Understanding New Zealand: Demographics of the Non-Christian Religious

Although the majority of religious people in New Zealand follow some kind of Christian denomination, there are enough non-Christian religious for it to be worth looking at them as a discrete category.

The Spiritualism and New Age movement is perhaps the most interesting group of non-Christians because they are the hardest to categorise. They are like the others in many ways and unlike them in many ways.

Perhaps the most striking set of correlations relating to the non-Christian religious are those with being foreign born. The correlation between being Buddhist and being foreign born was an extremely strong 0.90, and speaks to how little immigration to New Zealand there has been from Buddhist countries until recently.

There was also a significant positive correlation between being foreign born and belonging to any of Islam (0.75), Hinduism (0.74), Judaism (0.41) or other religions (0.34).

Interestingly, though, there was a moderately strong negative correlation between being foreign born and following Spiritualism or New Age traditions – this was -0.45.

Given that it is very likely any given non-Christian religious person is an immigrant, we can also see trends that are true of immigrants replicated with the non-Christian religious. For instance, the non-Christian religious are significantly better educated, especially in the case of Buddhists and Jews.

The correlation between having a Master’s degree and being a Jew was 0.78; with being a Buddhist it was 0.68; with being a Muslim it was 0.37 and with being a Hindu it was 0.34.

However, the correlation between having a Master’s degree and following a Spiritualist or New Age tradition was negative, at -0.07. This is probably because this particular tradition appears to have its own, New Zealand-specific focus and so they are less likely to be from highly educated immigrant groups.

Again replicating the patterns, all of the foreign non-Christian traditions had significant negative correlations with being on the invalid’s benefit, in contrast to Spiritualism or New Age, which had a significant positive one.

Likewise, all of the foreign non-Christian traditions had correlations of at least 0.50 with never having smoked cigarettes, but the correlation between being a Spiritualist or New Ager and never having smoked was -0.41.

All of these five non-Christian traditions had positive correlations with being on the student allowance, which may suggest a generally higher intelligence among this group. The correlation between being on the student allowance and being Buddhist was 0.30; with being Muslim it was 0.29; with being Jewish it was 0.22; with being Hindu it was 0.19 and with being a Spiritualist or New Ager it was 0.18.

Some might be able to predict the very strong correlations being being Buddhist or Jewish and working in one of information media and telecommunications, financial and insurance services or professional, scientific or technical services. Being Buddhist had a correlation of at least 0.55 with all three of these industries and being Jewish had one of at least 0.60 with all three.

One curiosity is when it comes to how people get to work. Hindus and Muslims are significantly more likely to take a private vehicle to work; Hindus, Muslims and Jews are significantly more likely to take a bus to work; Jews, Spiritualists and New Agers are significantly more likely to walk to work and Spiritualists and New Agers are significantly more likely to bike to work.

The fact that Spiritualists and New Agers have a high incidence of being on the invalid’s benefit but are among the most likely to exercise on the way to work speaks of the large proportion of psychiatric casualties among this group.

Here’s one for the conspiracy theorists: the correlation between being a Jew and having a personal income of $150K was a very strong 0.83. The only other non-Christian tradition to have a significant positive correlation with being in this income band was Buddhism, at 0.40.

For Hinduism, Islam, and Spiritualism and New Age the correlations ranged from 0.00 to -0.12.

The main reason for this can be seen if one looks at the correlations between following a particular non-Christian religious tradition and working as a professional. This had a correlation of 0.70 with being Jewish, 0.48 with being Buddhist, 0.13 with being Muslim, 0.12 with being Hindu and 0.11 with being a Spiritualist or a New Ager.

As a general rule, people following a non-Christian religious tradition were marginally more likely to become sales workers or clerical and administrative workers.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Voting Patterns of Age

The electoral divide between Labour and National is usually characterised as one of wealth, and to a major extent it is. But it is also about age to a major extent, and some of the correlations between age and party allegiance are surprisingly strong.

The correlation between being in the 50-64 age group and voting for National in 2014 was a very strong 0.74. The correlation between being in this age group and voting Labour in 2014, by contrast, was also very strong but negative, at -0.68.

These correlations are especially strong if they are compared with the respective ones for the 30-49 age group. This age group is almost entirely indifferent to the mainstream parties. The correlation between being aged 30-49 and voting National in 2014 was 0.19, and for voting Labour in 2014 it was -0.04.

Really old people like to vote Conservative more than anything else. The correlation between being aged 65+ and voting Conservative in 2014 was 0.71. Even the correlation between being aged 65+ and voting National was weaker, at 0.65.

Some might be surprised to see that the correlation between being aged 65+ and voting New Zealand First was not near as strong – only 0.10. However, as mentioned in the section about the party, the association between crotchety old pensioners and New Zealand First support is mostly a fabrication.

Indeed, at the other end of the age range, support for New Zealand First was about the same level – the correlation between being aged 15-19 and voting New Zealand First in 2014 was 0.05. This suggests that the early signs of Generation Z being a conservative throwback to a previous mentality may well be replicated in New Zealand.

Young people, for their part, prefer to vote Green more than anything else. The correlation between being aged 15-19 and voting Green in 2014 was 0.22, and between being aged 20-29 and voting Green in 2014 it was 0.56.

