysed using logistic regression and meta-analysis (Laszlo et. al. 2010). In fully adjusted models, job precarity was significantly linked to an increased risk of poor health in the Czech Republic, Denmark, Germany, Greece, Hungary, Israel, the Netherlands, Poland, and Russia, with odds ratios ranging from 1.3 to 2.0. Similar but not significant associations were observed in Austria, France, Italy, Spain and Switzerland. We found no effect of job precarity in Belgium and Sweden. In the pooled data, the odds ratio of poor health by job precarity was 1.39. The nexus of job precarity and health did not differ significantly by age, sex, education, and marital status. Persons with insecure jobs were at heightened risk of poor health in most countries in the analysis. Given these results and the trends toward greater frequency of insecure jobs, the public-health consequences of job precarity deserve attention.

On the labour-force-participation endogeneity, job quality, and self-perceived health

The effect of a person’s health on his or her labour-supply decision has been widely studied (Cai, 2010, Cai and Kalb, 2006, Strauss and Thomas, 1998; Dasgupta, 1997, Mitchell and Burkhauser, 1990; Stern, 1989, etc.). While Cai (2010) uses a simultaneous equation model that allows for labour-supply endogeneity and perceived health, the other studies typically assume causality from health to labour supply. An exception is Militaru et al. (2018), who investigate the relationship between self-perceived health (SPH) and labour-market

participation, controlling for the endogeneity of the health variable and including effects of health on wages. An inverse effect of employment on health has also been studied by Holmgren et al. (2009), who found a negative effect of work-related stress, illness symptoms, and sick leave on SPH. These papers, however, focus heavily on the adverse effects of unfavorable work conditions on health. Rijs et al. (2012) find no significant effect of retirement and retirement age on SPH. Persons who retire at ages 59–60, they report, are more likely to have excellent or good SPH than are age peers who remain employed. Rijs et al., however, like the others discussed above, do not test the effect of employment on (healthy or general) longevity and vice versa—a relevant question in the discussion of SI financial sustainability. The occurrence of simultaneity between employment and health suggests that simultaneity between employment and longevity also exists. Sede and Ohemeng (2015), studying determinants of life expectancy in Nigeria, and Segel-Karpas (2015), doing the same in Israel, point in this direction. Sede and Ohemeng report a significant negative effect of lagged unemployment on life expectancy; In Segel-Karpas, the relationship between the negative effect of the number of illnesses and depressive symptoms on SPH is moderated by employment. Employment also weakens the relation of SPH and depressive symptoms. According to Schuring et al. (2010), re-employment may lead to a rapid improvement in SPH. Segel-Karpas credits employment with psychological gains, finding that employment reduces the occurrence of depression because employed individuals adopt a ‘work role’ (following Thoits, 1992) that improves their well-being (Carter and Cook, 1995; Hobfoll, 1988) by connecting them with society (Kahn, 1972) and allowing for better self-definition (Stryker and Statham, 1985), self-worth (Ashforth, 2000), self-esteem, sense of accomplishment (Brown, 1978), and, possibly, maintenance of social support (Nathanson, 1980). Segel-Karpas argues that work may promote a self- perception of capability and health that mitigates the potential adverse effects of diagnosed illnesses on SPH. The opposite—the absence of work commitments due to retirement—may negatively affect mental health by placing individuals in a ‘sick role’ or depriving them of the ‘work role’; it may also, however, let people take better care of themselves due to newly found leisure time, the possibility of engaging in regular exercise, eating better, and mitigating work- life related stress. In the latter cases, retirement may improve self-perceived and mental health. All of this emphasises the absence of a straightforward relationship between employment and retirement; instead, simultaneity and reciprocity exist. The disentanglement of the two requires careful econometric estimation. Cai and Kalb (2006), examining the effect of health on labour- force participation using the Australian Household, Income and Labour Dynamics (HILDA) Survey, find that better health increases the probability of labour-force participation for all age groups. They also find a statistically significant positive feedback effect of previous labour-

