Following on from the previous post about Electorate geodata, if we know the votes cast at the polling place-level we can look for geographic differences in vote distributions. Because political prefernces are correlated with socio-economic status we can then use any differences to quantify the degree of segregation in each electorate.
As in the previous post we calculate the average of the positions of the polling places in each electorate weighted by the total number of party votes cast at each polling place, and also separately weighted by the number of left-wing party votes (Labour and Green) and right-wing party votes (National and ACT). The distance between these left-wing vote and right-wing vote centres of gravity gives us a measure of segregation in each electorate. (We normalise this distance relative to the two-dimensional normal distribution defined by the standard deviations of the positions of the centres of gravity for all party votes for each electorate. It’s not the best way to measure this, but it’s a case of close enough is good enough.)
Based on the results of the 2011 election the most segregated electorate in New Zealand is Botany, shown below (click captions for interactive versions).
The centre of gravity for the left-wing vote in East Tamaki lies over 1km south of that for the right-wing vote in Dannemora. This agrees reasonably well with prior expectations based on the differences in socio-economic status between Auckland suburbs such as Howick and Otara.
The second most segregated electorate is Mangare:
Again we see a difference as the more northern suburbs such as Mangare Bridge lean (relatively) more in favour of National than more southern suburbs such as Mangare and Mangare East. The right wing vote lies approximately 1km NW of the left wing vote.
The least segregated electorate in New Zealand is Rotorua.
In spite of the rather large provincial/rural electorate the centres of gravity for the left-wing and right-wing votes lie only a few hundred metres apart, just 4km from central Rotorua.
In each of these three electorates, however, either Labour or National won a fairly high proportion of the party votes, which means that the segregation measures aren’t particularly robust. A single enclave voting out of sync with the rest of the electorate could be enough to move the centres of gravity around and mess with the results. If we confine the analysis to electorates closer to the national median, where the left wing vote was in the range of 60%-100% of the right wing vote, then the most segregated electorate was Whanganui …
…, where we can see a clear difference caused by Hawera and rural South Taranaki voting (relatively) more in favour of National, and Whanganui city voting (relatively) more in favour of Labour.
The least segregated electorate was Ohariu:
These calculations have implications for get-out-the-vote efforts in the different electorates. Given limited resources, Labour supporters in Whanganui would be best to focus their efforts on Whanganui city. Likewise, National supporters in Botany should be mainly focussing their efforts on the northern two-thirds of the Botany electorate.
Any segregation occurring in electorates also gives us some idea about how the Representation Commission goes about their task of drawing up the electoral boundaries. From the Electoral Commission website:
All electoral districts must contain electoral populations within 5% of the quota for the North Island or South Island General
electoral districts or the Māori electoral districts as applicable.
The Representation Commission, in forming General electoral districts, is required by the [Electoral Act 1993] to give due consideration to:
- the existing boundaries of General electoral districts;
- community of interest;
- facilities of communications;
- topographical features; and
- any projected variation in the General electoral population of those districts during their life.
Studying the segregation implied by the differences in vote distributions amongst polling places gives us some idea of how the Commission go about their task. We are lucky in New Zealand that because we have MMP the drawing up of electorate boundaries is largely apolitical, and we don’t really have to worry about gerrymandering. Nevertheless, there are tradeoffs between the different features given consideration, and the existence of any form of segregation as seen above is evidence that the Commission is, at least to some extent, prioritising existing boundaries over communities of interest and topographical features. This is particularly true in the case of Botany, which was added during the 2007 boundary review to reflect population growth in the Auckland region. In addition to being the most segregated electorate the Botany electorate boundary looks ugly too, which is no doubt the result of trying to carve an area out of the Auckland region for a new electorate whilst maintaing as much as possible of the existing boundaries.
Again had a few hassles dealing with the geodata. The first step was to download the 2007 electorate district boundary files from Statistics New Zealand. Unfortunately I couldn’t get ArcExplorer running, so instead I installed the GDAL package and ran the ogr2ogr wrapper from the terminal to convert them to KML format. Thirdly, we want to extract the boundaries for single electorates, which was done by selecting layers in Google Earth and exporting. Fourthly, upload the individual boundary files in KML to Google Maps Engine using the classic Google Maps interface. And finally we can use the new Google Maps Engine to import and convert old KML from classic maps, and then add the other data points as necessary as a separate layer on top. There has to be an easier way to do this without dropping $USD400 for the full version of Google Earth! Hit me up if you have any recommendations.