5 Wealth
In this section we analyse key factors associated with the level of total wealth based on an OLS regression model of the type shown in equation (1). As the survey did not collect data on liabilities, the results relate only to total, as distinct from net wealth.[21] A summary of the significant results is given in Table 5-1 while the complete results of the regression model are set out in Appendix Table C.1.
Of primary interest is the relation between health status and wealth accumulation. Clearly there is a likelihood that those with poorer physical health would tend to have less connection with the labour market. As a result of lower earnings and possibly higher medical expenses, they could be expected to have lower wealth accumulation. An advantage of the regression model used here is that it is possible to control for a wide range of other variables including specifically whether the person was working and whether in receipt of a benefit.
| Dependent variable: Total wealth | |||
|---|---|---|---|
| Explanatory variable | Description | Difference in wealth | Sig. |
| Physical health | 1 unit improvement | +6,000 | *** |
| Male | Relative to female | +104,000 | *** |
| Māori | Relative to European | -169,000 | *** |
| Other ethnicities | Relative to European | -139,000 | ** |
| Years in New Zealand | 1 additional year | +6,000 | *** |
| Main urban | Relative to rural | -300,000 | *** |
| Other urban | Relative to rural | -385,000 | *** |
| Secondary education | Relative to no qualifications | +109,000 | * |
| Separated | Relative to married with non-working spouse | -164,000 | *** |
| Widowed | Relative to married with non-working spouse | -103,000 | * |
| Never married | Relative to married with non-working spouse | -269,000 | *** |
| On a benefit | Relative to those not receiving a benefit | -133,000 | *** |
| Receiving NZ Super | Relative to those not receiving NZ Super | -208,000 | *** |
| Has a super scheme | Relative to those who do not | +83,000 | ** |
| Plans to stop work | Relative to those who do not plan to totally stop work after retirement | +133,000 | *** |
| Negative aspects of retirement | Relative to those who do not attach importance to negative aspects of retirement | -173,000 | *** |
| Income | A $5,000 increase in income | +9,000 | *** |
Notes:
1 Only those explanatory variables that were statistically significant are shown in this table, rounded to the nearest thousand. The full results are in Appendix Table C.1.
2 *** = significant at the 1% level; ** = significant at the 5% level; * = significant at the 10% level.
The results indicate that a one unit improvement in the physical health score is associated with an additional $6,000 of total wealth. It is considered that a five unit change in the score is clinically significant (Ware, 2000). Extrapolating from the regression results yields an estimate of an additional $28,000 in total wealth associated with a five unit improvement in the physical health score. This represents a 10% increase at the mean level of the health score.
That those with better health have higher accumulated total wealth is not surprising. In the first place, those with poorer health may have had less working years and greater medical costs. Furthermore, poor health may be seen as signalling lower life expectancy, and with that less incentive to accumulate as much retirement wealth.
Males have significantly more wealth than females, and Māori and other ethnic groups have less wealth than NZ Europeans. Individuals who are separated or who never married have less wealth than those who are married with a non-working spouse. Those on a benefit have less wealth, and those with a superannuation scheme have higher wealth. Those planning to stop work totally at the time of retirement have higher wealth. Those who place importance on a range of negative aspects of retirement have significantly less wealth.
In the present study no association was found with mental health. Those with higher mental health scores did not report significantly higher levels of total wealth. It is possible that any relationship that might exist was obscured by the fact that in this study total, rather than net, wealth was measured. High levels of liabilities for a given level of total wealth may be associated with poorer mental health.
Carter et al(2008) examine the relation between mental health and net wealth using data from the SoFIE. They use a measure of psychological distress and explore the extent to which this is associated with the level of net wealth, after holding constant a range of socio-demographic characteristics. They find that the odds of reporting high psychological distress are much greater amongst those in the lowest wealth quintile compared to the highest. They conclude that policies which enhance wealth accumulation may have positive benefits for mental health. However, in drawing this conclusion the authors acknowledge that the potential exists for reverse causation such that those with poor mental health may accumulate less wealth through lower levels of labour force participation, lower earnings or higher levels of expenditure.
Anastasiadis (2010) has analysed the association between health and net wealth based on Waves 1 to 3 of the SoFIE data. He finds that poorer health is associated with lower net wealth after controlling for a range of other factors. Those with greater wealth are less likely to suffer health shocks.
Rich people tend to be healthier and live longer. With greater life expectancy they have more incentive to save for retirement and accumulate greater wealth. The finding in this study that better physical health is associated with higher wealth is consistent with this argument, and with similar findings for the USA by Nardi, French and Jones (2006).
Notes
- [21]However, it should be noted that the questionnaire did not ask the respondent to distinguish between assets owned by the respondent and those owned jointly with a partner. This implies the potential for measurement error to have influenced the results. There is no obvious way to estimate the direction of any possible bias.