force participation on older females' health. For older males, their results suggest that the impact of labour-force participation on health is not significant. We test this hypothesis on our multi-country database. On the basis of this literature review, we wish to test the following hypotheses: Do secular improvements in both healthy and general life expectancy affect self-perceived health positively? Does the rise in HLE, the age after which morbidity and sickness occur, exceed the rise in LE, implying that the share of HLE in LE should increase? An equivalent way of stating this is that the elasticity of HLE w.r.t. LE should be greater than one. If so, this implies that the period of employment may be prolonged, thereby also improving SI sustainability. To understand the likelihood of prolonged employment being a gain for the individual as well, we need to study a further hypothesis: that employment has a salutary effect on SPH. Clearly, the quantitative extent of employment is not enough to determine such an effect. It is important to add a hypothesis concerning job quality, such as precarious job conditions, involuntary part time employment, or physical hardship at work. Indeed, in some cases, women’s empowerment organisations have opposed initiatives to raise women’s RA due to gender discrimination in employment. Given the fact of this discrimination, it is crucial to study this question separately for men and women. The closest analysis of this issue is found in Laszlo et al. (2010), who performed logistic regressions of job security on SPH for each country in the SHARE survey and a meta-analysis of all sixteen countries in the combined database. In their research, both the gender effect and the age effect were statistically insignificant. As we show in the next section, our findings on job quality differ from this outcome in both the dependent and independent variables and, particularly, in the effects of age and gender.

The model

The model comprises a largely microeconomic equation that determines SPH dynamically over the medium and long run, augmented by several attached variables of macroeconomic nature, such as regional information and gender-specific life expectancy, as well as general time- specific country poverty rates. Our main hypotheses, spelled out at the beginning of the paper, require analyses of how gender, age, demographic variables, health risks, employment, and, especially, job quality affect SPH. We emphasise dynamic age effects on employment and job quality by using continuous age data from age 50 to 659 as well as other economic and educational variables.

9 We chose 65 because it approximates retirement age in many countries in the sample.

Differently from Laszlo et al., (2010) we produce a composite index of job quality for each individual in the sample by performing a factor analysis of each participant’s answers to ten questions in the SHARE survey relating to job satisfaction, the extent to which the job is physically demanding, time pressure caused by heavy workload, the degree of freedom given to get the work done, opportunity to develop new skills, support received when facing difficult work situations, recognition for completed work, adequacy of wage, prospects of promotion, and job security. We then used this composite variable, reflecting the aforementioned ten job qualities, as a variable of job quality in our main regression, explaining SPH. Our approach reflects the possibility of considerable simultaneity in the ten questions relating to job quality. For example, evidence for Israel shows that involuntary part-time jobs probably tend to be more preponderant among women (Gottlieb and Toledano, 2015). If so, treatment of the kind offered by Laszlo et al. may suffer from a simultaneity bias. Given the time span between the early (Wave 2) and the late wave (6) of the survey, we merge the results of our analysis of HLE and LE and test their effect on individuals’ SPH, allowing for country-specific effects. Focusing on HLE and LE will allow us in future work to develop a model of optimisation of SI sustainability by the use of an automatic balancing mechanism of RA (the age of old-age-benefit eligibility) based on the parameter estimates. Our model comprises several simultaneous dynamic equations:

(1) SPHj,i,t = sph(agei,t, gi, yi,t, Ei,t, LEi,t, xi) j=1….J individuals, i=1….N countries, t=wave 2 or 6

(2) LE = LE(xi,j, yi,j), i=1…..I, j=1…..J where x are the determinants of LE, its HLE part, or the ratio of the two, for individuals j, by gender, age, and country. We start by estimating a basic individual-level equation that attempts to explain self- perceived health (SPHj,t) as surveyed in Waves t=2, 6. The individual's age structure (agej,t) which expands from 50 to 65, and his or her gender (gi), are crucial, also affecting the other equations and variable calculations in the model. To allow for alternative ways of interaction between the gender and the life-expectancy variables, we present three regressions—one with all observations and one for each gender. The other variables (xi) stand for additional micro- variables such as income (yj,t), employment (Ej,t-1), and the job-quality variable in the previous wave, t-1, (i.e. 1 or 5) at the age given in Wave t, education, and, for the macro-variables of poverty and life expectancy, the macro-variable of average life expectancy of the individual's

gender-based age cohort j (LEj,i,t) at Time t=2 or 6, as well as its gender-based healthy part (HLE) and their ratio. The IV approach We control for simultaneity between employment quantity and job quality vis-a-vis SPH by using an instrumental variable approach that provides one job-quality equation for men and another for women, depending on age structure and family status, in the first stage.

