Key survey features | Accuracy of the data | Interpreting the data | Consistency between 1998/99 and 2009/10 surveys | Accessing the data | Customised data requests
Key survey features
Survey reference period
The Time Use Survey 2009/10 (TUS 2009/10) was carried out from 1 September 2009 to 31 August 2010.
The survey population for TUS 2009/10 was defined as the civilian, usually resident, non-institutionalised population, aged 12 years and over, residing in private households.
The following people were excluded from the survey population:
- long-term residents of old people’s homes, hospitals, and psychiatric institutions
- inmates of penal institutions
- those living in other non-private dwellings
- members of the permanent armed forces
- overseas diplomats
- overseas visitors who expect to be usually resident in New Zealand for less than 12 months
- people living on off-shore islands (except Waiheke Island).
TUS 2009/10 had three parts: an interviewer-administered household questionnaire and person questionnaire, and a two-day (48-hour) diary, plus a diary interview.
The household questionnaire collected socio-demographic data on every member of the household, and the relationships within the household.
The person questionnaire contained questions on the following topics:
- highest qualification, and occupation and industry of each individual
- whether in past four weeks they did any unpaid work for someone in their own household, another household, or any organisation or group
- names of any organisation or group unpaid work had been done for
- whether in the past four weeks anyone had been paid to do any cleaning or laundry, gardening, or lawn-mowing for the household
- whether in the past seven days they had eaten out
- whether on the days they filled in their diary, anyone was paid to look after any child in the household.
A completed diary contained the following information:
- what activity the respondent was doing (primary activity, and any other activities done at the same time)
- the start and finish time of each activity
- the length of time for the activity
- the physical location for each activity or how the respondent was travelling (mode of transport)
- who they were with at the time. This information was only collected in the 2009/10 survey to provide key information on social connectedness
- who any unpaid work activities were being done for. This data was captured by the interviewer in the follow-up diary interview.
Accuracy of the data
In 2006, Statistics New Zealand reviewed best practice for time use surveys. The results were published in the Time Use Survey Scoping Paper and used to improve the content and methodology for the 2009/10 survey.
Estimated population size
The target survey population was estimated as 3,564,228 people during the survey reference period.
Sample design and selection
New Zealand is divided into 21,812 geographic areas called primary sampling units (PSUs). Within this sample design, PSUs were assigned to groups called strata. PSUs were assigned to a super-stratum based on its regional council area and then assigned to strata based on characteristics of the PSU. To ensure an adequate sample, characteristics included urban/rural classification, proportions of Māori and Pacific people in the PSU, and other socio-economic variables such as level of education and employment status.
PSU selection – A total of 850 PSUs were randomly selected, with the number varying across strata.
Household selection – Households in each PSU were divided into groups of approximately 10 households. One household was selected from each group.
People selection – In households with more than two eligible people, two were randomly selected. Otherwise every eligible person was selected.
Diary day allocation – Within each month, households were allocated two consecutive diary days, with equal numbers starting on each day of the week. People in the same household were allocated the same diary days. One in seven selected people would have Monday as the first diary day and two in seven would have Monday as one of their two diary days – similarly for each day of the week.
Sample allocation –To minimise the effects of seasonal variation, the PSUs were allocated evenly across the 12 months of the year.
Selected sample size
The selected sample size and design is sufficient for measuring time use in New Zealand. It is adequate for analysing the time spent on common activities specified within the classification and allows for disaggregation into large subgroups of the population.
In total, 8,543 households were selected into the survey sample. It was expected that 61 percent of these households would be both eligible and respond. The average number of usable person questionnaires per household was estimated at 1.67, giving a sample size of at least 8,500 individuals. The achieved sample size was 9,159 individual respondents.
The target household response rate for TUS 2009/10 was 70 percent. The achieved household response rate was 72 percent, the same as for the Time Use Survey: 1998/99 (TUS 1998/99). This is an acceptable response rate, resulting in data that can be deemed to represent the New Zealand population.
The household response rate was calculated as the number of eligible responding households divided by the estimated total number of eligible households in the sample. An eligible responding household contained at least one eligible adult who has responded to the diary and person questionnaire to a satisfactory standard.
Data collection method
The collection method was a combination of face-to-face computer-assisted interviewing by trained interviewers, and self-administered questionnaires.
