Household net worth data collection 2017/18

The target population for HES is the usually resident population of New Zealand living in private dwellings, aged 15 years and over (15+). This population does not include: overseas visitors who expect to be resident in New Zealand for less than 12 months people living in non-private dwellings (eg hotels, motels, boarding houses, hostels, and homes for the elderly) patients in hospitals, or residents of psychiatric or penal institutions members of the permanent armed forces in group living facilities (eg barracks) people living on offshore islands (excluding Waiheke Island) members of the non-New Zealand armed forces non-New Zealand diplomats and their families. Children at boarding schools are also not surveyed, but housing costs on behalf of those children are included in the record-keeping of the parent or guardian. The survey population is therefore marginally different from the target population. For survey purposes, a ‘household’ comprises a group of people who share a private dwelling and normally spend four or more nights a week in the household. They must share consumption of food or contribute some portion of income towards the provision of essentials for living as a group. HES components As in HES (income), HES (savings) has four survey components: a household questionnaire an housing expenditure questionnaire an income questionnaire for each household member aged 15+ a material well-being questionnaire for one member per household who is aged 18+ (chosen randomly). The HES (savings) survey, besides collecting information from sampled New Zealand households on the above topics, also collects information on New Zealanders’ savings, assets, and liabilities. Topics covered in the survey to collect data on wealth include: Household net worth = (what you own) LESS (what you owe) Assets (what you own) Liabilities (what you owe) Real estate Owner-occupied residences Other residential and non-residential property Real estate loans Owner-occupied residence loans Other residential and non-residential property loans Other physical assets Consumer durables Valuables Other liabilities Consumer durables loans Other debt (eg credit cards) Education loans Financial assets Currency and deposits Investments (eg shares, mutual funds) Net equity in unincorporated businesses Net equity in trusts Pension funds (superannuation funds) Total Assets Total Liabilities We ask questions on assets and liabilities within existing HES modules in the income and expenditure questionnaires, or collect the information as separate sets of questions (modules) at the end of the income questionnaire. Topics related to net worth covered within existing HES modules include: principal residence [housing costs] other non-investment properties [other property] mortgages for principal residence and non-investment properties [mortgages and loans] superannuation schemes [private superannuation] New Zealand financial assets [investments] New Zealand investment property assets and liabilities [investments] overseas property and financial assets [overseas income]. Topics covered in separate modules include:: life insurance equity in businesses motor vehicles, collectibles, and cash assets household durables trusts non-property debt. Reliability of survey estimates Two types of errors are possible in estimates based on a sample survey – sampling error and non-sampling error. Sampling error: Sampling error is a measure of the variability that occurs by chance because a sample rather than an entire population is surveyed. We calculate sampling errors using the jackknife method. It is based on the variation between estimates of different subsamples taken from the whole sample. Given a certain sample size, the level of sampling error for any given estimate depends on the number of sampled households/individuals in the category of interest and the variability of the estimate due to the random nature of the sample selection. As the size of the sampled group decreases, the relative sampling errors (RSEs – sample error as a percentage of the estimate) will generally increase. For example, the estimated average annual household income from self-employment would have a larger RSE than the estimated average annual household income for households receiving income from wages and salaries. In the tables accompanying the Household net worth statistics, only income or expenditure estimates with RSEs less than or equal to 20 percent are considered sufficiently reliable for most purposes. Although estimates with RSEs over 21 percent are also included, these should be used with caution. Estimates with RSEs over 100 though also provided, these are not deemed very useful. Non-sampling errors: Non-sampling errors arise from biases in the patterns of response and non-response, questionnaire design, inaccuracies in reporting by respondents, and errors in recording and coding data. We endeavour to minimise the impact of these errors by applying best-practice survey methods and monitoring known indicators (eg non-response). Proxy A proxy may provide information in ‘family type’ households where: the whole household is informed about the survey. All agree to participate, but are not able to be present when the questionnaires are administered children are away at boarding school people don't work and have no source of income people are elderly, sick, or mentally incapacitated. In all proxy interviews, the interviewer must be convinced the proxy is totally familiar with the other respondent’s information. Population weighting adjustments The population weighting process takes account of under-coverage in the survey for specific population groups, such as young males and Māori. Weighting plays a vital role in estimation. We give each unit in the sample a weight that indicates the number of people it represents in the final population estimate. Weighting ensures that estimates reflect the sample design, adjusts for non-response, and aligns estimates with the current population estimates. For household surveys, deriving the weight is a multi-phase process. The first stage of weighting involves calculating a unit’s initial weight. The initial weight depends on the sample design and equals the inverse of the selection probability. The second stage involves adjusting the initial weights to account for unit non-response. This refers to a household without information, or where the amount of information provided (and/or quality of) is insufficient to be a response. The initial weight of a non-responding unit is reduced to zero, while initial weights of responding units are scaled up – by combining factors within the estimation group (eg region, ethnic densities, urban/rural, and interview quarter). The final stage in the weighting process is integrated weighting. This process ensures we give all eligible responding individuals within a household the same weight so we can produce household statistics. Integrated weighting also aligns estimates with externally sourced population individual and household benchmarks, and adjusts for under-count of specific sub-population groups (eg young males and Māori). The population used for the integrated weighting was benchmarked to estimates based on the 2013 Census. HES benchmarks The person benchmarks used for HES are: regional population estimates; children sub-population estimates by three age groups; adult sub-population estimates by sex and 13 age groups (including 75 years and over); and adult Māori sub-population estimates by two age groups (including 30 years and over). The household benchmarks are two categories of household composition (two-adult households and non-two-adult households), and these categories split further by regions. Population estimates are based on the 2013 Census. Consistency with other periods Although we adjust survey results for various demographic variables (age, sex, and region), there can be variability in survey estimates from one survey collection period to the next. This variability is because a different group of households is selected for each survey. Using material well-being data The material well-being questionnaire asks about ownership of particular items, or doing certain activities, and the extent that people economise. We also ask respondents how they rate their life satisfaction and whether income meets everyday needs. From the material well-being questionnaire we publish selected results for satisfaction levels, and for adequacy of income to meet everyday needs. Stats NZ does not produce an index measurement of material well-being from this data. Other agencies can use such index data in conjunction with other measures (eg income, expenditure on housing costs, or household demographics), to give an indication of the material standard of living of New Zealanders. Suppressed estimates We suppress estimates in this release if based on fewer than five people or households for total or mean values, or fewer than 10 people or households for median values. Publishing would be a risk to respondents’ confidentiality. Data is no longer suppressed if a relative sample error is 51 percent or higher (21 percent for cross-tabulated data). en-NZ