(1) E,i,j,t = E,i,j,t(age, gender, Family status) + ε,i,j,t

(2) Ehat,t = Et – εhat,t where εhat,t is the estimated residual of the first-stage regression. This allows us to use the estimated employment forecast in Equation (4) of the second stage instead of the actual employment variable:

(3) SPHj,i,t = q(agei,t, yi,t, LEi,t, Ehat,i,t, gi, xi) j=1….J individuals, i=1….N countries, t=wave 2 or 6 5. Empirical results A simple, gender-based elasticity of HLE to LE at age 65 is shown to have the same sign in almost all countries and a positive sign in eight of fifteen countries (Fig. 1). On average, female elasticity is more than 70% higher than that of males. Elasticities are defined here as the ratio of percentage changes in healthy life expectancy

(HLE65) to changes in general life expectancy at age 65 (LE65). The data show that these elasticities differ widely among the countries observed: In most countries, elasticities are well above 1. Only in four of the nineteen countries are male and female elasticities below unity. In most cases, elasticities are found to be lower for men than for women, although in twelve out of eighteen countries (men) and in thirteen of eighteen (women) they are above unity. These findings imply that for countries with coefficients exceeding 1, HLE at age 65 rises faster than LE. This means that, a priori, over time, people’s ability to work until a higher age is improving because such a linkage makes the retirement rate a potentially powerful tool for improving SI sustainability.

Fig. 1: Elasticity of healthy w.r.t. general life expectancy (HLE, LE), by gender10

20.0 Germany Germany Sweden 15.0 Estonia Czechia y = 1.734x - 0.6307 France 10.0 Portugal Spain Israel 5.0 Belgium

Female Female Austria Slovenia 0.0 Italy -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Luxembourg Poland -5.0 Netherlands Greece Denmark Greece -10.0 Male Authors’ calculation based on years 2005 to 2018; elasticity is defined as each country’s male and female annual percent change of HLE divided by the annual percent change of its LE; y = trend. Source: Eurostat and WHO. For most countries, the age-specific increase from birth to age 65 of the HLE/LE ratio (Fig. 2) grew over time (i.e., between the years of Waves 2 and 6). This implies that the healthy part of life expectancy is typically growing faster than general life expectancy, thus increasing the individual’s potential ability to continue working once she reaches RA. Self-perceived health for age groups 50–84 also appears to be consistent with this statement because age- group-specific SPH improved during the same period (Fig. 3).

10 Calculated as the relative percent change of expectancies over the 10-year period from 2005 to: (%-change HLE—15-05) / (% change LE—15-05).

Fig. 2: Change in HLE/LE from Wave 2 to Wave 6, by age (at age 65) and country

14.00% Belgium 12.00% Czechia Denmark 10.00% Germany Estonia 8.00% Greece 6.00% Spain France

4.00% Croatia percent Italy 2.00% Luxembourg Netherlands 0.00% Austria Poland -2.00% Portugal -4.00% Slovenia 1 6 11 16 21 26 31 36 41 46 51 56 61 66 Sweden Switzerland age Israel

Fig. 3: Self-perceived health by age groups, Waves 2 and 6, all countries

3.5 time 2 time 6 3

2.5

perceivedhealth 1.5 -

self 1

0.5

0 50-54 55-59 60-64 65-69 70-74 75-79 80-84 age Source: SHARE multi-country database, calculations based on Waves 2 and 6.

The SHARE data on SPH at the two points of sampling support the existence of two basic trends of importance in determining the possibility of automatic employment expansion by means of automatic RA adjustments: although SPH tends to decline with age, it tends to improve over time in each of the presented age brackets (Fig. 3). Fig. 4 stresses the positive relationship between changes in SPH and HLE.

Fig. 4: Elasticities of self-perceived health w.r.t. healthy life expectancy Calculated from changes between Wave 2 and Wave 6 for all countries in the sample