The big two parties appear to have very little support among young people in general. The correlation between being aged 20-29 and voting National in 2014 was -0.34, and with voting Labour it was only 0.32. Worryingly for them, the correlation between being aged 20-29 and voting for a party as unlike them as ACT was 0.25.

Taking this into account alongside the strong correlation between being young and voting Green, it appears that the big two parties are fated to fall into ever weaker positions as the Greens absorb the discontents from Labour, ACT absorbs the discontents from National and New Zealand First absorbs the discontents from the entire system.

The very youngest two age brackets obviously does not tell us about the voting preferences of those aged under 15, but they do tell us about the voting preferences of their parents and therefore gives us a clue as to what influences will be at work on the next generation.

In particular, we can see the influence that the higher birth rate of Maoris has. All of the parties generally associated with a high degree of Maori support (Maori Party, Internet MANA, New Zealand First, Aotearoa Legalise Cannabis Party and Labour) had correlations of at least 0.45 with both of the age groups of 0-4 and 5-14 years of age.

The Maori Party and the ALCP were the strongest of these, New Zealand First and Labour were the weakest, and Internet MANA was in between.

The degree of disenfranchisement that the young suffer can be seen from the fact that there is a very strong correlation of 0.77 between median age and turnout rate in the 2014 General Election. This correlation is so strong that it speaks of a widespread perception among the young that there really is no point in voting on account of that the entire system is set up specifically to serve people other than them.

The strongest negative correlation between median age and voting for any party in 2014 was with the Labour Party, which was -0.70. The reflection of this was that the strongest positive correlation was with the National Party, which was a whopping 0.81.

The only other party that generally appealed to old people was the Conservatives. The correlation between voting for them in 2014 and median age was 0.75.

Definitively underlining the fact that the stereotype of creeping swarms of pensioners voting New Zealand First every three years is totally false, the correlation between voting New Zealand First in 2014 and median age was actually negative (although not significant) at -0.08.

The Greens, despite that they are the mutual nemesis of the New Zealand First Party, appeal to a similar average age of voter. The correlation between voting Green in 2014 and median age was -0.17.

Predictably, there were significant negative correlations between median age and voting for any of the minor Maori-heavy parties. These were Maori Party (-0.66), Internet MANA (-0.65) and ALCP (-0.55).

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Demographics of Men and Women

There has been plenty of talk about the “gender gap”, which is the fact that the average Kiwi woman earns less per hour of labour than the average Kiwi man. This article looks into why this might have come about.

The correlation between being male and median personal income was on the border of statistical significance, at 0.23. That tells us that the average Kiwi male controls an income that is a fair bit larger than what the average Kiwi female controls. Looking at this on a more granular level, we can understand why.

There is very little difference between men and women when it comes to the plum jobs. The correlation between being male and having a personal income between $100-150K was 0.01 and with having a personal income of $150K+ it was 0.03.

So being a male and working in a plum job is essentially uncorrelated. However, as one goes down the income bands, it is possible to see that there are more men in middle income jobs than women, and more women in lower income jobs than men.

The strength of the correlation with being male peaks at $50-60K, where it is 0.22. A person in this income band is likely earning between $25 and $30 per hour, or at least 50 hours a week, so this is where a solid part of the full-time work force is cranking away.

As one goes even further down the income bands, however, we can see that an ever higher proportion of the workers are women. In the $30-35K income band there is a perfect absence of correlation with regard to male or female, but every income band lower than this has a positive correlation with being female.

The most significant is having a loss or no income, which has a correlation of 0.27 with being female.

By far the heaviest contributor to the fact that men occupy disproportionately more middle income bands than women is the moderately significant correlation between being male and working full-time (0.48), and the moderately significant negative correlation between being male and being unemployed (-0.48).

After all, it’s hardly suprising that a man’s paycheck is 20% bigger if he also works 20% more hours. In fact, the gap perhaps ought to be even larger than this because men work the vast majority of overtime hours.

There is no significant correlation between being male and working for a wage or salary – this was 0.11. There were, however, significant correlations between being self-employed and male (0.40) and being self-employed with employees and male (0.50).

This tells us that a disproportionate amount of the risk in the area of employment is borne by men. Women are more likely to take a safe job that had slim prospects of both advancing and of being fired or made redundant, whereas men were more likely to take entrepreneurial risks or to take on jobs in highly competitive (and highly rewarding) environment.

For example, there were significant correlations between being female and working in the healthcare and social assistance industry (0.43) and the education and training industry (0.32), and a near significant one between being female and working in administrative or support services (0.17).

In all three of these industries it is common to have a regular, secure 9 to 5 job.

On the other side of the coin, there were significant correlations between being male and working in the agriculture, forestry and fishing industry (0.45), the hospitality industry (0.28), the construction industry (0.25) and the rental, hiring and real estate services industry (0.24).

All of those industries are characterised by it being common for either workers to have the option of working longer hours or being more or less forced into it. The hospitality and rental, hiring and real estate industries in particular make it easy for anyone wanting to work 60+ hours a week to do so.

So talk of a “gender gap” that evinces an instituional and endemic underpayment of women across the nation is hyperbole. The best jobs are split evenly between men and women and, below that, men earn more because they choose to work themselves to death at a much higher rate.

