Understanding the trends in persistent disadvantage🍋
Overall poverty and material hardship has declined significantly in NZ, which may surprise you
I explored the trends in persistent disadvantage in Aotearoa New Zealand in a recent article for Policy Quarterly. Drawing on the latest data and research, I found that overall poverty and material hardship has declined significantly. This may surprise you, as the common narrative is that poverty is widespread and growing.
However, I also found that a small proportion of the population continues to experience multiple and persistent disadvantage. Policy actions that have contributed to reducing overall poverty and material hardship haven’t benefited people stuck in persistent disadvantage. Significant changes are needed to help these people who are experiencing the greatest need.
Multiple data sources help build a coherent picture of persistent disadvantage
Developing a clear shared understanding of what the data tell us – and don’t tell us – is essential for formulating effective and enduring policy responses. If we can’t agree on the nature of the problem, there’s little chance we’ll agree on a good solution.
Building this shared understanding requires examining multiple data sources, looking at trends over time, and understanding the characteristics and limitations of each data source – that is, the metadata about the data source, such as how it’s collected, and exactly what it’s measuring.
Looking at a range of data sources helps challenge any assumptions we may have and guard against confirmation bias. Understanding the metadata helps us interpret any apparent differences in trends. And using trend data helps us “look through” short-term blips or cyclical impacts in the data.
Comparing New Zealand data with other jurisdictions can also be informative, although to draw meaningful inferences we need to understand the policy context and macroeconomic conditions in those countries.
By looking at a range of data sources, and taking a medium-term view of the data, I was able to build a coherent picture of the trends in persistent disadvantage. For this post, I’ve picked three key charts that illustrate aspects of this picture.
There is no single “right” way of measuring persistent disadvantage, and different countries use different approaches. New Zealand currently lacks official definitions of both “disadvantage” and “persistent”, and also lacks measures to track persistent disadvantage.
As a starting point, I focussed on lack of adequate material resources. I looked at some of the commonly used measures of income poverty and material hardship in New Zealand, including the Government’s official measures of child poverty. I then explored poverty and hardship that persists over multiple years, focussing on the group of people who experience multiple forms of persistent disadvantage.
Income poverty has been declining
Commonly used measures of income poverty in New Zealand look at the proportion of the population whose annual equivalised household disposable income is less than a certain percentage of the median income – typically 50% or 60%. This relative measure of income poverty allows for real income growth over time.
The following chart shows the proportion of people who live in households that have less than half of the 2007 median income. By this measure, income poverty fell from 9.1% in 2007 to 3.7% in 2021. When housing costs are taken into account, the figures are higher but follow a similar trend (Figure 1)1.
Using the median income for a fixed year (2007 in this case) means that as incomes rise, relative poverty rates will fall. An alternative approach uses the median income in each year, giving a moving poverty line. Measuring poverty in this way produces a less marked decline over the decade from 2008, because income growth lifted the median.
The proportion of people in material hardship has also been falling
The Material Wellbeing Index (MWI) is a measure of material hardship that’s commonly used in New Zealand. The MWI consists of 24 items representing different aspects of material wellbeing.
Using this measure, people in households with 12 or fewer of these items are considered to be in material hardship (MWI ≤ 12), and those with six or fewer are considered to be in severe material hardship (MWI ≤ 6).
Material hardship has been tracking downwards since a peak in 2011, as Figure 2 shows.2 In 2021, the proportion of people in material hardship was 7%. The proportion of people in severe hardship is lower, and has also been falling. It was 2.4% in 2021.
Child poverty has dropped across all official measures
The decline in overall poverty and material hardship has contributed to improvements across all of government’s official measures of child poverty. Using a measure of <60% of the median equivalised household disposable income after housing costs, the proportion of children living in poverty fell from 29.3% to 28.5% over 2013 to 2022. This is quite a small drop as it uses a moving relative poverty line, which rises over time with income growth.
The proportion of children in material hardship during the same period dropped from 18.1% to 10.3% and the proportion in severe material hardship dropped from 7.7% to 3.9%.
The proportion living in households experiencing both income poverty and material hardship dropped from 10.5% to 5.9% (Stats NZ 2022).
A small cohort of people experience multiple and persistent disadvantage
Research by the New Zealand Productivity Commission (2023) for its A Fair Chance for All inquiry looked at seven measures and three domains of disadvantage – the domains being income poor, doing without, and being left out. A person was classified as “disadvantaged” if they experienced one or more of the measures in any of those three domains.
The measure used for income poor was <60% of the median equivalised disposable household income after housing costs. Two measures were used for doing without: living in a household that was overcrowded; and living in a household that lacked heating. Four measures were used for a person who is left out: living in a jobless household; living in a household with no high-school (or other) qualifications; having no access to a motor vehicle; and having no internet access.
The Productivity Commission defined “persistent multiple disadvantage” as experiencing disadvantage in one or more domains in both 2013 and 2018.3 Their results showed that 4.2% of people in working-age households experienced disadvantage in two or more domains in both 2013 and 2018. Less than half a percent (0.4%, or 15,500 people) experienced persistent disadvantage in all three domains (Figure 3).4
Taken together with other contemporary research, along with earlier studies (which I discuss in my Policy Quarterly article), these findings suggest that the proportion of the population experiencing multiple and persistent disadvantage is relatively small, but has remained stable over multiple years.
Getting the data right matters for public policy
The findings I’ve summarised in this post are important for public-policy making, because they imply two things.
First, the improvements in poverty and hardship are significant and we need to acknowledge them. Various policy changes have been central in helping people at the bottom of the income distribution – including increases in the real value of income support for families, increases in the real value of core welfare benefits, and improvements to other social supports. Changes to these policy settings need to be well-informed by analysis of any unintended consequences.
Second, the policies that have helped reduce overall poverty and material hardship haven’t benefited those experiencing the greatest and most complex need. This suggests a different approach is needed for helping these people. We need a concerted and coordinated policy focus on people facing multiple disadvantages, including greater devolution to those closest to those communities.
By Jo Smith
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Source: Ministry of Social Development analysis of Household Economic Survey data, presented in Hughes (2022).
The Productivity Commission’s research used a longitudinal sample, which is necessary for drawing conclusions about persistence over time. By contrast, cross-sectional samples can tell us the prevalence of disadvantage at different points in time, but not whether the same or different people are affected.