12.0%

10.0%

8.0% 2

6.0%

over P over 6 6 P 4.0% y = 0.2024x - 0.0117 - R² = 0.3686 2.0%

0.0% 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0%

SPHUS SPHUS change -2.0%

-4.0%

-6.0% HLE change - P6 over P2

In the empirical section of this paper, we show that an improvement in the HLE/LE ratio is an increasing function of adult cohorts and that the positive linear relationship of SPH and the HLE/LE ratio in consecutive survey waves yields evidence consistent with the hypothesis that healthy ageing is an important precondition for a rational and dynamic retirement policy. SHARE surveys among the ageing population in fifteen European countries were carried out seven times in 2004–2017. We used Waves 2 and 6 because we found them best for testing the hypothesis of a positive relationship between SPH and LE because Wave 1 was less comprehensive and Wave 7 was devoted mainly to retrospective issues. Wave 2 was carried out in 2006/7 (for Israel: 2009/10) and Wave 6 took place in 2015. The surveyed countries apply welfare regimes of various orientations in the spirit of Esping-Andersen (1990)—the corporatist model, as in Austria, Germany, France, Switzerland, Belgium, and Luxembourg; the North European model, as in Sweden and Denmark’ and the familial South European Social Model, as in Spain, Italy, Greece, and Portugal. In 1985, Israel began to move from a social economic model toward a more capitalistic one and did so increasingly between 2002 and 2006, when the government slashed various social benefits and tightened conditions for entitlement, causing poverty and its severity to rise sharply. The sample also includes transition economies such as the Czech Republic, Poland, Slovenia, Estonia, and Croatia, which are classified as East European (Tur-Sinai and Lewin Epstein, 2020).

Job quality and self-perceived health

Our estimations allow for a complex relationship among employment, health, and HLE by specifying not only the effect of employment quantity but also its quality on health. To characterize job quality, several variables are needed in order to explain the effect of work conditions on health. The potential endogeneity of SPH in the labour-force-participation equation is addressed by a simultaneous estimation of the health and labour-force-participation equations. Our job-quality measure is built by a separate factor analysis and, similarly to our procedure with respect to employment, we treat the possibility of simultaneity by regressing on job-quality variables from the previous (i.e. lagged) survey wave (a first-stage regression). The effects of gender and age groups on the dependent variables are particularly important; they capture discrimination against women in the labour market (Fig. 5) in addition to the direct and indirect dynamic effects of ageing on health. Fig. 6 demonstrates the large gender difference in job quality to the detriment of women’s jobs. Another important result of this regression is that women’s job quality is fundamentally negative and worsens with age, whereas men’s job quality is fundamentally positive and peaks at around age 55–56. In Fig. 6, we calculate the average percent difference between the gender-index values for each age and the maximum absolute gender difference across all ages. We find that the average female disadvantage amounts to 11–14 percent of the maximum difference.

Fig. 5: Estimated regression values of the job-quality index, by gender

female

-26 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 Austria f -26.5 Germany f -27 Sweden f -27.5 Netherlands f -28 Spain f -28.5 Italy f -29 France f

qualityindex value -29.5 Denmark f -

job -30 Greece f

-30.5 Belgium f Israel f -31 age

male

2 Austria m 1.8 Germany m 1.6 Sweden m 1.4 Netherlands m 1.2 Spain m 1 Italy m

0.8 France m qualityindex value

- 0.6 Denmark m job 0.4 Greece m Belgium m 0.2 Israel m 0 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 Czech Republic m age

Fig. 6: Disadvantage of women vs. men in the job-quality index (%)

20.0 18.6 17.6 16.1 18.0 16.0 13.7 14.0 12.6 12.0 11.1 Average 10.0 8.1 Maximum (age 65) 8.0 Minimum (age 50) 6.0 5.5 4.0 2.0

0.0

Italy

Israel

Spain

France

Poland

Ireland

Austria

Greece

Croatia

Estonia

Sweden

Belgium

Average

Slovenia

Portugal

Denmark

Germany

Netherlands Luxembourg Czech Republic Czech

Source: SHARE dataset, lagged Waves 2 and 6, i.e., Waves 1 and 5.

As expected, the regression on job quality (Table 1) reveals women’s severe disadvantage to men in job quality: a negative fixed effect and also a negative age-dependent effect that grows with age.

Table 1: Effects of age, gender, and nationality on job quality Dependent variable: job quality Age 0.341073 Age squared -0.00303 Gender (f=1) -17.1582 Gender-age interaction (f=1) -0.2229 Country dummies .. Constant -8.60223 Number of observations 80,383 F-test 437.22 Adj. R-squared 0.111 Root MSE 4.1453 All coefficient estimates are statistically significant at the 1% level, except for some of the country dummies.