The interviewer made up to three visits to establish contact with the selected households. One adult member (over 15 years of age) of the selected household answered the household questionnaire.
Diary and person questionnaire
After the household questionnaire was completed, two individuals aged 12 years or older (12+) were randomly selected to complete the two-day (48-hour) diary. This was left with respondents to complete on their allotted diary days. The diary contained clear instruction for the respondent to complete the diary to an adequate standard and quality, and the respondent was given additional instruction by the interviewer. Example pages were included for reference. Activity information was recorded at five-minute intervals.
When the interviewer collected the completed diaries, a person questionnaire was administered with each respondent. The diary was reviewed, to ensure the recorded information was of a high quality. Further information about the context of the activities was collected. For example, who unpaid work activities were done for.
Diary delivery and collection was recorded, which allowed the diaries to be tracked at any point. Completed diaries were returned to Statistics NZ by the interviewer.
There were rare instances of proxy interviews in the 1998/99 and 2009/10 surveys. A proxy interview was only acceptable if the respondent was too sick to complete the diary themselves, or had a disability that prevented diary completion.
Data processing and quality assurance
Processing and coding diary data
Diary responses were captured into a computer system by data entry staff using the activity classification.
A best-practice quality assurance process was implemented for the diary capture and processing. To maintain a high level of accuracy and consistency of diary coding, 46 percent of diaries were entered into the system twice. A quality assurer compared the consistency of these diaries to achieve overall consistency.
Editing and verification procedures
Logical edits checked particular coding entries in the diary with other information provided on the person questionnaire to minimise human error. Additional edits flagged unexpected activity, for example no eating or drinking on a diary day. However, the coder was able to bypass these if they accurately reflected the diary.
A minimal editing policy was adopted. Responses were only edited where enough evidence existed to support the change As a result discrepancies may still exist. For example, a respondent classified as living in a household on their own may have recorded spending time with someone they live with in their diary, or someone classified as unemployed may have recorded spending some time on work for pay or profit in their diary. These discrepancies do not affect the overall quality of the data.
To ensure the 1998/99 data was as comparable as possible with 2009/10 data, a copy of the final 1998/99 survey data was re-edited through a mapping exercise.
Validation and output checking
TUS 2009/10 incorporated a thorough validation process verifying the data for quality to ensure it was ‘clean’. This included checking for incomplete information, data that had failed internal edit controls, and other anomalies identified within the data. Comparisons were made with the 2006 Census of Population and Dwellings and other international time use surveys. To account for any anomalies, a number of macro and micro-edits were applied to the data.
Imputation for non-response
Certain key variables must be present before a questionnaire becomes usable. By imputing some of these values more questionnaires were able to be used. Imputation was done by copying values from complete questionnaires that closely matched the answers to the other questions.
Four variables were imputed: age, personal income, labour force status, and ethnicity. Less than 5 percent of personal incomes had to be imputed, while less than 0.5 percent of other variables had to be imputed.
Each responding person was assigned a unique survey weight to be used for calculating survey estimates. The weight reflected their inverse probability of selection into the survey sample.
The final weights resulted from applying integrated weighting to the selection weights. The process of integrated weighting ensured certain population benchmarks were met. This ensured each individual received the same final weight for each complete diary day.
The benchmarks used were: sex by age group, Māori by age group, regional council area, number of two-adult households, number of employed (aged 15+), survey month, and weekday/weekend.
The Statistics NZ Household Labour Force Survey (the official measure of labour force status) for the TUS reference period was used as the benchmark for employed.
Note: Unlike other Statistics NZ surveys, the TUS weights are diary day weights not household weights. This is because the survey measures days, not people.
Statistics NZ aims to minimise the impact of sampling errors. A sampling error can be measured. It quantifies the variability that occurs because a sample rather than an entire population is surveyed. The sampling errors present in this survey are at an acceptable level and enable accurate estimates to be calculated for the survey objectives to be met.
Non-sampling errors are all errors that are not sampling errors – these are not usually quantifiable and include mistakes by respondents, variation in the respondent's and interviewer's interpretation of questions asked, and errors in recording and coding data.
