Household Income and Living Survey (Income) 2024/2025 Data Collection

Information on New Zealand households’ income, housing costs and material well-being is based on data collected by Household Income and Living Survey (HILS) 2024/25. The 2024/2025 HILS is the core version of the HILS, and it runs every year. Changes made to the questionnaire in 2024/2025 From the 2024/2025 year, HILS replaced the Household Economic Survey (HES). HILS was introduced to streamline and modernise how we collect and produce household income, expenditure, net worth, and child poverty statistics. Key differences between the two surveys for users to be aware of relate to the collection of material wellbeing data and measurement of material hardship; the questions used to derive disability status; and which properties are in scope for the collection of expenditure on housing costs. For more information on the transition from HES to HILS see About the transition from the Household Economic Survey to the Household Income and Living Survey. Reference and collection period We collect HILS data over the course of a year, from 1 July to 30 June. At the interview, the respondent is asked about their income in the previous 12 months. For example, an interview in November 2024 would collect the household’s income and wellbeing in the 12 months from November 2023. This means that households interviewed for the HILS 2024/2025 survey in 2024 will include some 2023 income, while those interviewed in 2025 will include some 2024 income. Sample design. The HILS uses a stratified, multi-stage, cluster design. Primary sampling units (PSUs) – a geographic unit – are selected from the household survey frame, then dwellings within PSUs, then eligible persons within selected dwellings. A sample of PSUs was selected for the now discontinued Living in Aotearoa survey in 2021, using an updated sample design based on that introduced for HES in 2018/2019. The information on the frame used in the design was updated using 2018 Census data. A subsample of 4,368 PSUs were selected for Living in Aotearoa from the household survey frame. The 2024/2025 HILS selected 2,220 PSUs from the wider Living in Aotearoa sample, which are all common to the 2023/2024 HES. To ensure the ongoing sustainability of producing high-quality statistics, the sample size design for HILS was re-assessed ahead of the first HILS collection in July 2024. This assessment determined that a sample size of 17,000 households would achieve the balance of accuracy and sustainability into the future, enabling the continued production of high-quality child poverty statistics that meet Stats NZ’s responsibilities under the Child Poverty Reduction Act (2018). With 2,220 PSUs, and just over 11.4 households selected per PSU, we get a total selected sample of approximately 25,000 households. We assume that at least 68 percent of households will provide a full response, leaving a final achieved sample of at least 17,000 households. (The target sample sizes for the expenditure and net worth components, which are sub-samples of the core HILS, are 5,500 and 8,500 households, respectively, and these are unchanged from HES.) The final achieved sample in the 2024/2025 HILS included approximately 17,892 households. Data input Stats NZ data collection specialists visit selected households and conduct computer-assisted interviews with each eligible household member. HILS is optimised for computer-assisted in-person interviews, though for the last four years data collection specialists have also conducted computer-assisted interviews with respondents over the phone to maximise responses. In-person and phone interviewing are two examples of interview ‘mode’. We use computer-assisted interviewing software called Blaise to conduct the interviews, which guides the interviewer through the correct sequence of questions. Questions are automatically routed to ensure that respondents are only asked the questions appropriate for them. Salesforce is the centralised system we use to manage data collection, including assigning data collection specialists to households and real time monitoring of response rates. Once a household has been interviewed, the data is submitted to a central data store and a response logged in Salesforce. The data is then fed through various editing stages, before being loaded into the processing database. Despite our best efforts to obtain accurate information about respondents’ income, relying on survey responses for data of this nature inevitably introduces uncertainty. Respondents may not remember or may fail to disclose all sources of income over the past year to the interviewer. They may provide only ‘rough estimates’, describe income after tax, or forget changes to their regular income over the year. In some cases, family members may not know the income of other family members. Similarly, benefit income is often understated, particularly when it is received for only short periods throughout the year. We combine survey data on income with admin data from the IDI, a large research database managed by Stats NZ that holds microdata about people and households. It contains full tax information related to individuals, including data provided by employers for each employee (the employee monthly schedule), self-employment income, and some investment income. We also use data provided by the Ministry of Social Development about benefits paid, including Working for Families (WFF) tax credits, and Accommodation Supplement. Since 2018/2019, we have sourced annual salary and wage, and government transfer income from admin data. In the 2018/2019 HES, we asked respondents for their income but used the admin data in the published statistics. From 2019/2020, respondents were no longer asked to provide their income amounts for these income variables. Some income sources are not currently available in the IDI, including some sources of irregular income, and non-taxable income. We collect these income variables, as well