Somewhat surprisingly, there is a correlation of 0.42 with being male and living on the South Island. That might seem very strange until one takes into account the vastly accelerated death rate of Maori and Pacific Islander males, especially past age 50 or so. Because most of these men live on the North Island, their early deaths leave a significant imbalance of women among the remaining communities.

Other facets of this same phenomenon can be observed in the significant correlation between being female and being Maori (0.32). Obviously, as males and females are born at roughly the same rate, much of this correlation has to be explained by a greater death rate among Maori men.

Some may be interested to observe that there were significant correlations between being female and belonging to a number of religious traditions generally associated with disadvantaged people. In particular, these were significant correlations between being female and following any of Mormonism, Ratana, Jehovah’s Witnesses, Maori Christian, Pentecostalism or Christian not further defined.

The main reason for this is the tendency for women to turn to religion or spirituality after a significant male other has left their lives, particularly in the case of Maori women.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Internet MANA voters

As the Maori Party split away from Labour, so did the MANA Party split away from the Maori Party, and then it joined up with Kim Dotcom’s Internet Party to become the Internet MANA chimera. But who did Hone Harawira’s machine end up appealing to?

Like the Maori Party, Internet MANA appealed to Maoris. The correlations between voting Internet MANA in 2014 and with both voting Maori Party in 2014 and being Maori were 0.84.

Correspondingly, there are strong correlations between voting Internet MANA in 2014 and voting for all of the Maori-heavy parties in 2014. Between voting Internet MANA in 2014 and voting Aotearoa Legalise Cannabis Party in 2014 the correlation was 0.76; with voting New Zealand First in 2014 it was 0.44; and with voting Labour in 2014 it was 0.41.

Curiously, Internet MANA voters were exactly as unlikely to have sympathies for National or Conservative as Maori Party voters. As with the Maori Party, the correlation between voting Internet MANA in 2014 and voting National in 2014 was -0.75, and the correlation with voting Conservative in 2014 was -0.64.

Perhaps the major demographic difference between Maori Party voters and Internet MANA ones is that the latter were slightly less Maori and slightly more Pacific Islander and Asian. The correlation between voting Internet MANA in 2014 and being a Pacific Islander was 0.07, and with being Asian it was -0.23 (compared to 0.01 and -0.30 for the correlations between these two groups and voting Maori Party).

In fact, the general demographic trend is that Internet MANA voters, despite being generally disenfranchised, are doing slightly better than Maori Party voters. Correspondingly, the correlation between voting Internet MANA in 2014 and turnout rate in 2014 was, at -0.69, slightly weaker than for the Maori Party (-0.74).

Although most of the demographic distinctions are subtle, one of the clearest is when it comes to education. The correlation between voting Internet MANA in 2014 and having no qualifications was 0.42, which was weaker than the equivalent for the Maori Party. Also, unlike with voting for the Maori Party in 2014, voting for Internet MANA in 2014 had no significant negative correlation with holding either of the two highest academic qualifications.

Further underlining the minor class differences, Internet MANA voters were marginally less likely to be on the unemployment or invalid’s benefits, and marginally more likely to be on the student allowance. Also, they were much less likely to work in manufacturing and slightly less likely to be regular tobacco smokers than Maori Party voters.

They were, however, essentially the same age. The correlation between voting Internet MANA in 2014 and median age was -0.65, making them the smallest smidgen older than Maori Party voters. This underlines the degree to which Internet MANA differentiates itself from the Maori Party primarily through subtle class differences and not age.

Curiously, Internet MANA voters were more likely to be self-employed than Maori Party voters, but were less likely to be self-employed with employees. This might reflect the degree to which Internet MANA voters, or at least a significant cadre of them, are more likely to be immigrants and therefore less likely to be established than Maoris.

It may be that, in so far as Internet MANA appeals to a newer sort of New Zealander, it also appeals to a sort of person who does not have the intergenerational poverty and trauma that many Maoris suffer from. This may explain the small differences in wealth, health and educational outcomes.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Demographics of Employment Status

Knowing about the category of person who is self-employed with employees tells us a lot about the sort of person who has most of the power in New Zealand at the moment.

This sort of person has more power than anyone because they can legally cause more disruption than anyone. No politician cares too much if a single individual threatens to leave the electorate, but if an employer threatens to relocate their company with its 200 jobs then a politician will suddenly care very intently.

Surprisingly, there is no particularly strong difference between those who work for a wage or salary, those who are self-employed, and those who are self-employed with employees when it comes to median personal income.

These three groups have correlations of between 0.54 and 0.41 with median personal income, with the self-employed the strongest and the self-employed with employees the weakest.

However – as this section seeks to illuminate – holding political power is not merely a function of wealth, although wealth is a contributing factor.

There were very strong correlations between being of European descent and both being self-employed (0.58) and being self-employed with employees (0.70). This relates to the point made above about the power in an economy being held by a sort of person who was not necessarily the same as those who made the money.

Pacific Islanders were the least likely to be in either of those two categories. The correlation between being a Pacific Islander and being self-employed was -0.50, and with being self-employed with employees it was -0.61.

Being Maori was also negatively correlated with being in these categories of employment status: -0.44 with being self-employed and -0.36 with being self-employed with employees.

