This is the fourth installment in an ongoing series on the politics and economics of zoning reform. In the previous post, I took a look at the demographic factors underpinning variations in submission rates on the Auckland Unitary Plan between different parts of the city. That analysis showed that age and income matter quite a lot – variations in median personal incomes and the share of residents over the age of 65 explain a large share of the variation in submission rates from local boards.
In a representative democracy, voting matters. On the whole, politicians tend to respond to the interests and desires of the people who they represent. But there’s a caveat: If you don’t vote, they don’t have a good reason to listen to you.
This is important, because elected representatives get to decide how to address a lot of important issues. For instance, local governments’ choices affect:
- The availability, location, design, and price of housing – zoning rules can either facilitate or thwart peoples’ desires for a place to live
- The qualities and locations of the places where we work, shop, and play
- How we get around – local governments make decisions about investments in streets, public transport, walking, and cycling
- The quality of our local environment – air, water, and soil quality is regulated by local government.
Unfortunately, as I found when I looked at data on voter turnout in local government elections, people are increasingly disengaged from local elections. Across New Zealand, turnout appears to be structurally declining:
Why is this happening?
A useful starting place is to ask what we know about the reasons why voter turnout varies between different places. According to statistics published by the Department of Internal Affairs, in 2013 people were much more likely to vote in some local elections than others:
- Mackenzie District had the highest voter turnout – 63.7% of registered voters – followed by Buller District (62.4%) and Wairoa District (62.0%)
- Waikato District had the lowest voter turnout (31.6%) followed by Auckland Council (34.9%) and Waimakariri District (35.0%).
Why do outcomes vary so widely? As I did in my analysis of Unitary Plan submission rates, I’m going to use OLS regression to investigate a set of potential explanations. OLS regression is a statistical technique for investigating relationships between multiple explanatory variables and a single outcome variable – voter turnout in this case. Here are the hypotheses I want to test:
- H1: Size matters. Councils serving larger populations are less likely to be as engaged with the community.
- H2: Council functions matter. Regional councils and district councils serve different functions, which might be more or less ‘salient’ to voters. Regional councils are responsible for regulating environmental outcomes while district councils regulate land uses and provide roads.
- H3: Voting systems matter. Six councils use single transferrable vote (STV) rather than first-past-the-post (FPP) as a voting system. STV is a bit more complicated to understand, but it allows people to vote their conscience when choosing between multiple candidates and hence may result in more competitive, relevant races.
- H4: Competitiveness matters. Elections that are more closely contested are more likely to draw higher turnout. I’ve used candidates standing per open position as a proxy measure for competitiveness, although as the Auckland mayoral race shows, that’s not necessarily always true.
- H5: Age matters. As older people are more likely to turn out to vote, we would expect local governments with higher median ages to have higher voter turnout.
- H6: Home ownership matters. If home ownership is positively correlated with democratic engagement, we’d expect areas with higher home ownership rates to have higher voter participation.
The key findings are reported in the following table. For the non-statisticians in the audience, here’s what this quick analysis says about the hypotheses above:
- It provides support for H1 and H2 – larger councils tend to have lower turnout, while regional councils and unitary councils tend to have higher turnout than district councils.
- It also provides support for H5 – councils with higher median age tend to have higher turnout.
- It does not provide support for the other hypotheses. In 2013, at any rate, councils that used STV, had more candidates per open council position, and had a higher share of renting households did not have statistically significant differences in voter turnout.
[Technical note: I found that there was low multicollinearity between these variables, meaning that you couldn’t predict the majority of variation in, say, home ownership rates as a function of the other variables in the model. This suggests that there is low risk of understating the impact of any individual variable.]
|Dependent variable:||log(2013 voter turnout)|
|Regional Council (1)||0.111**|
|Unitary Council (1)||0.107*|
|STV voting system (2)||0.022|
|log(Candidates per position)||0.091|
|log(Share of households renting)||0.171|
|Residual Std. Error||0.112 (df = 67)|
|F Statistic||8.476*** (df = 7; 67)|
|Notes:||*p<0.1; **p<0.05; ***p<0.01|
|(1) Relative to District Council|
|(2) Relative to FPP|
In short, when we’re looking at determinants of voter turnout in local government elections, size matters, council type matters, and age matters. But there are two important caveats to this analysis:
- First, this model wasn’t very good at explaining variations in voter turnout. The adjusted R2 statistic of 0.414 indicates that this model only explains 41.4% of the total variation in voter turnout between different councils. In other words, the majority of variation is due to other, unobserved factors.
- Second, this is a “cross-sectional” model that tries to predict variations between places at a point in time. It can’t tell us much about how voter turnout might change if we adopted different policies. For instance, we can’t conclude, on the basis of this model, that we should reduce council size in order to raise turnout.
To illustrate the second point, let’s take a look at how voter turnout has changed in Auckland over the last three elections. In 2010, Auckland Council was amalgamated from eight predecessor councils. In effect, it got a lot larger. So did this reduce voter turnout?
The DIA voter turnout data doesn’t seem to support that story, at least not in such a simplistic form. Here’s a chart comparing local election turnout in Auckland with voter turnout in the rest of New Zealand from 2007 to 2013. As this shows, voter turnout in Auckland wasn’t that flash prior to amalgamation – in all predecessor councils except Rodney, it substantially lagged behind turnout in the rest of New Zealand.
Turnout rose significantly after amalgamation in 2010 before falling back again. This probably had more to do with the dynamics of those elections than the nature of the new council. In 2010, Aucklanders were more aware of the elections, which featured a competitive race for mayor. The mayoral candidates – Len Brown and John Banks – were both well-known local body politicians with genuinely different visions for the city.
In 2013, those factors probably weren’t as salient. The mayoral race was less competitive, and the new council had gotten on with doing all the million soporific tasks of local government.
So what does all this data and analysis mean, anyway? What should we do differently to get higher turnout?
I would draw two key conclusions:
- First, demographics matter to voter participation. Different groups vote at different rates, and councils with older populations tend to have higher turnout. This suggests that any attempts to address low voter turnout have to address barriers faced by different types of people.
- Second, there aren’t any obvious structural fixes related to council size, structure, or the like. Most variation in turnout between councils isn’t explained by the factors I’ve measured here, and the evidence for reducing council sizes as a way of raising turnout doesn’t seem too robust. (See the discussion of changes in voter turnout after the late-1980s amalgamations on page 22 of this document.)
In short, if we want a durable solution to low turnout rates, we need to look at some other, harder-to-measure factors, like the information available to people about local elections. But that’s a topic for the next installment.