6 Comparing our results with those for other countries

Now that we have tentatively estimated rates of income mobility for people from Dunedin and occupational mobility in New Zealand, we can very cautiously compare our results to results from the most similar overseas studies. Considerable caution is necessary when making comparisons because of sampling and methodological differences between studies (Causa and Johansson, 2009, p. 12). Comparisons by other researchers have sometimes been criticised on the basis that differences may reflect methodological differences rather than real differences in intergenerational economic mobility (Gorard, 2008, pp. 320, 322).

6.1  Comparing the Dunedin Study income results with similar overseas studies

Table 7 compares our intergenerational income elasticity results for New Zealand men and women from Dunedin to those of the most similar overseas studies. For all these results the models used included just the incomes or earnings of fathers or parents, the adult earnings or incomes of their children, and a varying range of age controls (Blanden and Machin, 2008, p. 106; Corak and Heisz, 1999, p. 510; Ermisch, et al., 2006, p. 673; Jäntti, et al., 2006, p. 5; Solon, 1992, p. 399).[33] To maximise comparability with the Dunedin data, we tried to find studies that measured children's incomes once in their early thirties, and fathers' incomes twice when their children were in their teens.[34]

We identified reasonably similar studies to the Dunedin Study for men and women in Britain, and for men in Canada and in the United States. However, the studies for most countries measured children's incomes during their late thirties, and have more income measurements, either for fathers or for their children, than the Dunedin Study. This may result in estimates for these countries being higher than if incomes were measured at the same ages and the same number of times as in the Dunedin Study (Jäntti, et al., 2006, p. 20; Solon, 1999, p. 1785, 2002, pp. 61-63). For instance, the high estimates for men in Germany in Table 7 probably partly reflect the much higher number of measures of father's income than for the other countries.

However, our data may include people from a wider range of income groups than overseas studies. Most of the studies in Table 7 exclude people whose father was not working, and this may reduce the magnitude of estimates in these countries (Fortin and Lefebvre, 1998, p. 17; Gorard, 2008, p. 320; Jäntti, et al., 2006, pp. 28-30). When the participants were aged 13, the Dunedin Study asked parents not to report benefit income. But when the participants were aged 15 their parents were asked to report income from all sources, including benefit income. When participants were aged 32 they were prompted about different sources of income and then asked to report the total income they had received (Poulton, [2003], pp. Fin1-2). In addition, some of the studies in Table 7 are just for labour market earnings. Studies of the United States and Canada have found that using total income tends to slightly inflate estimates compared to using just labour market earnings (Corak and Heisz, 1999, p. 512; Mazumder, 2005, p. 250; Peters, 1992, p. 466).

Differences in sample selection methods, definitions of income or earnings, the time-period covered, the number of income measurements and the ages at which incomes were measured all reduce the comparability of the Table 7 estimates and make international comparisons tricky (Jäntti, et al., 2006, p. 5; Solon, 2002, pp. 61-63). Because of the methodological differences between studies, we have not summarised the results in a graph. A more detailed version of Table 7 appears in the Appendix as Table A11.

Our preferred point estimate of the intergenerational income elasticity for New Zealand men from Dunedin (the result in Table 1, model four) is 0.29. Our preferred point estimate for New Zealand women from Dunedin is 0.215 (Table 1, model five). The latter result suggests that, on average, a 1% relative difference in the income of a woman's father is associated with about a 0.22% relative difference in that woman's own adult income. However, the wide confidence intervals indicate that our parameter estimates might change if we had additional cases, or took a different draw from the population of people born in Dunedin. Table 7 shows that the confidence intervals for the New Zealand results for people from Dunedin are much wider than for many countries. This reflects our relatively small sample size. For several of the countries included in Table 7 data is available for the entire birth cohort for one or more years, provided people had positive earnings as an adult and were still living in their home country. For instance, for Denmark the sample contains all people born between 1958 and 1960 and includes over 150,000 people. However, our sample size and confidence intervals are similar in size to Solon's for men in the United States, and those for a study of men from York in England and of men living in Sarpsborg in Norway (Atkinson, 1980; Solon, 1992, p. 401; Soltow, 1965, pp. 107-110).[35] The confidence intervals for people from Dunedin are also large because there is a weak relationship (compared to other variables not controlled for) between parental income and a person's own income.