This reflects the fact that Islanders generally have less social capital than Maoris, despite often being better educated, and that Islanders generally have less financial capital than Asians, despite often having moved to New Zealand earlier and being more culturally established.

Anglicans comprise a large proportion of the power elite, as can be seen by the correlations between being Anglican and being self-employed (0.40) and being Anglican and being self-employed with employees (0.58).

This latter correlation is strong enough to tell us that Anglicans have a lot of political power in New Zealand through occupying essential positions in industry.

Other religious orientations with the strongest correlations with being self-employed with employees were Presbytarianism (0.45), having no religion (0.37) and Brethren (0.22).

These four groups: Anglicans, Presbytarians, those from no religious tradition and the Brethren, comprise the true power elite of New Zealand. The reason for this is because it is these people who own everything: generally they are directly descended from early settlers and owners of large farms.

Here it is possible to further illuminate the distinction within the highly-skilled occupations between the managers who run everything and the professionals they depend on to get things done.

Certain religious traditions had positive correlations with working for a wage or salary but negative correlations with being self-employed with employees.

Catholicism was the most notable of these. The correlation between being Catholic and working for a wage or salary was 0.30, with being self-employed it was -0.23 and with being self-employed with employees it was -0.31.

Other religious traditions which had positive or near neutral correlations with working for a wage or salary but negative correlations with being self-employed with employees were Buddhism (0.11 versus -0.24, respectively), Hinduism (-0.03 versus -0.44) and Islam (-0.03 versus -0.49).

Ultimately these statistics reflect how these latter traditions have higher proportions of recent immigrants who, despite often being highly educated and earning good money, have not had the time to establish themselves as part of the power elite. These immigrants often moved to New Zealand because their high skills were needed by the landowners and managers who were more established.

It’s also possible to observe the fault lines of a generational conflict between the Baby Boomers, whose education is patchy, and Generation X and the Millennials, who generally have modern educations but who are yet to dislodge the deeply entrenched Boomers.

The correlation between having a Master’s degree and working for a wage or salary was 0.33, and with being self-employed with employees it was actually negative, at -0.02. This latter correlation is incredible if one also considers that the correlation between having NZQA Level 1 (School Certificate) as one’s highest qualification and being self-employed with employees was 0.22.

Explaining much of this comes down to the fact that establishing oneself as a member of the power elite is more a function of age than of education.

The correlation between median age and being self-employed with employees was a strong 0.71, whereas with working for a wage or salary it was -0.37. This tells us that, over and above just about anything else, the power elite is old, and the people they hire to do their bidding are young.

To take a more granular perspective, the correlation between being aged 65+ and being self-employed with employees was 0.56, which is interesting if one considers that any person in this age bracket can also claim a pension of $350+ per week which is not means tested.

This is not just a function of greed, of course: realistically, many of the people running a company, especially if it’s one they own, cannot simply give up all of their responsibilities at one moment.

Generally they employ the under-50s. The correlation between being in the 20-29 age bracket and working for a wage or salary was 0.37, and between being in the 30-49 age bracket and working for a wage or salary was 0.52.

The power elite is also much more likely to be male than female. The correlation between being male and working for a wage or salary was 0.11, but the correlation between being male and being self-employed with employees was 0.50.

This isn’t simply a matter of male nepotism: the correlation between being male and doing unpaid work in the family business was 0.48. The truth is that it is in the nature of Kiwi men to work, and the vast majority of us would rather work than just sit around or have nothing to do.

The last point about the power elite that might not be well understood is the degree to which it is intergenerational, especially in the case of farming interests.

Some light can be shed on how strong this degree is by consideration of the correlation between working in agriculture, forestry and fishing and doing unpaid work in the family business, which was an extremely strong 0.90.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Demographics of Education

Most people have a vague idea that education is for intelligent people who want to increase their human capital and how to leverage it more effectively, and that educated people more or less run everything. For these reasons, education correlates fairly closely with being part of the Establishment.

Many will be surprised to read that there are no significant positive correlations with being of European descent and having any of the university degrees. Two of them are even negative: the correlation between being of European descent and having a Bachelor’s degree is -0.03, and with having a Master’s degree it is -0.02.

The correlations between being of European descent and having an Honours degree or a doctorate were 0.16 and 0.22, respectively.

This is explainable by the fact that surprisingly few graduates in New Zealand were born here.

The correlation between being born in New Zealand and having a Bachelor’s degree was -0.61; with having an Honours degree it was -0.45; with having a Master’s degree it was -0.59 and with having a doctorate it was -0.32.

One can predict from this that the correlations between being Maori and having a university degree are significantly negative, and indeed they all are stronger than -0.40.

Because our immigration system makes it easier for people who have university degrees to come to New Zealand, we can see that the Pacific Islander and Asian populations – a large proportion of which were born overseas – are much better educated than most people might realise.

Pacific Islanders in New Zealand are much less likely than Kiwis of European descent to have an Honours or a doctorate degree, but the correlation between being a Pacific Islander and having a Bachelor’s degree is only -0.10, and with having a Master’s degree it is only -0.08.

Asians, for their part, are much, much more likely than the average Kiwi to have a university degree. The correlation between being Asian and having a university degree was 0.28 for a doctorate, 0.60 for a Master’s degree, 0.41 for an Honours degree and 0.64 for a Bachelor’s degree. All of these are significant.