as self-employment and investment income, directly from respondents. Salary and wage income is provided on an individual’s pay day and is updated in the IDI on a quarterly basis. However, self-employment and investment income rely on individuals providing their tax returns, which may be delayed before being included in the IDI. Due to this timeliness issue, we ask respondents to provide us with information on these income sources directly. Information on income received from WFF is available from Inland Revenue and from the Ministry of Social Development and this data is used for relevant households. However, for some households this income is received annually and there can be delays in this information being incorporated in the IDI due to delays in filing tax returns. For this reason, annual income from WFF is estimated for some families and is revised in the following year when more information is available. Linking administrative data The use of admin data in HILS requires individuals to be linked to the IDI spine, a secure dataset to which all datasets in the IDI are linked. This link uses address, address history, name, and date of birth. The ‘link rate’ refers to the proportion of individuals in the HILS sample that are successfully linked to the IDI. A high link rate ensures high quality data. The link rate of the overall HILS sample to the IDI in October 2025 was 93.2 percent (with a false positive rate of 0.8 percent). The link rate for children is lower than for adults, however, this does not affect the child poverty measures because these are determined from household income, which is based on adults in the household. Linking to the IDI enables us to assign admin income data (salaries and wages, and benefits) to all in-scope and eligible individuals aged 15+ years from responding households, even if they themselves did not respond to the survey. This increases the number of usable responses in the dataset. Records unable to be linked to the IDI have wage and salary, and benefit income imputed to reduce potential bias, although this will not reduce any error associated with the linked records themselves. Linking also allows for selected demographic variables to be imputed directly from admin records. Imputation for HILS 2024/25 We use imputation in the core HILS to replace missing data for households with partially completed surveys (item non-response), as well as for non-responding individuals (unit non-response) residing in otherwise fully responding households. Households are defined as fully responding when the HQ is complete, as well as the PQ of the nominated best person to answer financial questions. The demographic information collected allows us to impute the record of the non-responding household member by linking to the IDI or via imputation software (described below). Rather than discarding incomplete records, these methods allow us to make the best use of the data collected in HILS. We use imputation software when IDI information is unavailable, for the following variables: Income: employment earnings and government transfers where a respondent has not been linked to the IDI self-employment income where respondent is known to have such but has not provided a value investment income where respondent is known to have such but has not provided a value. Housing costs: local and regional authority property rates for primary property. Person demographics: age gender sex ethnicity disability status for people over the age of 2 years. Response rate for HILS 2024/2025 We set a target achieved sample rate of 68 percent and aim to achieve at least 17,000 responding households from 25,000 households that are initially selected. The final achieved sample in the 2024/2025 HILS included 17, 892 households (overall achieved sample rate of 71 percent ). The achieved sample rate (ASR) is calculated as the number of eligible households that responded divided by the total number of dwellings sampled. Essentially, it tells us what percentage of the sample responded to the survey. Eligible responding sample ASR = ____________________ Ineligible sample + eligible responding sample + eligible nonresponding sample The response rate for HILS 2024/25 was 82 percent . Response rate is also monitored at regional level and by NZDEP2018 status. The response rate is effectively an estimate of the proportion of the whole population that would have responded, from those that were eligible. It is calculated as the weighted number of eligible households that responded to the survey divided by the estimated number of total eligible households in the population. Eligible responding population Response rate = ___________________ Eligible responding population + eligible nonresponding population Besides being calculated using the sample, rather than the estimated population, the ASR differs from the response rate because it includes the ineligible dwellings in the denominator. This difference means that the ASR is less sensitive to the classification of household eligibility and is more stable over time than the response rate. Sample errors Sample error is a measure of the variability that occurs by chance because a sample, rather than an entire population, is surveyed. We can calculate the level of uncertainty around a survey estimate by exploring how that estimate would change if we were to draw many survey samples for the same period instead of just one. Sample errors are also calculated for estimates of change by considering the uncertainty associated with the estimate at each of the two time points of interest. This allows us to define a range around the standalone estimate or estimate of change, and to state how likely it is that the real value that the survey is trying to measure lies within that range. These ranges are referred to as confidence intervals and are typically set up so that we can be 95 percent sure that the true value lies within the range – in which case this range is referred to as a 95 percent confidence