The sample error measure should be taken into account when assessing the reliability of an estimate. Some survey estimates are unreliable, either because of a high sampling error or because only a few individuals contribute to a certain cell.
Absolute sampling error is expressed as a percent and indicates that the actual value is likely to be between the estimate plus or minus the sampling error. So if it was estimated that the participation rate is 35 percent with a sampling error of 7 percent, then the true value is likely to be between 28 percent and 42 percent.
For averages, users often prefer the sampling error to be expressed as a percentage of the estimate. This is the relative sampling error. For example, if an estimate of 100 minutes per day has a relative sampling error of 20 percent, then the true estimate is likely to lie within plus or minus 20 percent of 100 minutes per day – that is between 80 and 120 minutes per day.
Relative sampling error = (sampling error / estimate) *100
Confidentiality and suppression
For this information release, a relative sampling error of less than 30 percent is acceptable. This excludes a labour force status of unemployed (due to the low proportion of unemployed people in the total population).
An output with a relative sampling error of 30 percent to 50 percent should be viewed with caution (flagged in tables by an asterisk *), and an error of 50 percent or more should be considered unreliable (flagged by **).
Table cells with very few contributors are suppressed (‘S’). These cells have an estimated population of less than 2,000 and are deemed to be unreliable and a risk to respondents’ confidentiality.
Estimates of movement are also subject to sampling error. A difference between estimates from TUS 1998/99 and TUS 2009/10 is statistically significant if it is larger than the associated sampling error. The change is also statistically significant if the relative sampling error is less than 100 percent.
The sampling error of the movement can be estimated as where and are the sampling errors of the two survey estimates. The same formula is approximately valid for differences between groups within the same survey, when weak relationships between groups are expected.
Figures are rounded to improve the readability of the data and to provide a more appropriate level of precision for this sample survey. Average minutes per day are rounded to the nearest whole number of minutes. Where a figure for average minutes per day is less than half a minute it is rounded to zero. All percentages and comparisons are calculated from unrounded data and then rounded to a whole number. Due to rounding, individual estimates may not sum to stated totals.
Interpreting the data
The estimates produced in this release are as follows:
|Type of estimate
||Formula and description
|Mean time spent by all the population on primary activity ‘X’ on an average diary day
Average (mean) = Total time spent on activity 'X' across all diary days / Total count of all diary days
Includes all diary days, regardless of whether the activity occurred. Estimates in these tables can be summed.
|Mean time spent by people participating in primary activity 'X' on an average diary day
Average (mean) = Total time spent on activity 'X' across all diary days where activity 'X' was recorded / total count of all diary days where participation in activity 'X' was recorded
Includes only diary days on which activity 'X' was recorded. Estimates in these tables do not sum to totals as they include participants only.
|Percentage of population that participated in primary activity 'X' on an average diary day (Participation rate)
Percentage of population that participated in activity 'X' = (Total count of all diary days where participation in activity 'X' is recorded / Total count of all diary days) * 100
Estimates in these tables do not sum to totals as they include participants only.
|Counts and percentages of who respondents were doing activities for in 4 weeks before the interview
Percentage of people participating in activity in last 4 weeks = Total number of people who did activity ‘X’ in last 4 weeks / total count of all people
Table 11 presents data from person questionnaire. It is the only table where unit of analysis is people not diary days. Use data to look at participation rates for unpaid work – more accurate for estimates for activities that don’t happen daily.
|Time of day estimates
This release includes estimates on the proportion of people working at certain time points in a day. A person is considered to be working on the hour if they started work either before or after the hour, and they finished on or after the hour
Eg – if the work activity occurs from 4pm to 5pm:
- the 4pm time point would be counted because the start time is at 4pm and the end time is after 4pm
- 5pm would also be counted because the start is before 5pm and the end is at 5pm.
Note: as people can work in multiple hourly slots, the percentages of time spent working at each time point cannot be summed.
Note: The participation rate affects the average time spent on an activity by all people in the group of interest. Activities with a high participation rate show little difference in time spent by participants and by everyone. Activities with a lower participation rate have larger differences for participants only and for all people in a group. Changes in average times between 1998/99 and 2009/10 may be due to differences in time spent by participants, changes in the participation rate, or changes to both.
