9.2  Factors influencing the labour force: retirement choice

It is well recognised that the decision to leave the workforce and retire is influenced by a wide range of personal and family circumstances. In this study we are particularly concerned to identify the extent to which an individual's health status influences that decision.

Figure 13 illustrates schematically the process of modelling the effect of health on the decision to work. The principal avenue explored in this study is the contemporaneous effect of health status on working (as indicated by the bold arrow). The models endeavour to isolate this effect while holding constant a range of other “confounding” variables indicated around the periphery. The dashed arrows indicate potentially important linkages from both previous health states and earlier labour market experience. However, as the data used here are cross-sectional, inclusion of these lagged effects will need to await data from future waves of the HWR survey so that longitudinal observations can be incorporated.

Figure 13: Modelling the effect of health on labour force participation

A key message from this schematic view is that health status may influence the decision to work in a number of ways, as argued by Dwyer and Mitchell (1998). Poorer health may result in lower earnings owing either to reduced productivity or fewer hours worked, or some combination of the two. Poorer health may alter the preferences for leisure versus consumption, or make work more demanding. All these factors would tend to raise the utility of leisure and lead to earlier retirement.

In contrast, the needs of a person with poorer health might be such that they opt to continue working at least part-time to maintain consumption, thereby postponing retirement. The onset of a decline in health may lead an individual to alter the perception of their life expectancy. This may lead to an earlier retirement than would otherwise have occurred had their health not deteriorated. However, for some, continuing to work may provide a psychological boost which itself could mitigate, at least in part, the effects of poorer health. [26] In short, the effect of health on the decision to remain in the labour force is theoretically ambiguous. We are left to appeal to the evidence, recognising that the limitations of both the data and the models may not necessarily result in an unequivocal outcome.

There has been a long-run trend throughout the 20th century toward earlier retirement. Clearly, many factors shape the final decision. What effect does better health have? Does it mean that life expectancy is extended and hence the retirement date is shifted out so that working life simply remains proportional to life expectancy? Bloom, Canning and Moore (2004) extend the standard life cycle model to show that improved health hasbeen associated with a less than proportional increase in working life; ie, more time is spent in retirement as life expectancy rises. On one hand, better health means that the disutility of work is less, so retirement age could be expected to rise. But these authors note that a longer working life means a greater effect of compound interest earnings on savings, creating a wealth effect leading to more leisure (earlier retirement) and higher consumption (implying lower savings).

In a UK study, adverse health shocks are found to be an important predictor of individual retirement behaviour (Disney, Emmerson and Wakefield, 2003). This study relied on self-rated health status, but attempted to deal with the problem of endogeneity by using a constructed measure of a health stock Similar findings are reported by Banks and Tetlow (2008) who demonstrate that it is the onset of a major health condition rather than a chronic illness that increases the odds a person will leave full-time work.

Clearly, many factors shape the final decision to continue participating in the labour force. The final decision is an amalgam of health status (including that of family members), wealth levels, interest rates, the disutility of work, the extent of publicly provided pensions, health services and long-term care, and the strength of the bequest motive.[27] For this reason, it is important to use a multi-variate framework, if there is to be any chance of isolating the effect of a particular variable on the decision to retire.

We now turn to the application of logit models whose aim is to isolate the effect of health on the decision to remain in the labour force, while holding constant the influence of a wide range of other factors that may potentially influence the decision taken by an individual. These effects were estimated by fitting a logit model of the form:

Pr(W) = W(H^p,H^m,Z) + ε (13)

where the probability of working is postulated to depend on the physical and mental health component scores (H^p, H^m respectively) and a vector (Z) of control variables (including age, gender, marital status, region, migrant status, education level, benefit status, income, wealth, etc) plus a random error term (ε).

A summary of the main significant factors associated with the decision to work (defined as either full-time, part-time or seeking work) for males and females is given in Table 9-2. Estimates of the marginal effects are given in Section 9.3. Both physical and mental health are critical factors influencing the decisions by males whether or not to work. However, only their physical health status appears to influence the decisions of females.

While Māori men and women were less likely to be in the workforce, the differences were not significant. Having a tertiary education significantly raised the probability that both males and females would be in the labour force.

Relative to being married with a non-working spouse, virtually all other marital categories are associated with a higher chance of being in work. For both men and women, being separated or widowed significantly raised the probability of working, as did having a working spouse.

The receipt of a benefit or NZS lowers significantly the chance of being in the workforce for both males and females. While the level of total wealth typically has no effect, males are more likely to be in work (full- or part-time or seeking) when the income of other household members is higher. For males this is also true if they are in receipt of other sources of retirement income. Only half as many women as men have other superannuation schemes, and the effect for females, while still negative, is very much smaller and not significant.

It is notable that the effect of wealth is not significant. One might have expected that those with a taste for work are likely to have accumulated a greater stock of wealth. If this were the case, we would expect to find a positive relation. While it is true that the effect is typically found to be positive in this study, the coefficients for wealth are not statistically significant. There are at least three issues, however, that may have mitigated against finding a significant role for wealth. Ideally, we require a measure of the net stock of wealth but as the HWR survey did not collect estimates of liabilities we are restricted to using gross wealth. Second, the response rate on estimates of the value of major assets was relatively low, as respondents were invited to provide this information only if they so wished. Third, the NZS system provides a lifetime defined benefit on a universal basis, free of income or asset testing. As shown by Scobie et al, (2005) the implied stock of wealth associated with NZS forms a major share of the total retirement wealth of many New Zealanders. The incentive to accumulate other forms of wealth is reduced, relative to that which would prevail in the absence of such a state pension scheme. As a consequence it is possible that some of what is actually a wealth effect is being picked up by the highly significant effect of receiving NZS. We found some tentative evidence to support this explanation. As shown in Table 9-2, both males and females in receipt of NZS tend to have a lower probability of working, after controlling for their level of wealth and an extensive set of other variables.

A notable finding is that health status, as measured by the mental component score, has no significant effect on the labour force participation decisions of women. This stands in marked contrast to the results for males, whose decision to work is strongly related to both their physical and mental health scores.

Notes:
¹ Only those explanatory variables that were statistically significant are shown in this table.
² +++ or --- = significant at the 1% level; ++ or -- = significant at the 5% level; and + or - = significant at the 10% level.
³ The table of full results is given in Appendix Table C.14.