What happened to people who left the benefit system during the year ended 30 June 2019

What happened to people who left the benefit syste…
30 Jun 2019
30 Jun 2019


This report is the latest in a series examining employment and other outcomes for people in the 12 months after they stopped receiving a main benefit.

It follows the outcomes for about 111,000 people who came off a main benefit in the year to June 2019, after they had been off benefit for at least a calendar month. It observed them over the next year.

It considers reasons for coming off a benefit - including destinations, types of work or study, earnings over a defined threshold ($1,512 per month) and whether post-benefit life was sustainable. It provides some age, gender, and ethnicity breakdowns.

It also compares reasons for coming off benefit and outcomes with previous periods.

Earlier reports considered the same issues for those who left during the year ended June 2016, June 2014, and June 2011 (published by Superu).

Understanding what happens when people leave a main benefit, and whether and how this has changed over time, helps guide research, policy and service design which can improve the lives of individuals and their whānau.

The analysis presented in this report, and the appended tables, uses the integrated datainfrastructure to examine real-world outcomes for people who leave the benefit system.

It shows employment and exit-related outcomes for different parts of the population and country and, by tracking those outcomes over time, we can identify where outcomes appear to be improving or not.

Understanding what happens to people when they leave a main benefit, and whether and how outcomes have changed over time, helps MSD and the wider social sector improve supports for people leaving the benefit system. This is important because we want people to be supported into sustainable outcomes that improve their own and their
whānau’s life.

There are three key uses for this analysis:

  1. Looking at current outcomes helps us understand outcomes for people who leave main benefits, and subpopulations within that. This highlights outcomes and disparities, and so will help guide action.
  2. Looking at changes in those outcomes between cohorts highlights trends or changes that affect our clients. Doing so guides where additional effort or focusing of resources may be needed.
  3. Identifying current and changing outcomes related to after-exit destinations  shows what after-exit activity correlates with better outcomes. This will help guide frontline decision-making.

    The data presented in this report highlights key facets of the analysis. In doing so, it presents only a limited portrayal of the total outputs of the analysis – those outputs are appended to this report as a set of tables for further interrogation.


There is no one methodology to define the study population and assign reasons for exit or people’s statuses over time. We have broadly adopted the methodology used in the 2020 MSD report3, to enable meaningful comparisons to be made. Exit reasons are defined in Table 6. Changes to the methodology are explained, and their impacts quantified, in the appendix. The Reliances and limitations section below outlines some of the limitations of the data and methodology adopted.

We also examine how long people who have exited from a main benefit have remained off benefit support, or have maintained earnings above a threshold, and how earnings have developed over time. We used a threshold of earnings of $1,512 per month (indexed to December 2020 dollars). This amount was chosen as it is approximately equivalent to 20 hours per week at minimum wage. Twenty hours per week is the minimum hours of work required for a sole parent to qualify for the In-Work Tax Credit.

Key Results

Given the period covered, COVID-19 has had a limited impact on the results; the full effect will be more visible in future reports.

Some outcome trends have changed over time

  • The number of people supported by a main benefit has increased.
  • The likelihood of exiting a main benefit has been decreasing since at least 2013/14, and people who exit are generally sustaining those exits at lower rates.
  • Just under half of all people who leave a benefit exit to employment. Those exits make up a similar proportion of all exits, and are sustained at a similar rate, to previous periods.

Beneath the high-level figures, and to help guide research, policy, and service design, we can see different outcomes for different parts of the population

  • The likelihood and sustainability of exit have fallen over time across all ethnicities.
  • While Māori exit benefits at similar rates to the rest of the population, they are more likely to return to a benefit in the year after exit.
  • Both exit rates and sustainability of exit are higher for people with higher level of education, and for people who have had shorter periods supported by a benefit.
  • Exit rates are higher, but the sustainability of those exits is lower, for young people compared to other age groups, and for men compared to women.

Further, the analysis considers outcomes related to different post-exit activity. It shows that outcomes vary between different exit destinations

  • Most clients who exit to employment go to industries where they earn relatively low incomes. The two largest industries that people exit to (Administration and Page 2 D Support Services, and Manufacturing) have some of the lowest employment sustainability. Exits to Manufacturing have fallen significantly over time, but it still remains the second largest industry people exit to.
  • The most popular tertiary education course type that people exit to (Society and Culture) has a high exit sustainability, but the next three main tertiary subjects clients exit to have lower than average exit sustainability.
  • Similarly, the most common course type for those who exit to targeted/industry training (Manufacturing) has the lowest rate of off benefit sustainability after 12 months. All other course types tend to have much higher rates of sustainability.
Page last modified: 25 Oct 2023