Tag: Old-Age Poverty
Widowhood in Poland: Reforming the Financial Support System
Drawing on a recent Policy Paper, we analyse the degree to which the current system of support in widowhood in Poland limits the extent of poverty among this large and growing group of the population. The analysis is set in the context of a proposed reform discussed lately in the Polish Parliament. We present the budgetary and distributional consequences of this proposal and offer an alternative scenario which limits the overall cost of the policy and directs additional resources to low-income households.
Introduction
Losing a partner usually comes with consequences, both for mental health and psychological well-being (Adena et al., 2023; Blanner Kristiansen et al., 2019; Lee et al., 2001; Steptoe et al., 2013), and for material welfare. Economic deprivation may be particularly pronounced in cases of high-income differentials between spouses and in situations when the primary earner – often the man – dies first. Many countries have instituted survivors’ pensions, whereby the surviving spouse continues to receive some of the income of her/his deceased partner alongside other incomes. The systems of support differ substantially between countries and they often combine social security benefits and welfare support for those with lowest incomes.
In this Policy Brief we summarise the results from a recent paper (Myck et al., 2024) and discuss the material situation of widows versus married couples in Poland. We show the degree to which the ‘survivors’ pension’, i.e. the current system of support in widowhood, limits the extent of poverty among widows and compare it to a proposed reform discussed lately in the Polish Parliament, the so called ‘widows’ pension’. In light of the examined consequences from this proposal we relate it to an alternative scenario, which – as we demonstrate – brings very similar benefits to low-income widows, but, at the same time, substantially reduces the cost of the policy.
Reforming the System of Support in Widowhood
Our analysis draws on a sample of married couples aged 65 and older from the Polish Household Budget Survey – a group representing a large part of the Polish population (almost 1,7 million couples). Each of these couples is assigned to an income decile, depending on the level of their disposable income. Incomes of 9.5 percent of the sample locate them in the bottom decile, i.e. the poorest 10 percent of the population, while 4.4 percent of these older couples have incomes high enough to place them in the top income group – the richest 10 percent of the population.
Next, in order to examine the effectiveness of the different systems of support, we conduct the following exercise: incomes of these households are re-calculated assuming the husbands have passed away. This simulates the incomes of the sampled women in hypothetical scenarios of widowhood. The incomes are calculated under four different systems of support as summarized in Table 1.
Table 1. Modelled support scenarios.
Using these re-calculated household incomes, we can identify the relative position in the income distribution in the widowhood scenario as well as the poverty risk among widows under different support systems.
The change in the relative position in the income distribution following widowhood under the four support systems is presented in Figure 1. The starting point (the left-hand side of each chart) are the income groups of households with married couples aged 65+, i.e. before the simulated widowhood. The transition to the income deciles on the right-hand side of each chart is the result of a change in equivalised (i.e. adjusted for household composition) disposable income in the widowhood simulation, under different support scenarios (I – IV).
Figure 1. Change in income decile among women aged 65+, following a hypothetical death of their husbands.
Figure 1a shows that, without any additional support, the financial situation of older women would significantly deteriorate in the event of the death of their spouses (Figure 1a). The share of women with incomes in the lowest two deciles would be as high as 54.7 percent (compared to 17.5 percent of married couples). The current survivor’s pension seems to protect a large proportion of women from experiencing large reductions in their income (Figure 1b), although the proportion of those who find themselves in the lowest two income decile groups more than doubles relative to married couples (to 38.3 percent). The widow’s pension (Figure 1c) offers much greater support and a very large share of new widows remain in the same decile or even move to a higher income group following the hypothetical death of their spouses. For example, with the widows’ pension, 8.0 percent of the widows would be in the 9th income decile group and 5.3 percent in the 10th group, while in comparison 7.0 and 4.4 percent of married couples found themselves in these groups, respectively. The proposed alternative system (Figure 1d) raises widows’ incomes compared to the current survivor’s pension system, but it is less generous than the system with the widow’s pension. At the same time 4.6 percent and 3.4 percent of widows would be found in the 9th and 10th deciles, respectively.
Importantly, the alternative support system is almost as effective in reducing the poverty risk among widows as the widow’s pension. In the latter case the share of at-risk-of poverty drops from 35.3 percent (with no support) and 20.7 percent (under the current system) to 11,0 percent, while under the alternative system, it drops to 11.8 percent. Because the alternative system limits additional support to households with higher incomes, this reduction in at-risk-of poverty would be achieved at a much lower cost to the public budget. We estimate that while the current reform proposal would result in annual cost of 24.1 bn PLN (5.6 bn EUR), the alternative design would cost only 10.5 bn PLN (2.5 bn EUR).