The correlaton between being born in North East Asia and having a Bachelor’s degree was a very strong 0.72.

Looking at the correlations between belonging to certain income bands and having a certain educational level underlines the degree to which an education is the ticket to social advancement in New Zealand.

The correlations between having no academic qualifications and being in any of the income bands between $10-40K were all over 0.70. Having no academic qualifications also had correlations of 0.84 with being a regular tobacco smoker, 0.76 with being on the invalid’s benefit, 0.57 with being a single parent, 0.57 with being on the unemployment benefit and -0.68 with net median income.

So by a variety of measures, it’s clear that a person’s level of academic qualifications are generally a pretty good indicator of where they stand in socioeconomic terms.

There were already significant improvements in socioeconomic standing for Kiwis who only went as far as NZQA Level 3 or 4.

Having NZQA Level 3 or 4 as one’s highest academic qualification had correlations of -0.26 with being a regular tobacco smoker, -0.21 with being on the invalid’s benefit, -0.07 with being a single parent, 0.05 with being on the unemployment benefit and 0.12 with net personal income.

These are already vastly better statistics, and the step up from finishing high school to having a university degree is just as great as the step from having no academic qualifications to finishing high school.

Having an Honours degree as one’s highest academic qualification had correlations of -0.64 with being a regular tobacco smoker, -0.55 with being on the invalid’s benefit, -0.49 with being a single parent, -0.39 with being on the unemployment benefit and 0.72 with net personal income.

It’s evident, therefore, that a higher education is extremely strongly correlated with general well-being. The ultimate cause of this might well be natural intelligence, which is of course out of the scope of this study. However, in so far as education correlates with intelligence, we can make an educated guess at the habits of educated New Zealanders by looking at education.

Interestingly, the correlations between education levels and religion spanned the whole spectrum. Some religious traditions in New Zealand are exceptionally well eduated on average; others exceptionally poorly.

The best educated are the Buddhists and the Jews. The correlation between being Buddhist and having no qualifications was -0.72, with having NZQA Level 3 or 4 it was 0.43 and with having an Honours degree it was 0.52. The correlation between being Jewish and having no qualifications was -0.70, with having NZQA Level 3 or 4 it was 0.42 and with having an Honours degree it was 0.76.

Catholics are the next best educated religious demographic, which is a reflection of the large proportion of Catholics that were born overseas and had to get through the immigration system. The correlation between being Catholic and having no qualifications was -0.32, with having NZQA Level 3 and 4 it was 0.19 and with having an Honours degree it was 0.31.

Curiously, the next best educated demographic were of those who had no religious affiliation, and the bulk of these people were born in New Zealand. This might not surprise any readers who are materialist atheists, because this sort of person dominates the universities of this nation.

The correlation between having no religion and having no qualifications was -0.08, with having NZQA Level 3 and 4 it was 0.15 and with having an Honours degree it was 0.27. It may be that a fair proportion of these people were born into a religious family but then came to reject their faith after exposure to university culture.

The average New Zealander who identifies as a Christian has a significantly poorer education than the average New Zealander. The correlation between being a Christian and having no qualifications is 0.15, with having NZQA Level 3 and 4 it was -0.34 and with having an Honours degree it was -0.30. Probably this is a reflection of the fact that there are a fixed number of hours in the day to read books and so reading the Bible must necessarily come at the opportunity cost of reading non-fiction.

The most poorly educated, however, are Mormons and Jehovah’s Witnesses – probably a reflection of the predatory and aggressive proselytising culture of these movements.

The correlation between being a Mormon and having no qualification was 0.40, with having NZQA Level 3 or 4 it was -0.04 and with having an Honours degree it was -0.40. The correlation between being a Jehovah’s Witness and having no qualification was 0.74, with having NZQA Level 3 or 4 it was -0.41 and with having an Honours degree it was -0.71.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Conservative Party Voters

The Conservatives are a strange sort of movement. In many ways they appear to be some kind of rump movement of people who didn’t like it when National decided to move into the 21st century.

The strongest correlation between voting Conservative in 2014 and voting for another party in 2014 was with National – this was 0.77. This is strong enough to suggest that many Conservative voters would have been former National voters, or would have been severely tempted to vote National in 2014.

National was the only party to have a significant positive correlation with voting Conservative in 2014.

There were two parties that were close to uncorrelated. The correlation between voting Conservative in 2014 and voting New Zealand First in 2014 was 0.01, and with voting ACT it was 0.13.

The former of these is probably because both movements compete for the angry, scared old person vote, and the latter is probably because both movements share an indifference towards the poor.

Voting for any of the left-wing parties had significant negative correlations with voting for the Conservative Party in 2014, further emphasising the degree to which the Conservative movement appeals (and is intended to appeal) to disaffected National voters.

The correlation between voting Conservative in 2014 and voting Greens in 2014 was -0.42, and with voting Aotearoa Legalise Cannabis Party it was -0.54. This pair involved slightly weaker correlations than for the other three parties, primarily because Green and ALCP voters are closer to middle aged.

The correlation between voting Conservative in 2014 and voting for the Labour, Maori or Internet MANA parties were -0.63, -0.64 and -0.64 respectively.