Simultaneous activity estimates
Time spent on activities that occurred simultaneously, and were coded as the same activity, was only counted once. As a result, subtotals in the output tables for simultaneous activities do not equal the sum of the underlying activity categories. Coding of activity data was at a detailed level. For example, activities such as ‘preparing dinner’, and ‘cleaning kitchen’ that occurred at the same time were both coded to ‘food or drink preparation and cleanup’. The only exception to this rule applied to childcare activities. Time was counted twice when the primary activity was: travel associated with childcare activities, or other childcare activities, and the simultaneous activity was a passive childcare activity.
Tables with simultaneous data (tables 6.1 and 6.2) show the amount of time spent on each activity using the methodology described above. Each activity should be considered independently, and not added together.
Limitations of the data
Participation rates for diary data
The diary data was not designed to be used to determine general participation rates. This is due to the bias caused by diary day selection – some activities are non-daily. For example, many people only work Monday to Friday. If their diary days include a Saturday, a Sunday, or both they won't be counted as having spent time in work.
However, the diary data can provide estimates of the average time that participants spend on an activity, because the time spent and the number of diary days both include only data from participating diary days. But time spent on labour force activities does not relate well to the working week concept as averages include weekend days, weekdays, and holidays.
Data from the person questionnaire can be used to calculate general participation rates, and is presented in table 11.
Some differences exist between participation rates collected in the diary and the person questionnaire, particularly around unpaid and paid work. For example, an individual may have stated in the person questionnaire that they did no household work for their household in the last four weeks, but entered a household work activity in their diary. The discrepancy is acceptable, due to the different collection modes, but should be taken into account when analysing participation rates.
One of the purposes of statistical analysis is to place the data in perspective and this often done by comparing means or proportions. However, many factors can contribute to differences between any two subgroups of the population. Our outputs give valid estimates of the differences, but are not adjusted for other contributing factors.
An example – If estimates show that Europeans spend more time on household work than other ethnicities, it could be tempting to conclude that ethnicity is the factor influencing this estimate. However, the European population tends to be older than the other ethnic populations, and older age groups have a different pattern of time use than other age groups. A better conclusion could be that because the European population has more older people, they are more likely to spend more time on household work.
Standardisation has not been used within this release. However, when looking at ethnic differences age effects were taken into account. In most cases, ethnic differences do exist, and age effects only partly contribute. Where the differences could be mostly explained by the differing age distributions, this is noted explicitly.
Comparability with other data sources
The results in this release are internationally comparable. The development and design of TUS 2009/10 followed United Nations guidelines for time use statistics.
Further concepts and definitions
Activities recorded by respondents in their time use diaries were entered into an electronic system using the New Zealand Activity Classification for the Time Use Survey (ACTUS). This was based on the classification used for TUS 1998/99 which met international standards at that time. For TUS 2009/10 improvements reflect the needs of users, satisfy world changes such as the use of technology, and improve international comparability.
For this information release, a copy of the 1998/99 data has been mapped to the 2009/10 classification to ensure the highest level of comparability between the two surveys.
The conceptual basis for the New Zealand (and also Australian) activity classification is Aas' four categories of time:
- necessary time (personal care activities) – includes personal care activities such as personal hygiene and grooming, sleeping, eating and drinking, private activities, personal medical care, and travel associated with personal care. These activities serve basic psychological needs.
- contracted time (employment or education activities) – includes all types of labour force activity and education and training activities. These activities often constrain the distribution of other activities over a day.
- committed time (unpaid work activities) – includes household work, child care, purchasing goods and services, and other unpaid work activities. This describes activities to which a person has committed him/herself because of previous acts or behaviours or community participation.
- free time (leisure activities) – includes religious, cultural, and civic participation activities, social entertainment, sports and hobbies, and mass media and free-time activities. This is the amount of time left when the previous three types of time have been taken out of a person's day.
ACTUS can also be mapped to the equivalent United Nations draft international classification (IACTUS). TUS 2009/10 did not use ICATUS because a key objective was comparability with the 1998/99 survey.
To be a 'child’ a person must usually reside with at least one parent, and have no partner or child(ren) of their own living in the same household. A ‘child' can be of any age.
- Young child(ren) – under 15 years living with parent.
- Older child(ren) – 15 years and over living with parent.
