5.2 Intergenerational mobility with variables for being Māori, for ethnicity and for region

We can tentatively measure intergenerational occupational mobility for Māori using 1996 Election Study data because the Election Study had a large sample size and collected data on a similar proportion of Māori to the proportion of Māori in New Zealand's population. Nevertheless, there are still only 371 cases where people identified as Māori and for whom we have data on their age, their occupation and their father's occupation. This makes accurately calculating intergenerational mobility for Māori difficult.

To measure intergenerational occupational mobility for Māori we reran the regressions with a binary variable for Māori ethnicity and an interactive term for Māori ethnicity by father's SES. The binary variable measures the difference in SES between all people and Māori. The interactive term measures whether father's SES has a statistically significant additional effect on the SES of Māori. We also included a binary variable for those who had not identified as New Zealand European, Pākehā or Māori, and an interactive variable for this group by father's SES. To maximise the sample size and lower the sampling error, we included all people aged over 18 in our regressions, although including only those aged 25 or over produced similar results. Because of the small number surveyed, we were unable to calculate intergenerational mobility for ethnic groups such as Pacific peoples.

Our results (Table 6, model one) indicated that Māori, on average, had lower SES than New Zealand's population as a whole, and that this effect was statistically significant at a 5% level. The model's estimate suggests that Māori tended to have SES scores that were 6.86 points lower on the 10 to 90 scale than for New Zealand's population as a whole (95% confidence interval: 1.62 to 12.10). However, the interactive term for Māori ethnicity by father's SES was not statistically significant, even at a 10% level. This suggests that there is insufficient evidence that father's SES had a different effect on Māori intergenerational mobility than for New Zealand's entire population.[31] The binary and interactive variables for having an ethnic identity that was not Māori or Pākehā/New Zealand European were not significant in any of the models.

In model one, the variables for Māori include those who identified just as Māori and those who identified themselves as being Māori and as belonging to one other ethnic group as well. The results were very similar when these variables included only those who identified just as Māori (results not shown).

Language is a key component of Māori and of ethnic identity. We therefore tried dropping the Māori ethnicity and other ethnicity variables and replacing them with variables for speaking Māori or another language at home (model two). However, neither the binary variable for Māori language skills nor the interactive variable for speaking Māori at home by father's SES was significant. The binary variable for speaking a language other than English or Māori at home was positive, but was also not statistically significant. In addition, the interactive variable for speaking a language other than Māori or English by father's SES was not significant. Within our sample, speaking a language other than English at home does not seem to have had a statistically significant effect on people's SES or their intergenerational occupational mobility. However, the 1996 NZES questionnaire was only available in English. This may have discouraged responses by some Māori and by other potential respondents.

Our third model returned to using ethnicity controls and added controls for people's geographic location. Adding geographic location only slightly diminished the effects of Māori ethnicity on a person's SES. However, the results showed that people living in provincial cities, provincial towns and rural areas on average had lower SES than those living in New Zealand's three main urban centres.

We also followed an overseas study by experimenting with other ways of quantifying intergenerational mobility for different groups (Hertz, 2005, pp. 167-168, 175-178). Running separate regressions for the Māori and non-Māori population or for Māori and for New Zealand European/Pākehā (results not shown) produced a similar pattern of results.

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.

The lower SES for Māori than for New Zealand European/Pākehā is likely to reflect historical factors. Until the 1940s New Zealand Māori largely lived in rural areas, with the largest numbers in the north and north-east of the North Island. Between the early 1940s and late 1960s Māori rapidly become urbanised (Pool, 1991, p. 105). Since the 1940s, median outcomes for Māori in areas such as educational achievement, health status, income levels and family size have become more similar to median outcomes for non-Māori New Zealanders. In the 1990s, there was “considerable overlap” in outcomes for Māori and non-Māori (Gould, 2008, p. 260; Treasury, 2001, pp. 6-8). However, the median position of Māori often continued to differ from the median for non-Māori in areas such as occupation, educational qualifications, geographic location, age structure, family size, the age at which women had children, the language they spoke at home and health status (Pool, 1991, pp. 136, 167, 181, 183, 201). These differences help explain why the data suggests that in 1996 Māori continued to have a lower average SES than New Zealand European/Pākehā.

The data precedes the massive expansion of the non-degree part of the tertiary sector from the late 1990s, and the associated development of tertiary education providers that have concentrated on the needs of Māori (Ministry of Education, 2007, section 12). For instance, between 1996 and 2004 the number of effective full-time Māori tertiary students more than doubled, with Māori participation rates becoming higher than for New Zealand’s total population (Ministry of Education, 2005). This may have changed the position of Māori and the rate of intergenerational mobility by Māori. However, increases in higher education expenditure in other countries have not always increased intergenerational mobility (Blanden, et al., 2005, p. 14; Blanden and Machin, 2004, p. 230). Generational replacement is also continually changing the characteristics and experiences of the Māori population. More recent data might therefore produce different results.

Important limitations to our research include that we are dependent on a single measure of people's SES, when many people change jobs over time, and that we are also reliant on respondents' recall of their father's occupation (Björklund and Jäntti, 2000, p. 23; Ermisch, et al., 2006, p. 665).[32] In addition, the SES of occupations can change over time, while some SES categories, such as farming, contain people with a wide variety of economic circumstances (Davis, et al., 2003, p. 86; Galbraith, et al., 2003, p. 23). As noted in Section 3.2, our sample also imperfectly mirrors some characteristics of New Zealand’s population. Furthermore, the data we are using is now over 14 years old and we might not necessarily get the same results using more up-to-date data.