Age is the main reason for the strong negative correlations between voting Conservative and any of these parties. The correlation between voting Conservative in 2014 and median age was 0.75, which means Conservative voters are almost as old as National voters.

Conservative voters are even more likely to be on the pension though. The correlation between voting Conservative in 2014 and being on the pension was 0.64, compared to a correlation of 0.50 between voting National in 2014 and being on the pension.

Conservatives are also less educated than average. Whereas the correlations for voting National in 2014 and having any of the university degrees were all positive and either significant or bordering on it, the correlations for voting Conservative in 2014 and having any of the university degrees were all negative and bordering on significant.

Females are less unlikely to vote Conservative than they are to vote National. The correlation between being female and voting Conservative in 2014 was -0.19, compared to a correlation of -0.35 between being female and voting National in 2014.

One major way the two differ is with respect to wealth. The average National voter is much wealthier than the average Conservative one. The correlation between net median income and voting Conservative in 2014 was only 0.06, compared to National’s 0.53.

In fact, looking at the correlations with income bands tells us that wealth is the major differentiator between Conservative and National voters.

The income band that had the strongest positive correlation with voting Conservative in 2014 was the $20-25K band, which was 0.17. All of the correlations between voting Conservative in 2014 and any income band above $25K were negative (although they were all very weakly correlated; not close to significant).

By contrast, all of the correlations between voting National in 2014 and any income band above $60K were positive and significant.

One of the largest differences was that with median family income. The correlation between median family income and voting National in 2014 was 0.42; for voting Conservative it was -0.08.

Oddly, although the average Conservative was more likely than the average National voter to be a Christian, these tended to belong to denominations that were less part of the establishment than the National voters.

The correlation between being a Christian and voting Conservative in 2014 was 0.37, compared to 0.29 for voting National in 2014.

Conservatives, though, were much more likely to belong to the Brethrens. The correlation between being a Brethren and voting Conservative in 2014 was 0.54, compared to 0.25 with voting National in 2014.

Conservatives were also much more likely to be Mormons, Jehovah’s Witnesses, Ratana, Pentecostalists or “Christian not otherwise defined” than National voters, who were more likely to be Anglicans, Presbytarians or Catholics.

Also, the average National voter is slightly less likely to be religious, whereas the average Conservative is slightly more likely to be religious.

The average Conservative is also less likely than the average National voter to be a Kiwi of European descent. The correlation between being of European descent and voting Conservative in 2014 was 0.46, compared to 0.60 between being of European descent and voting National in 2014.

All of this suggests that the main Conservative constituency is those who are like National Party voters in many demographic ways, but who do not have the same level of wealth or social status. It could even be that there is a degree of resentment among them because they are often both old and poor.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

Understanding New Zealand: Demographics of Industry

Some stereotypes are true; others are not. One of those that is not true is that Maoris dominate all working-class industries. Although (as described elsewhere) many working-class industries and occupations are heavily populated by Maoris, this isn’t the full story.

The correlation between working in the agriculture, forestry and fishing industry and being of European descent (0.37) was stronger than the correlation between working in that industry and being Maori (0.22). Part of the reason for this is the number of family-run farms, especially on the South Island, that are run by Pakeha.

Working in the mining industry was also much more strongly correlated with being of European descent (0.25) than with being Maori (0.08). This is a consequence of that a large proportion of the Maori population lives in Auckland and thus far from where most of the mining takes place.

Being Maori did have significant positive correlations with a number of generally working-class industries, in particular transport, postal and warehousing (0.47), manufacturing (0.44), education and training (0.43), electricity, gas, water and waste services (0.42) and administrative and support services (0.37).

One point to note here is that these industries are not so much working class as they are people-focused. It might be that much of the association between being Maori and being working class is because many people-focused jobs happen to be working class ones and Maori gravitate towards people-focused jobs.

The correlations with median personal income give us a good indication of which industries in New Zealand are the best paid.

The strongest positive correlations between median personal income and working in a particular industry were 0.76 for professional, scientific and technical services, 0.69 for financial and insurance services, 0.54 for information media and telecommunications and 0.49 for rental, hiring and real estate services.

The strongest negative correlations between median personal income and working in a particular industry were -0.40 for manufacturing, -0.29 for transport, postal and warehousing, -0.23 for agriculture, forestry and fishing and -0.15 for mining.

The negative correlations were weaker than the positive ones for the reason that anyone in gainful employment – in any industry – is almost guaranteed to be wealthier than all beneficiaries and the majority of pensioners.

The correlations with education reflected that the highest paying industries were also the ones that generally required the greatest degree of previous training and therefore education.

The strongest of all was the correlation between working in scientific, technical and professional services and having a Master’s degree – this was 0.94. There is nothing suprising about this because often a Master’s degree minimum is necessary for a professional job.

The correlations between working in a particular industry and being born in New Zealand are interesting because they can tell us what sort of person is most likely to successfully get through our immigration system. Because our immigration system prioritises the sort of person who has a skill that New Zealand has a shortage of, these people will be disproportionately many in some industries.

Foremost of these was scientific, technical and professional services. The correlation between working in this industry and being born in New Zealand was -0.47, which tells us that a fair number of these workers have moved here from overseas.

