Correctly predicting the winners of the 70 electorate contests is vital for any New Zealand General Election simulation to be meaningful. There are two major reasons for this; firstly, for many of the minor political parties the electorate waiver determines eligibility to receive additional list seats in parliament, a current example being the four list seats held by the ACT Party solely because Rodney Hide won the Epsom electorate. Secondly, electorate seats can be the cause of an overhang which alters the number of seats needed to form a majority: in the 2008 New Zealand General Election the Maori Party’s five electorate seats caused an overhang of two seats in parliament, meaning the governing coalition would need 62 seats for a majority instead of the normal 61.
Unfortunately, accurately predicting the winners of the electorate seats is also quite a difficult task, mainly because they are not subject to the same level of polling intensity as the nation as a whole. This means it is necessary to model the electorate contests by some other means. I hope to do a series of detailed posts later about how the poll-averaging and election simulation works, but I figured the electorate seat calculation was likely to be a bit contentious, so I thought I’d get a rough explanation out of the way first.
There’s a handful of ways to predict these results:
- Just assume the results are unchanged from the previous General Election. This is the zero-knowledge solution, and is used by David Farrar for his Curiablog public poll average calculations [actually, it's a bit more complicated, see below].
- Calculate the results for each electorate by calibrating them against another index that you can measure. This was the method used by David Farrar in his “Electoral Pendulum” series leading up to the 2008 election. It is also the method used by FiveThirtyEight for their calculation of the “Partisan Polling Index (PPI)”.
- Try to predict the vote for an electorate by use of regression analysis on a variety of different variables. In the case of New Zealand these may include age distribution, ethnic distribution, qualifications, iwi and religious distributions, family incomes, marital and socio-economic status, occupations and others – all of which are available on the New Zealand Parliament website. This was another of the methods FiveThirtyEight used to predict the state-by-state results of the Electoral College for the 2008 US Presidential Election.
In addition to the above methods it is preferable to include electorate-level polling data where available, but it is not possible to rely on it completely due to sparsity and small sample sizes (I believe the Curiablog polling average does include electorate level polling data where available, and uses the results from the last election as a fallback position where it is not.)
For this simulation/website we’ve decided to more or less go with method #2 above. There are a few reasons for this; firstly, it’s feels intuitively correct. Secondly, there is a bit of historical data in New Zealand and overseas to indicate the swing in the electorate polling correlates with a swing nation-wide. Thirdly, it’s relatively simple (compared to method #3 above.) Fourthly, New Zealand votes under the MMP electoral system, which means that while the exact electoral results are important for determining the exact number of seats held by each party in parliament, they are of only limited importance in determining the overall result of an election. In addition to the above reasons, it is easy enough to combine this method with electorate-level polling data when it is available (most likely in the lead-up to an election,) so any unusual results should hopefully take care of themselves in the long run anyway.
Effectively the algorithm operates by assigning eight numbers to each electorate to indicate how the electorate vote in that electorate differs from the party vote in the nation as a whole. These eight numbers are determined from the results of the 2005 and 2008 NZ General Elections. For Tauranga, Epsom, Wigram, Ohariu, and the seven Maori electorates this can get a bit complicated, but for the remaining 59 electorates only one of these eight numbers is effectively meaningful; a number we denote \delta e_0, and which roughly parametrizes the swing in the vote in the electorate as viewed on a traditional left-right political scale. Positive values of \delta e_0 correspond to a swing towards the National Party, negative values to a swing towards the Labour Party, and near-zero values indicate New Zealand’s bellwether electorates. The values for some electorates are shown in the table below.

Electorate biases for a sample of New Zealand electorates. Helensville, Taranaki-King Country and Clutha-Southland are National strongholds, East Coast Bays, Ilam and Nelson are typical National-leaning electorates, Rotorua, Otaki and Hamilton West are bellwether electorates, Christchurch Central, Hutt South and Rimutaka are typical Labour-leaning electorates, and Mt Albert, Manukau East and Mangare are Labour-strongholds.
Based on the values of \delta e_0 and the current polling averages we simulate the results for each electorate if an election were held today. The probabilities for candidates from each party to win an electorate are shown below for the same electorates in the table above.

Simulation results of selected electorate seats based on current polling averages. The columns denote the National Party (NAT), Labour Party (LAB), ACT, Maori Party (MAO), Progressive's (PRO), and United Future (UNF). The Green Party and New Zealand First party are not expected to win any electorate seats, and are not shown. A large swing in favour of National is expected; in the 2008 General Election the electorates of Christchurch Central, Hutt South, Rimutaka and Manukau East were all convincingly won by Labour.
Tomorrow, I’ll show graphs indicating how many electorates each party are expected to pick up in total.
Great work – would love to see the whole table.
And yes if there has been a public electorate poll, Curiablog will go with that, otherwise assume the status quo.
I have found that there is a strong geographic component in swings in seats. For example provincial NZ turned against Labour held seats in 2005 and 2008, but less so in maor urban centres.
DPF,
Thanks. Bit concerned about your comment that there is a geographic component in swings in seats though. Do you mean changes in swings in seats between 2005 and 2008? If so that could be a bit of a problem. I guess it would mean that the simulation overestimates the probability of Labour winning the provincial seats, although shouldn’t affect the overall results too badly – at least with the parties polling as they are currently.
[...] 19, 2009 by Kiwi Poll Guy Yesterday I started on a general outline of how the electoral seat simulation works. Today I show the results for the number of electoral seats won by each party. Histogram [...]