The distributional implications of the two reforms are presented in Figure 2 which shows the average gains in the incomes of ‘widowed’ households between the reformed versions of support and the current system with the survivor’s pension. The gains are presented by income decile of the married households. We see that the alternative system significantly limits the gains among households in the upper half of the income distribution.
Figure 2. Average gains from an implementation of the widow’s pension and the alternative system, by income decile groups.
Conclusions
While subjective evaluations of the material conditions of older persons living alone in Poland have shown significant improvements, income poverty within this groups has increased since 2015. This suggests that the incomes of older individuals have not sufficiently kept up with the dynamics of earnings of and social transfers to other social groups in Poland. As shown in our simulations, the current widowhood support system substantially limits the risk of poverty following the death of one’s partner. However, while the current survivor’s pension decreases the poverty risk from 35.3 percent in a system without any support to 20.7 percent, the risk of poverty among widows is still significantly higher compared to the risk faced by married couples.
The simulations presented in this Policy Brief examine the implications of a support system reform; the widow’s pension which is currently being discussed in the Polish Parliament, as well as an alternative proposal putting more emphasis on poorer households. The impactof these two reforms on the at-risk-of poverty levels among widowed individuals would be very similar, but the design of the alternative system would come at a significantly lower cost to the public budget. The total annual cost to the public sector of the widow’s pensions would amount to 24.1 bn PLN (5.6 bn EUR) while our proposed alternative would cost only 10.5 bn PLN (2.5 bn EUR) per year.
An effective policy design allowing the government to achieve its objectives at the lowest possible costs should always be among the government main priorities. This is especially important in times of high budget pressure – due to demographic changes or other risks – as is currently the case in Poland.
References
- Adena, M., Hamermesh, D., Myck, M., & Oczkowska, M. (2023). Home Alone: Widows’ Well-Being and Time. Journal of Happiness Studies.
- Blanner Kristiansen, C., Kjær, J. N., Hjorth, P., Andersen, K., & Prina, A. M. (2019). Prevalence of common mental disorders in widowhood: A systematic review and meta-analysis. Journal of Affective Disorders, 245, 1016–1023.
- Lee, G. R., DeMaris, A., Bavin, S., & Sullivan, R. (2001). Gender Differences in the Depressive Effect of Widowhood in Later Life. The Journals of Gerontology: Series B, 56(1), S56–S61.
- Myck, M., Król, A. & Oczkowska, M. (2024). Reforming financial support in widowhood: the current system in Poland and its potential reforms. FREE Network Policy Paper Series.
- Steptoe, A., Shankar, A., Demakakos, P., & Wardle, J. (2013). Social isolation, loneliness, and all-cause mortality in older men and women. Proceedings of the National Academy of Sciences, 110(15), 5797–5801.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Old-Age Poverty and Health – How Much Does Income Matter?
The question concerning the material situation of older people and its consequences for their wellbeing seems to be more important than ever. This is especially true given rapid demographic changes in the Western World and economic pressures on governments to reduce public spending. We use data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to examine different aspects of old-age poverty and its possible effects on deterioration in health. The data contains information on representative samples from 12 European countries including the Czech Republic and Poland. We use the longitudinal dimension of the data to go beyond cross sectional associations and analyze transitions in health status controlling for health in the initial period and material conditions. We find that poverty matters for health outcomes in later life. Wealth-defined and subjective poverty correlates much more strongly with health outcomes than income-defined measure. Importantly subjective poverty significantly increases mortality by 58.3% for those aged 50–64 (for details see Adena and Myck, 2013a and 2013b).
Measuring Poverty
When measuring poverty, the standard approach is to define the poverty threshold at 60% of median equalized income. This standardized measure offers some advantages, such as simplicity and comparability with already existing studies. However, there are valid arguments against its use when analyzing old-age poverty. The permanent-income theory provides arguments against current income as a major determinant of quality of life of older people. Moreover, poverty defined with respect to current income while taking account of household size through equalization, ignores other important aspects of living costs such as disability or health expenditures. Additionally, most analysis using income-poverty measures ignore such aspects as housing ownership and housing costs.
Our analysis examines different aspects of poor material conditions of the elderly. The first poverty definition refers to respondents’ wealth as an alternative to income-defined poverty. Poor households, defined with reference to wealth (“wealth poverty” – WEALTH), are those that belong to the bottom third of the wealth distribution of the sample in each country. For this purpose, household wealth is the sum of household real assets (net of any debts) and household gross financial assets. Secondly, we compare the above poverty measures to a subjective measure of material well-being. This measure is based on subjective declarations by respondents, in which case (“subjective poverty” – SUB) individuals are identified as poor on the basis of a question of how easily they can make ends meet. If the answer is “with some” or “with great” difficulty, individuals in the household are classified as “poor”.