The IV results are presented in Tables 2a and 2b for LE and HLE, respectively. The instrument used is the lagged variable of employment quality, the lag being the status of employment quality in the previous wave—in Wave 1 for individuals in Wave 2 and in Wave 5 for individuals in Wave 6. The signs of the regression coefficients fit those expected from theory: Age has a negative sign because it reduces SPH, and it does so at a diminishing pace (coefficient of age2 >0). Loneliness, proxied by the ‘Single’ variable, is shown to affect men’s SPH negatively whereas women cope with it better; this is true for both LE and HLE. SPH is further explained by variables such as ADL, IADL, body-mass index, and depressive disorder (EUROD). The higher the ADL or IADL index, depressive disposition, or BMI, the lower is the forecasted SPH in the models with LE and with HLE. These effects are mitigated by enhanced education, higher income, and assets. LE and HLE both raise SPH, with HLE having the stronger effect. In Table 2b, we estimated the effect of poverty on SPH and found it to be significant and negative. We also tested the often-presented hypothesis of the ‘feminisation of poverty’, i.e., that there is a distinctly higher poverty rate among women (see also Morris, 2007, who finds such an effect in the U.S.), and found it unsupported by the data. We also tested the effect of living in a rural area and being a (Jewish) immigrant in the past couple of years. Instead of regressing either LE or HLE separately, we obtained a good result by using a relative specification of HLE/LE. The rural-area variable was statistically insignificant and immigration affected SPH negatively in the first year of immigration and positively in years 3–5 of immigration. (These two variables are not reported in the table.)

Table 2a: Self-perceived health, employment quality and quantity, and life expectancy by gender IV models Women Women Men Men Dependent Variable: SPH Age -0.08347 * -0.082671 * -0.04158 * -0.0411 * Age squared 0.000544 * 0.000538 * 0.000268 * 0.000261 * Gender (m=0) Single (s=1) 0.03754 * 0.0365926 * 0.019443 0.024179 Single (s=1)*gender (m=1) #-children 0.003083 0.003479 -0.00091 *** -0.0013 ADL -0.0936 * -0.092658 * -0.12223 * -0.12135 * IADL -0.11654 * -0.116427 * -0.10852 * -0.10935 * Eurod (depressive disorder) -0.12814 * -0.12775 * -0.14393 * -0.14328 * BMI -0.01015 * -0.010057 * -0.01041 * -0.01039 * Years of schooling 0.02157 * 0.021638 * 0.021644 * 0.021383 * ln(income) 2.40E-02 * 0.0251463 * 3.95E-02 * 0.041321 * Net financial assets 1.89E-07 * 1.93E-07 * 1.66E-07 * 1.71E-07 * ep26_35_n1 -0.01049 * -0.01053 * 0.016158 * 0.016084 * ep26_35_n1*gender (f=1) Employment_pred 7.17E-03 * 6.99E-03 * 4.55E-03 *** 0.005017 ** Life expectancy (LE_65) 7.02E-02 ** -3.13E-02 * Healthy life expectancy (HLE_65) 1.42E-02 *** 0.042966 ** Wave 6 (d=1) 7.06E-03 5.08E-02 8.53E-02 -0.01374 Constant 4.685848 * 5.838527 * 5.006653 * 3.662837 * Number of observations 37,384 36,905 23,425 23,174 F-test 498.06 490.51 267.68 265.4 Adj. R-squared 0.3528 0.3523 0.3182 0.3187 Root MSE 0.84651 0.84559 0.8862 0.8854 * Statistically significant at 1% level ** Statistically significant at 5% level *** Statistically significant at 10% level Statistically insignificant In the gender regressions life expectancy (LE_65) is measured by gender.

Table 2b: Self-perceived health, employment quality and quantity, life expectancy, and poverty IV approach All Dependent Variable: SPH Model 1 Model 2 Age -0.0720923 * -0.071651 * Age squared 0.0004686 * 0.0004682 * Gender (f=1) 0.3090309 * 0.4199273 * Single (s=1) 0.0041356 -0.0026877 Single (s=1)*gender (m=1) -0.0334686 *** -0.0313888 #-children 0.0016346 *** 0.0024419 ADL -0.1035851 * -0.1063784 * IADL -0.1143164 * -0.1224443 * Eurod (depressive disorder) -0.1329978 * -0.1349582 * BMI -0.0101226 * -0.0106666 * Years of schooling 0.0217177 * 0.02 * ln(income) 0.0309786 * 0.0288621 * Net financial assets 0.000000186 * 0.0000002 * ep26_35_n1 0.0137056 * 0.0134001 * ep26_35_n1*gender (m=0) -0.02521 * -0.0256921 * Employment_pred 0.00776 * 0.0085704 * Ratio HLE_65/LE_65 0.7264991 * 0.7262975 * Ratio HLE_65/LE_65*gender -0.33534 (f=1) * -0.3380737 Poverty (relative) - -10.23945 * Poverty (relative)*gender (f=1) - -1.096308 Wave 6 (d=1) 0.04308 * 0.0451788 * Constant 4.931552 * 5.760375 * Number of observations 60,079 50,731 F-test 488.99 463.99 Adj. R-squared 0.3385 0.326 Root MSE 0.86171 0.87037 * Statistically significant at 1% level ** Statistically significant at 5% level *** Statistically significant at 10% level Statistically insignificant