There are two main types of child care:
- active child care – when the respondent stated they were actively looking after a child, as either a primary or simultaneous activity. Includes physical care of child, teaching/helping a child, playing/reading/talking with a child, or accompanying or supervising a child
- passive child care – when the respondent’s main activity did not concern the child, but the child was under the respondent’s care. This was only coded as a simultaneous activity when the respondent had not recorded active care for that activity.
Child care is often done at the same time as other activities, so analysing primary child care alone would result in an underestimate of childcare activities. For example, a person can record 'cooking' as their primary activity and 'available for child care' as a simultaneous activity.
Passive child care was collected in two ways:
- responsibility method – interviewers asked respondents whether they were responsible for anyone during the activity time. If so, this was coded to passive child or adult care
- respondent-recorded care method – respondents recorded passive care as a simultaneous activity in their diary.
Passive child care is one of only two non-travel activities that could be done while sleeping (the other being 'on call for work while at the workplace'). Due to different methods used to record and estimate passive child care, the estimates in this release may not be comparable with international estimates.
Ethnicity is the ethnic group(s) that people identify with or feel they belong to. Ethnicity is a measure of cultural affiliation, and is self-perceived. People can belong to more than one ethnic group. Respondents were counted once in each ethnic group reported. This means the total number of responses for all ethnic groups can be greater than the total number of people who stated their ethnicities.
Because the classification groups Middle Eastern / Latin American / African and ‘other’ were too small for analysis they are excluded from tables showing estimates with ethnicity as a subgroup.
This variable allows analysts to distinguish what role individuals play within their family unit. Ten family roles are used in the output tables:
- coupled parent or partner living with youngest child aged 0–14 years
- coupled parent or partner living with child or children all aged 15 years or older
- sole parent living with youngest child aged 0–14 years
- sole parent living with child or children all aged 15 years or older
- partner in couple with no children (includes without children or children who have moved away)
- child aged 12–17 years living at home with parent/s
- child aged 18 years or older living at home with parent/s
- person aged 15–64 years living alone
- person aged 65 years or older living alone
- other individuals who are not a parent or child, who live with others but not with a partner, such as people in a flatting situation.
These definitions may clarify the roles above:
- couple – two people who usually reside together and are legally married or in a civil union, or two people who are in a consensual union
- parent – the mother, father (natural, step, adopted or foster), or 'person in a parent role' of a 'child in a family nucleus'. An individual will also be classified as a parent if they are the partner of a parent
- parent in couple with children – a couple with child(ren) under 15 years. Also includes an individual if they are the partner of a parent.
- sole parent – the parent in a one-parent family
- sole parent with children – a sole parent with child(ren) under 15 years.
A household is either one person who usually resides alone, or two or more people who usually reside together and share facilities (such as eating, cooking, bathroom, and toilet facilities, and a living area), in a private household. At least one household member must be aged over 15 years.
Internet and computer use
For activities that used the Internet, or the computer, the activity’s purpose was coded. For example, shopping online was coded to purchasing goods and services, and chatting via online social networks was coded to socialising and conversation. General computer use for no specified purpose, such as browsing the Internet, was coded to the other Internet and computer use activity category.
An Internet-use derived variable was created to flag whether activities were being done online. Data using this derived variable is not provided in this release, but will be available in datasets through the Statistics NZ Data Lab.
Labour force status
Employed – all people in the working-age population (those aged 15 years and over) who:
- worked for one hour or more for pay or profit in the context of an employee/employer relationship or self-employment
- worked without pay for one hour or more in work that contributed directly to the operation of a farm, business, or professional practice owned or operated by a relative
- had a job but were not at work due to their illness or injury, personal or family responsibilities, bad weather or mechanical breakdown, direct involvement in an industrial dispute, or being on leave or holiday.
Full time – people who are employed full time usually work 30 or more hours per week.
Part time – people who are employed part time usually work less than 30 hours per week.
Unemployed – all people in the working-age population who, during a defined time period, were without a paid job, were available for work and had actively sought work in the past four weeks, or had a new job to start within the next four weeks.
Not in the labour force – all people in the working-age population who are neither employed nor unemployed. This category includes:
- retired people
- people with personal or family responsibilities, such as unpaid housework and child care
- people attending educational institutions
- people permanently unable to work due to physical or mental disabilities
- people who were temporarily unavailable for work in the survey reference week
- people who are not actively seeking work.
