4.1  Including those living overseas

Most overseas studies of intergenerational mobility have included only those living in their home country with data not being collected on those who have emigrated (Jäntti, et al., 2006, pp. 28-31). In contrast, the Dunedin data allows us to explore what has happened to all people, irrespective of the country they are living in. Compared to other developed countries, New Zealand has proportionately high emigration (Bedford, 2001, p. 52). Excluding the 24% of the cohort who were living overseas at age 32 could therefore risk inaccurately measuring intergenerational mobility for New Zealanders. Many New Zealanders who live overseas in their twenties and early thirties also consider themselves to be only temporarily away, undertaking what they call their “overseas experience”, and plan to return to New Zealand (Conradson and Latham, 2005, p. 167; Lidgard, 2001; Milne, Poulton, Caspi and Moffitt, 2001). Although about 60% of those who were overseas at age 32 were in Australia, where New Zealand has a large and relatively settled expatriate population, the remainder were in countries that migration and census data shows most New Zealanders return home from during their late twenties or their thirties. Because New Zealand has such high emigration, the results for the entire group are probably more comparable to the population of similar overseas studies than the results for just those who were living in New Zealand.

Model four therefore shows the effect of fathers' log incomes on the log incomes of males. This model generates an intergenerational income elasticity estimate of 0.290. Although this point estimate is slightly higher than for model one, because the confidence intervals overlap we cannot say the results are different. The equivalent elasticity for females is 0.215 (model five). Unlike the results for women living in New Zealand (model two), the model five results for all women are statistically significant at a 5% level. However, the proportion of variance explained is extremely low at only 0.7%. Indeed, the probability (p value) of 0.14 associated with the F statistic indicates that the explanatory variables (father's income and father's age) do not reliably predict the dependent variable.[20]

To maximise the sample size, the model six results include male and female participants, irrespective of the country they were living in, and without the statistically insignificant controls for the ages of participants' fathers. This model generated an intergenerational income elasticity of 0.264 (95% confidence interval: 0.143 to 0.385).

People who were born in Dunedin and who were living overseas at age 32 tended, on average, to have higher incomes (and to work in higher status occupations) than those living in New Zealand. Further details on these differences are in Section 8.1.4 of the Appendix. The data for women included in model five did not show a statistically significant difference in the proportion of women in New Zealand and overseas who were not participating in the labour force. However, if we include cases where father’s income data was missing we can be confident at a 10% level that women in New Zealand were more likely to be homemakers than women living overseas. Further research might uncover more subtle differences in labour market participation between these groups.

Because of limited data and because the incomes of children's fathers have tended to be higher and more stable than those of their mother, most overseas studies of intergenerational income mobility have used the income of fathers as the main explanatory variable. However, studying the combined effect of both parents' incomes arguably produces a richer picture of intergenerational mobility and in some countries increases the magnitude of estimates (Corak, 2006, pp. 9, 11). Many participants had mothers who were working (Silva, 1996, pp. 49-50), and this affected their standard of living when they were growing up. In model seven, the relationship between parents’ combined income and the income of their child or children, irrespective of the country they were living in, was therefore tested. The intergenerational income elasticity estimate for model seven of 0.272 is very similar to the 0.264 result for model six, showing that changing the explanatory variable had very little effect. Changing the explanatory variable for the other models to parents’ combined income (not shown) also had little effect on the results. This is not entirely surprising: when participants were 13 and 15 on average fathers received 75% of the total income of Dunedin Study families. There was also a 0.20 correlation between the unlogged incomes of mothers and of fathers, indicating assortative coupling. In other words, the data suggests that high income men and high income women tended to be living together.

To better understand the effects of changes in different variables, we will look at two further examples. In 2008 values, the average family income in the Dunedin Study when the participants were 13 and 15 was about $70,000 while the highest reported family income was imputed at $161,000. Suppose a man from Dunedin had parents who were in the top income bracket when he was aged about 14. In model seven, assuming linearity, this would result in that man's income at age 32 (on average) being about $13,000 higher than if he had been brought up in an average income family. For a woman, the equivalent income difference would be $7,000, on average. This difference between men and women occurs because the model controls for the tendency for men to earn more than women.

In model eight we added variables for people's educational qualifications, while in model nine we added variables for the country they lived in. These changes increased the proportion of variance explained to 25%. The effects of educational qualifications on income are discussed in the next section of this paper. In model nine, the effect on a person's income of living overseas, and in particular the effect of living in Britain, are affected by the value we impute to the top income category. We are therefore reluctant to calculate the apparent economic benefits of living overseas. Previous research has also found that participants who had lived overseas had better physical and mental health than those who had remained in New Zealand (Milne, et al., 2001, p. 450). This suggests that some of the income effects our model has linked to country of residence may be caused by other variables. When we ran separate regressions for people in New Zealand, Australia, Britain and all other countries combined, the overlapping confidence intervals suggested there was no statistically significant difference between intergenerational income mobility rates for people in different countries. Median incomes and mean SES for people living in different countries are listed in Section 8.1.4.

Models six and seven contain our preferred estimates of the intergenerational income elasticity for all people from Dunedin. Earlier models give estimates for particular groups of individuals. For instance, models four and five are respectively the best estimates for all men and women. Although models eight and nine explain substantially more of the variation in incomes, adding controls for education reduces the size of the intergenerational income elasticity. This is because individuals from better-off families tend to have higher levels of educational attainment. The estimates of the intergenerational income elasticity in models eight and nine will therefore not capture the full parental income effect. Education will also have a direct effect on an individual's income, but disentangling these effects is difficult. Section 4.2 discusses this in more detail.