One reflection of potential problems with the standard income poverty measure becomes visible when it is compared with the subjective measure. The graph below shows the differences in country rankings when using one or the other poverty measure. The country with the greatest disproportion is Czech Republic. While being ranked as second according to the income measure, it is ninth according to the subjective measure.
Figure 1. Country Ranks in Old-Age Poverty According to an Income versus a Subjective Measure Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0).Even more striking is the fact that the differences between ranks are not because of over or under classification of individuals as poor, but rather because of misclassification. Figure 2 shows that there is little overlap between different poverty measures. The share of individuals classified as poor according to all three measures is only 7.95%, whereas it is 60% according to at least one of the measures.
Figure 2. Poverty Measure Overlap Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0).Measuring Well-Being
We examine three binary outcomes measuring the well-being of the respondents – two reflecting physical health, and one measuring individuals’ subjective health. The two measures of physical health are generated with reference to the list of twelve symptoms of bad health and the list of twenty-three limitations in activities of daily living (ADLs). In both cases, we define someone to be in a bad state if they have three or more symptoms or limitations. The two definitions are labelled as: “3+SMT” (three or more symptoms) and “3+ADL” (three or more limitations in ADLs). Subjective health “SUBJ” is defined to be bad if the subjective health assessment is “fair” or “poor”. Finally, we also analyze mortality as an “objective” health outcome.
Poverty and Transitions in Well-Being and Health
There is some established evidence in the literature that poverty negatively affects health and other outcomes at different stages of life.[1] At the same time, there is little evidence on how the choice of the poverty measure might result in under- or over-estimation of the effects of poverty. We address this question by examining different poverty measures as potential determinants of transitions from good to bad states of health.
The results confirm that living in poverty increases an individual’s probability of deterioration of health. In a compact form, Figure 3 presents our results from 12 separate regressions (4 outcomes, three poverty measures). Here we report the odds ratios related to the respective estimated poverty dummies. Individuals classified as poor according to the income measure are 37.7% more likely to report bad subjective health in a later wave of the survey than their richer counterparts; they are 4.5% more likely to suffer from 3 or more symptoms; 18.7% more likely to suffer from 3 or more limitations; and 5% more likely to die. The last three effects, however, are not statistically significant.
In contrast, the effects of wealth-defined poverty and subjectively assessed poverty are 2-8 times stronger than those of income poverty, and they are also significant for all outcomes but death. Overall, wealth-defined poverty and subjective assessment of material well-being strongly correlate with deterioration in physical health (exactly the same goes for improvements in health, see Adena and Myck 2013b).
Figure 3. Poverty and Transitions from Good to Bad States Overlap Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).Poverty and Mortality in the Age Group 50-64
Our analysis reveals differences between age groups and confirms the decreasing importance of income (and thus income defined poverty) with age. As compared to the average effects presented in Figure 3, for the younger age group 50–64 income poverty proves more important as a determinant of bad outcomes, with transition probabilities between 20 and 40% for all outcomes (see Figure 4). The magnitudes are closer to those of other poverty measures, but still lower in all cases. Importantly, we find that wealth-defined and subjective poverty is an important determinant of death in the age group 50–64.
Figure 4. Poverty and Transitions from Good to Bad States 50-64 Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).Conclusions
The role of financial conditions for the development of health of older people significantly depends on the measure of material well-being used. In this policy brief, we defined poverty with respect to income, subjective assessment, and relative wealth. Of these three, wealth-defined poverty and subjective assessment of material well-being strongly and consistently correlate with deterioration and improvements in physical and subjective health. We found little evidence that relative income poverty plays a role in changes in physical health of older people. This suggests that the traditional income measure of household material situation may not be appropriate as a proxy for the welfare of older populations, and may perform badly as a measure of improvements in their quality of life or as a target for old-age policies. To be valid, such measures should cover broader aspects of financial well-being than income poverty. They could incorporate aspects of wealth and the subjective assessment of material situations as well as indicators more specifically focused on the consumption baskets of the older population.
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References
- Adena, Maja and Michal Myck (2013a): “Poverty and transitions in key areas of quality of life”, in: Börsch-Supan, Axel, Brandt, Martina , Litwin, Howard and Guglielmo Weber (eds.) “Active Ageing and Solidarity between Generations in Europe – First Results from SHARE after the Economic Crisis.”
- Adena, Maja and Michal Myck (2013b) Poverty and Transitions in Health, IZA Discussion Paper 7532, IZA-Bonn.