4.7 Factors that influence the extent of an expected shortfall in retirement income

In the previous section an estimate was made of the difference between the income a respondent expected to have and that which they felt they would need to either cover their basic living costs or alternatively live comfortably in retirement. Clearly, some respondents will report a shortfall and others a “surplus.” Furthermore, a respondent may feel their expected income to be more than adequate to meet basic needs (that is, an excess), while estimating that with respect to the amount needed to live comfortably they would experience an expected shortfall.

In this section, a regression model is estimated in order to identify those factors associated with the size of any differences (either positive or negative) between respondents expected income and that which is required. Separate equations were fitted for the basic needs and comfortable cases.

In generating observations of the expected shortfall in retirement incomes, respondents had to satisfy three conditions: namely: (a) be 25-years-old and over; (b) had thought at least a little about financial planning for retirement; and (c) were able to give an estimate of their expected income in retirement. From the total sample of 825 observations, 696 were aged 25 and over; of these 573 had done some financial planning; and of these 367 could provide an estimate of their expected retirement income.[13]

In this case, standard regression techniques may result in biased coefficient estimates. Therefore, we instead utilize a Heckman selection model, a procedure specifically designed to control for any sample selection bias that may result from survey routing of the type described above.

The Heckman procedure involves first estimating a “participation equation” involving all 825 survey respondents. In this case, a probit regression was estimated in which the dependent variable assumed a value of one if the three conditions specified above were satisfied, and zero otherwise. This is then used to calculate an adjustment factor known as the inverse Mills ratio that is included in the second-stage regression, in which the size of the expected shortfall (a continuous dependent variable) is estimated.[14] In each stage, the explanatory variables were the large set of independent variables used throughout this study.[15] The results of the second stage regression are summarised in Table 10.

Amongst the standard explanatory variables (eg, age, gender, income, etc.) used throughout this analysis, KiwiSaver membership status is included in an effort to determine whether, and the extent to which, KiwiSaver membership is a factor that explains an expected shortfall or surplus in retirement income.

Consider first the results in the block headed “with respect to basic needs.” Two factors significantly reduced the expected shortfall or increased the excess of expected retirement income relative to that required; these were income and labour force status. Those with higher incomes, other factors equal, were likely to have a smaller shortfall or larger excess. For every $1,000 of extra income, the gap was reduced by $105, indicating a modest but statistically significant effect. Relative to those in fulltime employment, those respondents who were self-employed, unemployed or not in the labour force had expected shortfalls some $10,000 less (or excess of $10,000 more). This could well represent the fact that expectations of retirement income of those not in full-time employment were much more closely matched to their living costs, albeit at more modest levels. Alternatively, particularly in the case of those not in the labour force, this could represent an active choice, given they already have significant wealth or are matched with a high-wealth partner.

Notes:

1. Only variables that were statistically significant for at least one sub-group are shown. Dollar values preceded by a (+) indicate that increasing the associated variable reduces the expected shortfall or increases the excess.

2. +++ or --- significant at the 1% level; ++ or -- significant at the 5% level; + or - significant at the 10% level.

3. ns = not significant.

4. Relative to full-time employment.

5. Relative to New Zealand European.

6. Relative to male.

7. Relative to non-owners.

8. Relative to excellent health.

9. Significant at the 11% probability level.

The second block of results examines the factors that are associated with the relation between expected income and the amount needed for living comfortably. Again income (with a modest effect) and labour force status are associated with a lower shortfall (or greater excess). In this case, however, there is an additional set of significant variables associated with a greater shortfall (or reduced excess). Females are shown to have a shortfall some $3,500 greater than that for males; Maori a shortfall $220 more than Europeans; and those reporting less than excellent health have a significantly increased shortfall.

The health factor creates the largest effect, with those reporting only fair health having a shortfall some $11,600 greater (or an excess smaller by this amount) relative to those reporting excellent health. This could reflect that those with inferior health expect higher medical costs in retirement and hence the amount they perceive they would need for comfortable living, other things equal, would be commensurately greater. At the same time, their poorer health during their working life may impede their ability to accumulate savings for retirement, as a result of reduced labour force participation. There is well documented evidence on the association of health and labour force participation (Enright and Scobie 2010, Holt 2010) and between wealth and health (Anastasiadis 2010, Carter, Blakely et al 2009). However, it is worth noting that this analysis has assumed that the self-assessed health rating provided by respondents which presumably was based on their state at the time of the survey interview, is a reasonable proxy for their expected health in retirement.

A possibly counter-intuitive outcome relates to home ownership. Typically it is thought that those owning a home enjoy a higher standard of living than those who are paying rent in retirement. However, the present finding is that home ownership is associated with a greater shortfall. This could arise if aspirations differ; for example, that home owners set a higher bar for the income they would need to live comfortably.

KiwiSaver membership was, of course, included as an explanatory variable. It was not, however, found to be statistically significant. In other words, all else equal, KiwiSaver membership was not found to improve expected retirement income outcomes; that is, KiwiSaver membership was associated with neither reduced expected shortfalls nor increased excesses of retirement income over the amount respondents required either to meet their basic needs or to be comfortable. This result is robust to any selection bias that may have resulted owing to survey routing and is an important point to bear in mind when considering the results in the following section.