6. Conclusions Advances in medical knowledge and technology have helped to raise both general life expectancy (LE) and healthy life expectancy (HLE) and are propelling a secular increase in the share of the elderly in the population. These developments present a challenge to PAYGO social-insurance systems in many countries by increasing their default risk (Fehr et al., 2012; Godinez-Olivares et al., 2016). The COVID-19 pandemic seems to have attenuated the increase in LE, especially in its healthy part, although the sharp increase in unemployment and lockout benefits may have degraded many SI reserve funds. One way to tackle the problem of reduced solvency is to raise the retirement age (Pensions at a Glance, 2019). Such a policy, however, suffers from an inherent adverse policy bias. Automatic linkage of RA to some concept of LE is a possible rational response. Our results suggest that the increase in employment that such a response may trigger requires steady improvement in people’s health in tandem with life expectancy, an issue that has not been sufficiently studied. Testing this and other underlying assumptions carefully, we obtain stable results that justify a linkage to HLE or its ratio to LE rather than to LE itself. Analyzing the determinants of self-perceived health (SPH), we find that simultaneity-adjusted employment indeed improves SPH. We also find a serious gender effect of job quality—to women’s detriment—that has not been recognised in the literature of RA linkage. Namely, precarious jobs are particularly widespread among women and their deleterious effect on SPH increases with age, making the typical RA ‘front-loaded’ strategy of raising the retirement age of the older population particularly problematic. Job quality among men is mainly positive, peaking when men reach their mid-fifties and thus possibly justifying a higher RA. In our future research, we intend to use a model of optimisation in the multi-country database of the present study, in which automatic RA adjustment is indeed an important measure of SI sustainability stabilization. As demonstrated by our treatment of job quality, it is crucial for reasons of promoting social justice that the RA adjustment be done in a fair way, accounting for existing gender discrepancies concerning job quality—which for women is really job precarity that escalates with age. This is the reason for the increase in RA to be applied regressively with age, such that the main RA increase occurs at younger ages. A weakness of the proposed strategy is that SI solvency adjusts slowly because the actuarial improvement has to wait until the younger generation reaches the linked retirement age while SI reserves may continue to decline. The strength of this strategy, however, is that it fixes the longevity risk in the fundamental way of a legally cemented rule-based approach, that reestablishes long-term trust in the SI. It is the discretionary approach that is prone to

adjustment fatigue because it leaves the short-term political bias present. To further reduce the risk of excessive decline in reserves during the period required for the young to ‘get older’, a supporting tool is needed in the form of an automatic contribution increase in case the depletion of reserves is deemed persistent. The policy of strengthening SI financial stability is really an attempt to improve social security and intergenerational social justice especially for the future generations that face an increasingly risky world, in which workers are threatened by rapid robotics-supported automation of production processes and must adapt quickly to changing jobs as climate change powers a rapid switch to an uncertain ‘gig economy’. However, SI sustainability is also threatened by other processes that will entail an adequate policy response, one being the commonly found refusal to raise contributions even when social programs are newly introduced. Furthermore, due to past delays in agreeing to raise contributions, many countries’ actuarial deficits have been rising and must be reduced in order to assure SI sustainability. Yet another issue that is not sufficiently based on rational foundations is the design of governmental participation in SI finance. Government participation in financing SI is necessary because SI, being a social organization, typically pays out important benefits not only to those who contribute but also to those incapable of functioning, many of whom are legally exempt from contributions or pay in at reduced rates. Only government can fill the resulting revenue gap. Finally, SI reserves must be maintained at an optimal level in order to respond to unexpected economic slowdowns, recessions, or depressions. These and additional issues need to be addressed in order to assure thorough improvement of PAYGO SI programs in an environment of increasingly social precarity.

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