The results in Table 7 show that the 95% confidence intervals for the preferred intergenerational income mobility estimates using Dunedin Study data overlap with those for people living in most developed countries.[36] At a 5% level, only men in Denmark are more mobile than men from Dunedin. Men from Dunedin are more mobile than United States men at a 5% level using the alternative United States results shown in the last row of Table 7. However, the alternative United States results measure the incomes of men twice and at an older age than the Dunedin Study results.[37] This would increase the size of the elasticity and the level of the lower and upper confidence intervals (Corak, 2006, p. 10). Solon’s results for the United States are a more valid comparison, and his confidence intervals for the United States overlap with those from the Dunedin Study.

All these results were generated using Ordinary Least Squares regression. Studies using two-stage least squares methods (France, Italy, Japan, Spain and Switzerland) were excluded because this method tends to yield different results from only using one or two measurements of actual income. The results for Australia should be treated with caution because incomes for fathers were predicted on the basis of finely grained occupational data.

Comparing the results for different countries using 90% confidence intervals (not shown here) does not result in any additional differences emerging between rates of intergenerational mobility for men from Dunedin and men in other countries. Even using 90% confidence intervals, differences between rates of intergenerational income mobility for New Zealand women from Dunedin and women in other countries were not statistically significant. Our results suggest that rates of intergenerational income mobility for New Zealand men and women are probably within a similar range to rates of intergenerational income mobility in most other developed countries.

Other researchers comparing rates of intergenerational income mobility between countries have often initially reported similarly inconclusive findings (Björklund and Jäntti, 1997, pp. 1016-1017; Solon, 1999, p. 1787). Greater certainty about the relative position of countries has usually resulted from parallel analysis, which involves applying the same methods and methodological assumptions to datasets from different countries, and by increasing the number of cases included in regressions (Grawe, 2004, pp. 65-66, 70; Jäntti, et al., 2006, p. 1).

Future researchers could slightly increase the number of cases by imputing missing income data for parents of Dunedin Study participants from information on parents' occupation, education, age and employment status. This would reduce comparability with the results shown in Table 7, although some comparisons with results for other countries would be possible. Deriving the income of each parent in the top income group from other data, such as their occupation and education, could potentially produce a richer picture of the economic circumstances of some families. Imputing income from benefits when the participants were 13 could also improve the dataset. It would also be desirable to test the relationship between the income data and other measures of wellbeing, such as SES and self-assessed standard of living. The comprehensiveness of the Dunedin dataset would also make it possible to test how variables such as physical and mental health and childhood intelligence influence adult income.

The results from the Dunedin Study data could potentially be cross-validated using income data from the Christchurch Study of 1,265 children born in mid-1977. This cohort was last assessed at age 30. Although the Christchurch data would provide results for people who had grown up in a different geographic region, the results would be from a similar point in time and for a slightly younger age group. In the future, it might be possible to develop large national datasets containing the incomes of New Zealanders from government statistical records. This might make it possible to calculate intergenerational income mobility estimates with smaller standard errors, and to calculate estimates for people born in different time-periods. Despite potential privacy and data protection concerns (Lane and Maloney, 2002; Sinnott, 2000; Wilson, 2002), longitudinal analysis of detailed individual-level New Zealand benefit and employment data collected by the government has occurred (Dixon and Crichton, 2007; Wilson and Soughtton, 2009). However, researchers using administrative data to study intergenerational mobility would need to match individual-level historical data on parents with subsequent data on their grown-up children. This could be difficult (Corak and Heisz, 1999, p. 509). A new longitudinal study was launched in New Zealand in 2008-09, and if participants are tracked into their thirties and forties this study could also eventually be used to study intergenerational income mobility (Growing up in New Zealand, 2010).