interval. Confidence intervals are used as a guide to the size of the sample error. A wider confidence interval indicates a greater uncertainty around the estimate. Generally, a smaller sample size will lead to estimates that have a wider confidence interval than estimates from larger sample sizes. This is because a smaller sample is less likely than a larger sample to reflect the characteristics of the total population, and therefore there will be more uncertainty around the estimate derived from the sample. The 95 percent confidence interval is used in HILS reporting and is calculated as the estimate plus or minus the sample error. We calculate sample errors using the jackknife method, which is based on the variation between estimates of different sub-samples taken from the whole sample. The tables below summarise the sample errors between 2018/2019 and 2024/2025 by income source and housing-cost type. The tables also indicate the variability of the estimates between the five surveys. Customers should take care when interpreting income or housing-costs estimates with sample errors greater than 20 percent – they are statistically less reliable than estimates with sample errors less than or equal to 20 percent. Sample errors for average annual household income, by income source (over all households) Year ended June 2019–2025 Income source Relative sample error (%) 2018/19 (R) 2019/20 (R) 2020/21 (R) 2021/22 (R) 2022/23 (R) 2023/24 (R) 2024/25 Wages and salaries 1.4 1.6 1.5 2.0 1.6 1.2 1.4 Self-employment 8.7 7.2 5.5 7.5 7.4 6.5 7.0 Investments 11.0 6.7 6.2 9.8 17.5 8.7 7.7 New Zealand Superannuation and war pensions 1.1 1.0 1.3 1.4 1.1 0.8 0.8 Other government benefits 2.3 2.7 2.2 3.7 2.7 2.3 2.5 Other regular sources 6.6 7.0 7.8 9.5 10.7 8.4 7.5 Total Gross income 1.5 1.3 1.1 1.5 1.6 1.3 1.2 R revised Sample errors for average weekly household expenditure, by housing cost type (for households with that type of expenditure Year ended June 2019–2025 Expenditure item Relative sample error (%) 2018/19 (R) 2019/20 (R) 2020/21 (R) 2021/22 (R) 2022/23 (R) 2023/24 (R) 2024/25 Property and ground rent 1.9 1.9 1.9 2.5 2.0 1.5 1.6 Other payments connected with renting 7.6 11.7 6.9 9.4 7.7 9.7 2.4 Total rent payments 2.0 2.1 2.0 2.6 2.1 1.7 1.6 Mortgage principal repayments 2.5 2.6 2.5 3.3 6.3 3.1 2.5 Mortgage interest payments 3.6 3.0 3.3 4.1 3.7 2.9 3.0 Application and service fees for mortgages 16.3 19.8 21.3 28.7 31.9 31.9 40.2 Total mortgage payments 2.3 2.3 2.4 2.8 3.9 2.4 2.3 Property rates 1.5 1.7 1.6 2.5 1.8 1.7 1.3 Building related insurance 2.0 1.7 1.7 2.0 3.8 2.0 1.3 Other housing costs 10.6 22.5 13.5 17.1 16.8 11.8 16.9 Total housing costs 1.6 1.7 1.9 1.9 2.2 1.5 1.4 R revised External influences Events that could have influenced income and housing costs in the 2024/2025 HILS data are: the Consumer Price Index (CPI) annual inflation rate decreased from 5.6 percent in the September 2023 quarter to a low of 2.2 percent in the September 2024 quarter before increasing again to 2.7 percent in the June 2025 quarter the Official Cash Rate has been slowly decreased by the Reserve Bank’s Monetary Policy Committee from 5.5 percent in July 2024 to 3.25 percent in June 2025. the annual change in cost of living for the average New Zealand household as measured by the Household Living Cost Index (HLPI) decreased from 3.8 percent in the 12 months to September 2024 quarter to 2.6 percent in the 12 months to June 2025 quarter. Lower mortgage interest payments were a large contributor to this decrease. minimum wage had two increases that are captured in the income reference period (July 2023 to June 2025), the first being from 1 April 2024 from $22.70 to $23.15, and the second from 1 April 2025 from $23.15 to $23.50. the starting out and training wage increased from $18.16 to $18.52 on 1 April 2024, followed by an increase to $18.80 effective from 1 April 2025. increases to benefits came into effect on 1 April 2024, in accordance with the Annual General Adjustment. To reflect the 4.66 percent increase in CPI over the previous year, adjustments were made to: The rates for main benefits, Student Allowances, Orphan’s Benefit, Unsupported Child’s Benefit, Foster Care Allowance, board and lodging payments, long-term hospital patient benefits, and New Zealand Superannuation. The rates and thresholds of allowances and various forms of supplementary assistance Thresholds for Disability Allowance and the Community Services Card. specific increases to main benefits included: Student Allowance increased by up to $15.96 per week Working for Families tax credits increased by $988 per year Orphan’s benefit increased by up to $14.79 per week benefits increased on 1 April 2025, in accordance with the Annual General Adjustment, with main benefits increasing by 2.22 percent (reflecting the increase in the CPI) and New Zealand Superannuation and Veteran’s Pensions rates increasing by 3.51 percent (reflecting increases in both the CPI and net average wage). The benefit increases for 2025 will only impact the 2024/2025 HILS data in households that were interviewed after April 1st. in 2024, the government introduced FamilyBoost. This is a childcare payment that is made available to low-to-middle-income families with children aged 5 and under. If families meet the eligibility criteria, they can receive a partial reimbursement of early childhood education fees. Although this reimbursement is not captured directly in HILS it will impact on a household’s ability to meet other expenses out of their household income. the unemployment and underutilisation rates have increased from 3.9 percent and 10.4 percent from the September 2023 quarter to 5.2 percent and 12.8 percent in the June 2025 quarter. Over this same period the employment rate has declined from 69.1 percent to 66.8 percent. labour cost index (a measure of wage inflation) has decreased from an annual change of 4.3 percent in the September 2023 quarter to 2.4 percent in June 2025 quarter. en-NZ