The correlation between being born in New Zealand and working in financial and insurance services was even more strongly negative, at -0.56. The main reason for this is probably because the bulk of this industry in New Zealand is based in Auckland and that’s also where most foreign-born people are.

Many of the people who own their own farms work at home in a family business. This is evident from the strong positive correlation between working at home and working in the agriculture, fishing and forestry industries, which was 0.81, and the very strong positive correlation between working unpaid in the family business and working in the agriculture, fishing and forestry industries, which was 0.90.

One trend that makes sense if considered from an economic psychology perspective is that the better paid a person’s job is, the more likely they are to work full time.

The industries that had the strongest positive correlation with working full-time were professional, scientific and technical services (0.52), financial and insurance services (0.48) and information media and telecommunications (0.44).

There are several reasons for this, but the major one is that anyone of a mind to learn the skills necessary to do jobs in these industries are usually also of a mind to work full-time and to earn as much money as possible during this time.

The other major one is that anyone with the capital to employ a person with these skills is likely to be a serious operator and consequently will be looking to get full productivity out of their employees.

Perhaps the best way to determine which industries are the best paid are to see which of them have the strongest correlations with high income bands.

The industries that had the strongest correlations with low income bands were hospitality in the $5-10K band; mining in the $15-20K band; healthcare and social assistance in the $20-25K band; agriculture, forestry and fishing in the $25-30K band; electricity, gas, water and waste services in the $30-35K band; and manufacturing and transport, postal and warehousing in the $35-40K band.

These are the industries for people who are generally doing it hard. The jobs are not well paid, and they are insecure, and they are often seasonal. Usually they are also jobs that have a high turnover (hospitality is particularly well known for this).

Where jobs are more stable, regular and predictable, we can also see a rise in which income band their workers belong in.

The industries that had the strongest correlations with medium income bands were construction and retail trade in the $40-50K band; administrative and support services in the $50-60K band; education and training in the $60-70K band; and wholesale trade, public administration and safety and arts and recreation services in the $70-100K band.

Construction is arguably the top of the working class industries, because even though the majority of the labour is manual it involves very high amounts of capital. The other five industries in this group (leaving aside retail trade) are the start of the knowledge industries, in that they generally demand a higher level of prior education.

The industries that had the strongest correlations with the high income bands were information, media and telecommunications, finanical and insurance services and professional, scientific and technical services at $100-150K, and rental, hiring and real estate services at $150K+.

In other words, if a New Zealander works in any of these industries, the odds are that they have a six figure salary. This is because these industries all, like construction, involve gigantic amounts of capital, but unlike construction they are knowledge industries and the workers in these industries are in higher demand and shorter supply.

Rental, hiring and real estate services involves not only big money but employees that work on a commission and not a salary. This explains why working in this industry has its strongest correlation with the highest income band.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.

An Essay Concerning Who Ought to Take the Crease at the Fall of a Wicket in T20s

When ODI cricket was invented, it took players, coaches and strategists a while to adapt to the fact that they were no longer playing Test cricket. For example, the fact that 220/3 after 50 overs is great in Tests and terrible in ODIs was not immediately appreciated.

The first ever Cricket World Cup match was famously marred by an innings of 36 off 174 balls from Sunil Gavasakar, who went on to state that “I wasn’t overjoyed at the prospect of playing non-cricketing shots and I just got into a mental rut after that.”

Gavaskar’s Test record shows that he was an exceptionally capable batsman, so the initial adjustment to such concepts as “scoreboard pressure” and “required run rate” must have been a big one, and a psychological one.

It was solved when it was realised that strike rate is about as important as average runs scored for an ODI batsman, especially the closer the game gets to the last over.

T20 cricket is still new enough that original plays are still being thought up. Every year there are new innovations, or new variations on old ones. Some concepts have to be abandoned, some concepts have to be tweaked, and some concepts have to be synthesised out of wordless intuition and perception.

This essay suggests one radical concept: that we need to do away with the old concept of batting order, and to replace it with a batting dynamic.

The major advantage of thinking in terms of a batting dynamic is that it would help the Black Caps find a place in the T20 side for Ross Taylor, who is simply too good to be left out.

A batting dynamic means no longer having a batting order in terms of openers, a first drop, a middle order etc. It means (to simplify it) to have one accumulator and one hitter at the crease at all times.

The reasons for this are mathematical. It’s better to have one accumulator than two hitters, because the hitters can lose wickets in clumps very easily and cripple the team. But it’s better to have one hitter than two accumulators, because you only have 20 overs and batting too slowly will lose you the game just as surely as losing a pile of wickets.

It’s best to consider these to be entirely separate skills – which they are, until the real slog of the last few overs.

The Black Caps have made it to No. 1 in the world T20 rankings partially by opening the batting with who are at time of writing both in the top 8 in the world – Kane Williamson at 3 and Martin Guptill at 8.

In doing so, they have a world-class accumulator in Williamson and a world-class hitter in Guptill, so all is good.

The problems arise when the first wicket falls.

Under the old concept of a batting order, this wouldn’t matter much, as it seldom does in Tests and hardly matters in ODIs.

But when the first wicket falls in a Black Caps T20 innings, the team runs the risk of making two mistakes, namely having two accumulators or two hitters at the crease.

