I was thinking about what the “average voter” for each
political party looks like, and my marketing research training kicked in. Pull a
bunch of demographic data from the census, try to match it to party vote
data from the last election, and hey presto, we should be able to build some
reasonably interesting profiles.
It turns out that it’s a bit harder than it seems, and as a
result there are a lot of caveats. We can’t match individual demographics to
individual votes, because if that data was available it would be a reasonably
significant breach of privacy. So we have to decide what level of granularity
is sufficient for our analysis – after digging through meshblocks and area
units, eventually I settled on electorate demographic comparisons; in electorates where there are more people
of x category, were there more or
less votes for y party?
Note that I am being careful with my
wording there (and I will do my best to be careful with my wording throughout
these posts, but will inevitably slip up somewhere). Most importantly, these
are correlations, which does not imply
causation. This is important, so I will say it again – correlation does not imply causation. If you read this post and
make unconditional declarative causative statements I will be upset at you. For
many of the correlations I found, it is entirely plausible for it to be a
coincidence or for there to be some other factor that explains the
relationship. It is tempting to say that certain groups of people are more or
less likely to vote for a particular
party, but we must remind ourselves that these statistics do not imply causation; these statistics cannot prove that the fact
that an individual belongs to a particular demographic group causes them to vote for a particular
party. I should also note that all discussions in these posts about why the correlations exist are largely guesses/opinions and not
scientific.
Just so that I don’t bore the general
audience too much, other statisticsy things that I did to try and make things
robust and fair are explained in an appendix post for those who are interested.
For each of the correlations, I’ll
include the correlation
coefficient, or r statistic. This is a measure of how strong the
relationship between the two variables is, ranging between -1 and 1. If r is
negative, then as one variable increases the other decreases, and if the number
is positive then as one variable increases the other also increases. r=0 would
indicate exactly no relationship. The larger the magnitude of the number, the
stronger the relationship. For example, r=-0.25 would be a weakly negative
relationship, r=-0.8 would be a very strongly negative relationship, r=+0.4
would be a reasonably strong positive relationship, and so on.
To give us some direction, I figured
maybe what we should do is explore some commonly held stereotypes about the
political parties, and see if they were reflected in the demographics and
voting statistics. Let’s start with income and age.
“Richer
people vote for ACT, the Conservatives, and National, poorer people vote for
Labour”
In electorates where there are more people (aged 15 and over)…
… with zero income, more people voted for ACT (r=+0.358), fewer people voted for Democrats for Social Credit (DSC) (r=-0.472)
… in the $10,001-$35,000 income bracket, more people voted for NZ First (r≈+0.6), and slightly more people voted for DSC (r≈+0.25)
… in the $15,001-$25,000 income bracket, slightly more people voted for the Conservatives (r≈+0.23)
… in the $25,001-$30,000 income bracket, fewer people voted for ACT (r=-0.575)
… in the $25,001-$40,000 income bracket, more people voted for Ban1080 (r≈+0.23)
… earning $50,001 or more (per year), slightly more people voted for National (r≈+0.25)
… earning $50,001 or more (per year), more people voted for United Future (r≈+0.4)
… earning $60,001 or more (per year), more people voted for the Greens (r≈+0.5)
… earning $70,001 or more (per year), more people voted for ACT (r≈+0.38)
In electorates where there are more people (aged 15 and over)…
… with zero income, more people voted for ACT (r=+0.358), fewer people voted for Democrats for Social Credit (DSC) (r=-0.472)
… in the $10,001-$35,000 income bracket, more people voted for NZ First (r≈+0.6), and slightly more people voted for DSC (r≈+0.25)
… in the $15,001-$25,000 income bracket, slightly more people voted for the Conservatives (r≈+0.23)
… in the $25,001-$30,000 income bracket, fewer people voted for ACT (r=-0.575)
… in the $25,001-$40,000 income bracket, more people voted for Ban1080 (r≈+0.23)
… earning $50,001 or more (per year), slightly more people voted for National (r≈+0.25)
… earning $50,001 or more (per year), more people voted for United Future (r≈+0.4)
… earning $60,001 or more (per year), more people voted for the Greens (r≈+0.5)
… earning $70,001 or more (per year), more people voted for ACT (r≈+0.38)
Discussion:
The statistics would suggest that electorates with richer people do vote for
ACT and National, but also vote for United Future and interestingly the Greens!
The Green relationship in particular is possibly explained by the support for
the Greens in central urban areas, especially in Wellington, that also happen
to be areas with higher income individuals. Electorates with more low income
individuals did not vote more for Labour. Surprisingly, electorates with more
people with zero income also had more people vote for ACT, which could possibly
be explained by those electorates having more stay-at-home housewives or young
students with no income, dependent on the high(er) income of the main
breadwinner in the household.
“Old
people vote for NZ First”
In electorates where there are more people…
… aged 15-39 years old, fewer people voted for NZ First (r≈-0.4)
… aged 50-79 years old, significantly more people voted for NZ First (r≈+0.7)
… aged 50 years and older, more people voted for the Conservatives (r increasing from +0.209 to +0.65)
… aged 50-84 years old, more people voted for DSC (r≈+0.47)
… aged 60 years and older, fewer people voted for InternetMANA (r decreasing from -0.164 to -0.406)
… aged 45-54 years old, more people voted for the Māori Party (r≈+0.25)
… aged 60 years and older, fewer people voted for the Māori Party (r decreasing from -0.124 to -0.417)
… aged 55 years and older, more people voted for National (r increasing from +0.252 to +0.515)
In electorates where there are more people…
… aged 15-39 years old, fewer people voted for NZ First (r≈-0.4)
… aged 50-79 years old, significantly more people voted for NZ First (r≈+0.7)
… aged 50 years and older, more people voted for the Conservatives (r increasing from +0.209 to +0.65)
… aged 50-84 years old, more people voted for DSC (r≈+0.47)
… aged 60 years and older, fewer people voted for InternetMANA (r decreasing from -0.164 to -0.406)
… aged 45-54 years old, more people voted for the Māori Party (r≈+0.25)
… aged 60 years and older, fewer people voted for the Māori Party (r decreasing from -0.124 to -0.417)
… aged 55 years and older, more people voted for National (r increasing from +0.252 to +0.515)
Discussion:
The stereotype largely holds up – electorates with more young people voted less
for NZ First, and electorates with more old people voted more for NZ First (Bay
of Plenty, Tauranga, Coromandel, and Whangarei). Other “old-friendly” parties
included the Conservatives, DSC, and National, while InternetMANA and the Māori Party were less popular in electorates with more people aged 60 years and older.
“Young
people are more left-wing”
In electorates where there are more people…
… aged 20-29 years old, slightly more people voted for the Greens (r≈+0.23) and the Civilian Party (r≈+0.16)
In electorates where there are more people…
… aged 20-29 years old, slightly more people voted for the Greens (r≈+0.23) and the Civilian Party (r≈+0.16)
Discussion:
The Greens do well at attracting the youth vote on the back of long-term
sustainability policies, and they had a lot of party votes in student-heavy
electorates like Christchurch Central, Dunedin North, Auckland Central,
Rongotai, and Wellington Central. Younger people probably also take politics
less seriously (or alternatively are more disenfranchised with the system),
hence the Civilian Party. It’s a little odd that there is no statistical
relationship between young people and Labour though.
The interesting thing (at least to me) about these statistics is how they reveal people’s biases. The statistics are hard cold truth, but how we choose to interpret the statistics is another matter. Whether we allow ourselves to question our biases or just selectively reinforce them is something I find fascinating. Coming up – more voter demographics!
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