Wealth

Table 14.4 shows the distribution of wealth among our sample population of pen-sioners aged 65–84 residing in Switzerland. One in four respondents owns less than CHF 60′000, while one in three respondents has more than CHF 500,000 in savings or investments. Among those who responded ‘not having any wealth’, 30% are income-poor, compared to 6% among the wealthiest category. In terms of self- assessment, the difference between the proportions of vulnerability in the lowest (47%) and the highest wealth category (4%) corresponds to a factor of 10. The perceived angle of vulnerability displays a disparity of almost identical size between the highest and the lowest category of wealth: 44% of those who own ‘nothing’ are worried about their finances, compared to 9% of those owning more than half a mil-lion Swiss francs.

As we could expect, the effect size of wealth is strong, negative and highly sig-nificant (p < 0.001) for all three measures of economic vulnerability. But interest-ingly, it is greatest for the Self-Assessed Measure (gamma = −0.63), followed by the Perceived Measure (gamma  = −0.48) and lastly the Objective Measure (gamma = −0.43).

Figure 14.1 shows the prevalence of wealth categories by vulnerability type, which have been ordered by the size of proportion of the lowest wealth category.

Type ABB takes the lead in this ranking with 54% of this type not having any sav-ings, followed by type BBB (46%). Bearing in mind the strong correlation between income and wealth, a close look at all types featuring objective vulnerability (types BXX) is imperative: on the upper side of the graph we see that among type BAA, 16% own no wealth but a relatively high share (42%) are in wealth categories above 150,000. The important difference between type BAA and BBB seems to support our general hypothesis stating that the income-based measure does not sufficiently take into account other relevant resources and that, in contrast, the self-assessed

Table 14.4 Sample distribution by wealth category and measures of economic vulnerability Wealth

Sample distribution obj_ev sa_ev perc_ev

n % % vulnerable within wealth

(almost) nothing 195 12.0 29.7 47.2 43.6

<60,000 223 13.7 23.3 23.8 31.8

60,000–150,000 284 17.4 19.4 12.3 14.8

150,000–500,000 422 25.9 11.1 6.9 10.9

>500,000 507 31.1 5.9 4.3 9.3

Total 1631 100 14.8 14.2 17.8

Gamma −0.43 −0.63 −0.48

z 10.7 17.6 12.3

p <0.001 <0.001 <0.001

Kendall’s tau-b −0.19 −0.30 −0.24

z 9.1 −14.4 11.1

p <0.001 <0.001 <0.001

174

angle performs better at revealing the existence of coping resources (in this case, the availability of financial assets).

At this point, it is of general interest to look at the most frequent combinations of categories of wealth and income. Table 14.5 confirms a clustering of high-income categories with high-wealth categories at the lower right corner, peaking at the inter-section of the highest income with the highest wealth category (18%).

At the opposite end of the spectrum, among the financially less privileged, the combinations of income and wealth are more diverse: while most individuals with modest monthly household incomes are found to have small levels of savings, low levels of wealth is similarly prevalent among middle income classes.

The next step naturally consists in taking a closer look at the income-wealth constellations by vulnerability type, in order to further examine how stock and flow of resources interact and reflect in subjective appraisals. Table 14.6 shows the fre-quency of all possible combinations between wealth and income categories in our sample population (N = 1631).

At first sight it stands out that several vulnerability types occur in a very concen-trated manner, part of which is naturally the result of the coding of the lowest

54.1

1. nothing or close to nothing 2. < 60,000 CHF 3. 60,000 - 150,000 CHF 4. 150,000 - 500,000 CHF 5. > 500,000 CHF

Fig. 14.1 Distribution of wealth categories, by vulnerability type

Table 14.5 Distribution of combinations between wealth and income categories

Wealth Income

Count 1. <2400 2. 2400–3600 3. 3600–4800 4. >4800

1. <60,000 110 139 123 46

2. 60,000–150,000 55 64 97 68

3. 150,000–500,000 47 77 162 136

4. >500,000 30 45 137 295 1631

%

income category as ‘BXX’. The fact that BAA is exclusively found among constel-lations 1 to 4 is an example of this; however, the concentration of BBB in the very lowest category (constellation 1. = 36 respondents) lends weight to the congruence of the three angles of measurement. Two other wealth-income constellations stand out: type ABB is highly concentrated in constellation 6 (39 respondents), and type AAB is clearly most often found for constellation 9 (24 respondents), both of which are combinations based on wealth category ‘less than 60,000’. As for type ABB, the fact that as many as 50% of this group are in the low wealth-income constellation

‘<60,000/2400–3600’ provides strong evidence for the potential relevance of the typology in terms of what it is able to reveal about coping resources: in the present constellation we can see the stylized example of someone with an income just above the poverty line, who experiences economic strain (sa_ev), resulting in stress (perc_

ev) because low levels of savings do not permit to sustainably cope with the situation.

Regarding type AAB, we are now onto a possible explanation for this type that makes little sense theoretically (see Table 5.2) and for which the plausible explana-tion of higher levels of neuroticism was rejected. Indeed, it seems that for these 24 respondents, not having a lot of savings provokes financial worry, despite the fact

Table 14.6 Absolute frequencies of wealth-income constellations, by vulnerability type

Fortune/income BBB BAA ABB ABA AAB BAB BBA AAA Total %

1. <60,000/<2400 36 37 15 22 110 6.8

2. 60,000–150,000/<2400 10 32 5 8 55 3.4

3. 150,000–500,000/<2400 4 32 4 7 47 2.9

4. >500,000/<2400 5 18 4 3 30 1.8

5. <60,000/2400–3600 39 23 15 60 137 8.4

6.

60,000–150,000/2400–3600

3 8 5 48 64 3.9

7.

150,000–500,000/2400–

3600

6 5 8 57 76 4.7

8. >500,000/2400–3600 2 3 4 36 45 2.8

9. <60,000/3600–4800 15 5 24 79 123 7.6

10.

60,000–150,000/3600–4800

1 2 13 80 96 5.9

11.

150,000–500,000/3600–

4800

2 2 14 144 162 10.0

12. >500,000/3600–4800 1 4 12 119 136 8.4

13. <60,000/>4800 3 2 9 32 46 2.8

14. 60,000–150,000/>4800 1 2 4 61 68 4.2

15. 150,000–500,000/>4800 1 2 7 126 136 8.4

16. >500,000/>4800 4 18 272 294 18.1

1625 100

176

that the wording of the survey question clearly states a very short time horizon.⁴ Possibly, these respondents fear that they have to start consuming their wealth in order to be able to maintain their living standard, which seems at a comfortable level. Still within group AAB, we must not ignore another, clearly distinct sub- group: 18 respondents are worried or very worried about their current finances, while finding themselves in the highest possible wealth-income situation.

The analysis of the variable wealth, and particular in interaction with household income, confirms the overall importance of financial stocks that was discussed in the theoretical part. Firstly, the strong correlation between monthly household income and wealth was confirmed: the concordance of income and wealth is par-ticularly marked in the wealthier segment while lower wealth levels are common throughout the lower and middle range of income categories. However, by far most respondents that are objectively vulnerable are also found in the lowest wealth cat-egory. Secondly, the presence of assets is exceedingly important for the subjective appraisal of economic vulnerability. This finding is in line with our theoretical model, which posits that the self-assessed angle takes into account economic resources other than monthly income, and that the perceived angle reflects whether coping resources (such as wealth consumption) are thought to be sustainable in the long run.

Appendix

Appendix 14.1: Sample Distribution by Financial Support