The concept of a batting dynamic means that we divide the batsmen into accumulators and hitters, and that we try not to have two of both until the last few overs when everyone hits.

So for the T20 side, one might open with Kane Williamson and Martin Guptill, with Williamson the designated accumulator and Guptill the designated hitter.

If Williamson is dismissed early, we send Ross Taylor in. This way, it becomes less likely that the opposition will run through our lineup, as happened in February this year.

Conversely, if Guptill is dismissed first, the next hitter in line comes in to bat – perhaps Colin Munro, Corey Anderson, Tom Bruce, Colin de Grandhomme or even Tim Southee.

It doesn’t matter who it is, as long as they have a licence to hit, because the emphasis is on avoiding having two accumulators at the crease. This way we can avoid burning through the overs while scoring too few boundaries and using up our 20 with piles of wickets in hand.

So if Kane Williamson carries his bat, then Ross Taylor will not take the crease until all the other hitters are out. This means that Taylor could bat anywhere between 3 and 7 depending on the hitting ability of the other batsmen and when Williamson is dismissed.

But if Williamson is out on the first ball then Taylor comes in to ensure that the strike is always rotated to the hitter at the other end.

The worst case scenario (besides being bowled out) is that all our hitters get dismissed and we’re left with Williamson and Taylor to finish the innings. Obviously this is still an excellent outcome.

The other point is that if we aim to always have one of Williamson or Taylor at the crease until the death (let’s say until the 15th over at least), then the choice of the other batsmen in the team becomes much more straight-forward: they can simply all be hitters, as it’s very unlikely that Williamson and Taylor will both get out early.

Statistically, one would expect this to have the effect of causing the Black Caps to win by smaller margins, but to win more games, as the variance of the scores will be reduced if there are fewer hit-and-miss batsmen at the crease.

– DAN McGLASHAN

Understanding New Zealand: Demographics of Asian New Zealanders

The main reason why Asian immigration to New Zealand has been the polar opposite to Muslim immigration to Europe in terms of its success and how happy the locals are with it can be seen by the demographics of the group. In particular, the Asians moving here are considerably wealthier, better educated and more middle class – the sort of person that is most likely to make a positive contribution to those around them.

The demographics of Asian New Zealanders, like the voting patterns of this group, are primarily characterised by the fact that the majority are immigrants or descendents of relatively recent immigrants, and as such had to pass the relatively stringent points system.

For example, the correlation between being Asian and being born overseas is an extremely strong 0.91. This tells us that the vast majority of Asians living here were born overseas. The correlation between being Asian and being born in North East Asia was 0.87, but the correlation between being Asian and being born in the Pacific Islands was also fairly strong, at 0.51.

This tells us that, although the bulk of Asians in New Zealand are from China, Hong Kong, Taiwan, South Korea and Japan, there are also many South Asians, and even a fair number of Fijian Indians who are here.

The Asians that do come here certainly do so with higher educations (as mentioned above, this helps them pass the points system). The correlation between being Asian and having a university degree was 0.64 for a Bachelor’s, 0.41 for an Honours, 0.60 for a Master’s and 0.28 for a doctorate.

Interestingly, these figures are not especially indicative of higher earning. The correlation between being Asian and net median income was only 0.22, positive but not significant. This is curious considering that being Asian had a significant positive correlation with either of the two highest income bands: with $100-150K it was 0.32 and with $150K+ it was 0.28.

The reason for this might be that Asians, despite the stereotype of the Chinese slumlord, have not accumulated enough wealth to move into the rentier class yet – a class that is dominated by Kiwis of European descent and Maoris.

It may also be that Asians are much less likely than other Kiwis to live in a family where both parents are working, and that this lowers the average. Although the correlation between being Asian and earning $150K+ was 0.28, the correlation between being Asian and living in a family with an income of $150K+ was only 0.10.

There was a significant negative correlation between being Asian and living in a freehold house (-0.34) and a significant positive one between being Asian and living in a rented house (0.26). There is also a significant negative correlation between being Asian and being self-employed with employees (-0.31) and a significnat positive one between being Asian and working as a professional (0.37).

This group of correlations tells the story of Asians moving to New Zealand recently with professional educations and working professional jobs, but not having been here long enough to become old money and make investment income.

Correspondingly, there are strong correlations between being Asian and working in knowledge-intensive industries and none with either capital or labour-intensive industries.

The correlations between being Asian and working in a particular industry were 0.62 with financial and insurance services, 0.57 with wholesale trade, 0.50 with information media and telecommunications and 0.48 with professional, scientific and technical services.

That Asians tend to be middle-class can be seen from the positive correlation between being Asian and never having smoked tobacco: a very strong 0.77. As anyone who has been to Asia knows, this statistic is far from representative of the people who live there, which suggests that the sort of Asian that emigrates to New Zealand is a cut above their fellows.

The strongest correlation in this entire study – even stronger than the correlation between being Maori and voting Maori Party – is the correlation between being a Buddhist and an Asian – an immensely strong 0.95. This tells us that no matter how trendy Buddhism might be among certain Westerners in Nelson, Grey Lynn and Khandallah, the vast majority of New Zealand Buddhists are Asians who were born into it.

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This article is an excerpt from Understanding New Zealand, by Dan McGlashan, published by VJM Publishing in the winter of 2017.