3  The New Zealand data

No representative nationwide New Zealand datasets on the incomes of children's parents and on the incomes of these children when they are adults are currently available to researchers. However, we are able to test intergenerational economic mobility using two datasets. These datasets are income data from the Dunedin Multidisciplinary Health and Development Study of people born in Dunedin in 1972-73; and occupation data from the nationwide 1996 New Zealand Election Study (NZES).[10] This section describes these datasets.

3.1  The Dunedin Study data

The Dunedin Study is a cohort study of the population of children born between April 1972 and March 1973 in Dunedin who were still living there at age three. Almost all eligible children have participated in the study. When the participants were growing up Dunedin had the fourth biggest population of any New Zealand metropolitan centre. The study included 1,037 children from a full range of economic backgrounds (Silva and McCann, 1996, pp. 11-13).

Data from similar cohort studies, including a study of people from one city, has also been the main source for intergenerational income mobility estimates in Britain (Atkinson, 1980, p. 205; Blanden, et al., 2007, p. C46). New Zealand household economic surveys only capture the incomes of parents and their children if they are living at the same address. They therefore do not produce a random sample of adult children and of their parents. New Zealand also does not have large intergenerational administrative datasets on people’s incomes that are available for research purposes (Lane and Maloney, 2002; Wilson, 2002). This makes the Dunedin Study income data extremely valuable.

Although the Dunedin Study sample is most representative of children born in Dunedin at the time the participants were born, in many respects Dunedin is also a microcosm of New Zealand. Indeed, when the participants were born the occupational structure of Dunedin closely resembled New Zealand as a whole (Silva and McCann, 1996, pp. 2, 10, 14). Health outcomes for the participants at ages 21 and 26 were usually not statistically different from those of other New Zealanders of the same age, but the study is under-representative of Māori and Pacific peoples compared to New Zealand’s entire population (Poulton, Hancox, et al., 2006, pp. 1, 9). Irrespective of where they live in New Zealand, people have the same entitlements to welfare payments and to public education and health services, while the central government also sets employment laws. By the time they were 21, a third of the participants were living outside Dunedin (Silva and McCann, 1996, pp. 14-15). At age 32 only 38% were living in Dunedin, 76.7% were living in New Zealand and 23.7% were living overseas. The Dunedin Study considers its participants to be “broadly representative” of New Zealand children born in 1972-73 (Poulton, et al., 2006, p. 9).

This paper treats the Dunedin Study data as if it were a random sample of people born in Dunedin in the early 1970s, rather than as a sample of all New Zealanders born during this period. However, because Dunedin is reasonably similar to other parts of New Zealand, and because the participants have been geographically mobile, the results from the Dunedin Study are useful for understanding intergenerational income mobility by New Zealanders. Intergenerational income mobility studies in other countries that have used regional datasets have tended to generate similar results to later studies that have used larger national datasets, and that apart from using a national dataset have been similar in other methodological respects. Although there is some evidence of regional differences in intergenerational income mobility in the United States and in Finland (Mayer and Lopoo, 2008, pp. 149, 151, 154-155; Pekkarinen, et al., 2006, pp. 5, 10), New Zealand has much fewer regional differences in public policy than these two countries (OECD, 2009, pp. 56-57). Further discussion of this topic is in Section 8.1.1.

Existing Dunedin Study results show high rates of intra-generational mobility, with only 41% of participants remaining in the same three-group SES category between the ages of 0, 5 and 9 (Parnicky, Williams and Silva, 1987, p. 121). The Pearson's correlation between childhood SES and adult SES was 0.32 (Melchior, et al., 2007, p. 969).[11]

We used data on parents' incomes when the participants were aged 13 and 15, together with data on the incomes of participants from their most recent assessment at age 32. When data on the incomes of participants' parents was collected the average age of mothers was 40 and the average age of fathers was 42.[12] In our dataset, parents are therefore more likely than their children to be in their peak earning years. Overseas researchers have found a decrease in intergenerational mobility when people are in their peak earning years, compared to when they were younger. This is because early-career data understates the long-term economic situation of better educated workers who tend to have higher life-time earnings growth rates (Jäntti, et al., 2006, p. 3). Admittedly, 32 is similar to the age of children used in some overseas studies (Blanden, 2008, pp. 5, 42-44; Corak, 2006, pp. 10, 61). However, increases in educational attainment and the increased tendency of many young people to travel and to move between jobs means that the age-earnings profile of people has been changing (Grawe, 2006, p. 565). Indeed, historically many New Zealand men have only reached their peak earning years in their mid-thirties, and the peak earning years for women have traditionally been in their forties. The age-earnings profiles for both New Zealand men and women have also changed over time, and the median earnings profile for women born in the early 1970s was considerably higher at 30 than for women born just five years earlier (Coleman, 2006, pp. 14-15, 29-30). This makes it difficult to assess whether we are measuring participants’ incomes at an appropriate age.

We considered also seeking income data from the Christchurch Health and Development Study of 1,265 children born in Christchurch in mid-1977. However, because the most recent assessment of Christchurch Study participants was when they were 30, the Christchurch data would currently appear to be less suitable than the Dunedin data.

At age 32, 94% of those assessed by the Dunedin Study at age three were still participating. We lose some additional cases, mainly because of non-reporting of fathers' incomes when the participants were 13 and 15. This reflects the intensely personal nature of information about people's income, with the pattern of results suggesting some mothers of participants felt unable to accurately state their partner's income.[13] The missing income data does not seem to affect the characteristics of our sample. Indeed, the incomes of those whose father's income data is missing are not statistically different, using 95% confidence intervals, from those whose father's income is available. We also lose a small number of cases when female participants (and occasionally participants' parents) reported zero income. Our analysis excludes these cases because the log of zero income is undefined. When female participants declared zero income all but one declared an income for a partner, suggesting that they had zero income because they were homemakers. Our sample size for men is similar to that of samples used in early intergenerational income mobility studies of men in the United States, Britain, Norway and Sweden (Atkinson, 1980, p. 210; Becker and Tomes, 1986, p. S26; Gustafsson, 1994, p. 82; Solon, 1992, p. 401).

The Dunedin Study asked people which category best represented their income, and we used midpoints except at the extremes. This masks some of the variation in income, particularly for those in the top income category. Although the Dunedin Study's income categories were based on the census categories, the second half of the 1980s was a period of high inflation in New Zealand. As a result, 14.1% of parents (27% of fathers and 2.4% of mothers) are in the top income category. We set the top income category for parents at the equivalent of $47,000 in 1987 values, which was just over $80,600 in 2008 values. A much lower proportion of participants reported incomes in the top category at age 32. The incomes of participants who had declared in an overseas currency were converted into New Zealand dollars using purchasing power conversion rates. For participants who were in the top income category we used the $135,000 income Statistics New Zealand allocated to this group after the 2001 and 2006 censuses. Increasing the income imputed for parents and participants in the top income bands had very little effect on the results. However, skews in the data affect our results and reduce their precision in ways that we are unable to quantify (Gujarati, 1995, pp. 325-336, 343; Miles and Shevlin, 2001, pp. 78-80). Overseas studies have encountered similar problems (Atkinson, 1980, pp. 205, 207; Haider and Solon, 2006, p. 1313; Mazumder, 2005, p. 243). Fuller details on the income data are in the Appendix.

If additional years of income data were available this would give us a more accurate picture of people's economic circumstances (Haider and Solon, 2006; Mazumder, 2005, pp. 249, 253). Nevertheless, the Dunedin Study data is very useful because it includes longitudinal information on the actual incomes of both parents and their grownup children, includes New Zealanders who have moved overseas and has a very high participation rate.