5 New Zealand Election Study results

Although the Dunedin Study dataset is very comprehensive, includes income data for both participants and for their parents, and includes people now living outside New Zealand, the study is restricted to people born within a 12-month period in a single centre. Testing intergenerational occupational mobility using a national dataset that includes immigrants and people born in all regions of New Zealand provides another source from which to estimate intergenerational economic mobility. As discussed in Section 3.2, Election Study data on the SES of respondents and of their fathers was therefore used to measure intergenerational occupational mobility. The average income of people in different occupations in the 1996 census, together with data on their educational qualifications and the value of goods they consumed, determined the SES of occupations (Davis, et al., 2003, pp. 12-16).

Because the distribution of the SES data did not appear overly skewed, we were able to use it unlogged in our regression equations.[26] The results should therefore be interpreted differently than for the Dunedin Study. In the models using Election Study data the effect of father's SES is linear, and a person's SES reflects the coefficient for father's SES times the full value of their father's SES.[27] Because of the different model specifications and different units of measurement, readers should only cautiously compare the Election Study and Dunedin Study results. Our data suggests only a weak relationship between logged income and SES.

Table 3 shows that, in 1996, the estimated effect of the SES of fathers on the SES of their children was 0.18 (model one). This implies, on average, that growing up with a father who had an SES 10 units higher than another man's father, on the 10 to 90 SES scale, is associated with having an adult SES that is 1.8 units higher than the other man. For men the coefficient for the effect of father's SES was 0.20 (model two) and for women was very similar at 0.17 (model three). Because of the large size of the dataset, the confidence intervals are smaller than for the Dunedin data.

Although these regressions use our full sample, many people experiment with different jobs when entering the workforce (Atkinson, 1980, p. 203), while students usually do not have a permanent job until after they graduate. Many young New Zealanders also travel after they finish their education, and this can further delay both entry into the workforce and seeking a permanent job (Conradson and Latham, 2005, pp. 166-167). We therefore followed an overseas study by also running separate regressions for all men and women who were 25 years or older (Ermisch, et al., 2006).[28]

The coefficient for everyone aged 25 years or older increased only modestly to 0.20 (model four). This implies that having a father who is a lawyer (SES of 83) rather than a labourer (SES of 20) is, on average, associated with a 12.6 unit difference in a person's adult SES. This is approximately the difference between being an insurance underwriter (SES of 48), and being a builder (SES of 36) or of being a nursing or midwifery professional (SES of 45) and being a secretary or keyboard operator (SES of 33) (Galbraith, Jenkin, Davis and Coope, 2003, pp. 26-28). However, model four explains only 5% of the variance in people’s SES. This indicates that other variables, which have not been included in the model, had a larger effect than father’s SES on a person’s own SES. As Table 5 indicates, many people from low SES backgrounds also later become adults with a high SES, and vice versa.

For men aged 25 years or older the estimated effect of father's SES was 0.23 (model five), and for women was 0.18 (model six). The confidence intervals for men and women still overlapped, indicating that the relatively small differences between the intergenerational occupational mobility estimates for men and women were not statistically significant. Restricting the analysis to those aged over 30 left the point estimates unchanged, while further restricting the analysis to those aged over 35 slightly diminished the point estimates (results not shown).

Although the average incomes of people in different occupations at the 2006 census largely determined the SES scores, the average educational qualifications of people in each occupation were also used in the calculation of the SES scores. As a result, we have not used people's years of education to explain their SES.

Using the 1993 New Zealand Election Study dataset generated almost exactly the same intergenerational mobility point estimates, despite differences in the occupational coding schemes used. These results are also similar to a recent unpublished estimate of occupational intergenerational mobility for New Zealand men (using 1995 data and a small sample) by Ganzeboom and Treiman (Blanden, 2008, p. 32; Ganzeboom and Treiman, 2007, p. 45).

The intergenerational occupational mobility point estimates for men and women (25 years or older) using Election Study data are about 80% of the size of the intergenerational income mobility point estimates for men and women using Dunedin Study data. A study of intergenerational mobility in Britain has also found that intergenerational occupational mobility seems to be higher than intergenerational income mobility (Ermisch and Francesconi, 2004, p. 182).[29]

Column entries are unstandardised linear regression coefficients. We have not used the log of SES in the regressions.

Standard errors are in brackets. *=p<.10, **=p<.05, ***=p<.01