A respondent’s labour force status was derived from answers to the person questionnaire.
Paid for domestic or household services
Information was collected in the person questionnaire on services that respondents paid someone to perform, such as looking after children, or cleaning, laundry, gardening, or lawn-mowing for the respondent’s household. Respondents were also asked whether cleaning and gardening services were provided by a household member, or someone who did not live in the household. This data is not provided in this release but will be available in datasets through the Statistics NZ Data Lab.
Primary activities and simultaneous activities – see Definitions.
Three residual categories were used for diary entries:
- response unidentifiable – used when the information in the diary was unreadable or otherwise unidentifiable
- response outside scope – used when the information was outside the survey scope
- not stated – used when information was missing.
All travel activities were associated with the next activity recorded, with the exception of driving home, which was associated with the previous one. For example, if a respondent drives to work but stops off at the shops along the way, the travel time was coded as ‘drive to shops’ followed by ‘drive to work’.
Who the activity was done for
The interviewer filled in information about who an activity was done for, for each committed time activity, when the diary interview was conducted. More than one response could be recorded for each activity. There are eight response categories:
- own household (including self)
- household member aged 0–13
- household member aged 14+
- another household or individual
- non-household member aged 0–13
- non-household member aged 14+
- organisation or group
- response unidentifiable.
Who the activity was done with
Data was collected about other people who were present when the activity occurred. There are five response categories:
- with family members from their own household
- with family members who live in another household
- with other known people (this may include non-family household members)
- with unknown people.
Weekdays and weekends
Weekdays are the time between 4am on Monday and 4am on Saturday. Weekends are defined as the time between 4.00am on Saturday and 4.00am on Monday.
Consistency between 1998/99 and 2009/10 surveys
TUS 2009/10 was designed to be as comparable as possible with TUS 1998/99. The following section highlights the main changes between the two surveys. Minor design differences between the surveys do not affect the overall quality of the survey data or the ability to make comparisons between the two surveys.
Edits to the original TUS 1998/99 estimates
Minor changes to the activity classification between the surveys created inconsistencies in the way activities were coded, and the range of activities that were coded. For example, sleeplessness was an addition to the TUS 2009/10 classification. These changes were made to meet user demands, ensure international comparability with other TUS, and because of real-world changes (eg technology). The New Zealand classification is now closer to the Australian Time Use Survey classification and the quality of data collected has improved.
To produce high-quality comparative estimates of time spent on activities for the two surveys, the activity codes used in 1998/99 were matched to those used in 2009/10. This was done through a mapping exercise at the lowest level of the activity classification (using individual synonyms).
Synonyms are used to group together and code literal statements of activities written in the respondents’ diaries. For example, the literal statement ‘watching the news on television’ would be coded to the synonym ‘watching television’.
As a result of the edits, the 1998/99 estimates in this release differ from those originally published in 1999.
Changes to the activity coding rules between the surveys
Eating and drinking
Initially in 2009/10, eating/drinking while also socialising was coded as 'socialising and conversation' with no simultaneous activity of eating and drinking. In 1998/99 the two activities of eating/drinking and socialising were both recorded as primary and simultaneous activities. The 2009/10 data has been edited to add eating/drinking as a simultaneous activity. However, it is likely that in the 2009/10 data less time was coded to eating/drinking as a primary activity than in 1998/99.
In 2009/10, school breaks such as lunch or morning tea were coded as eating/drinking, whereas in 1998/99 they were coded as formal education. It is therefore likely that the 1998/99 data has more time coded to formal education than the 2009/10 data.
Other unpaid work
In 2009/10 unpaid work activities involving household work, child care, or purchasing goods and services, were coded to specific categories, rather than to the general ‘other unpaid work’ category. These rules were not as strictly adhered to in 1998/99. As a result, more time was coded to other unpaid work in 1998/99 than in 2009/10. In particular, this affects the unpaid work activities performed for another household.
Playing, reading, talking with child
In 2009/10, ‘talking to a child’ was coded to child care, while in 1998/99 it was coded to socialising and conversation. The 1998/99 data has been re-coded so that talking to a child is now coded as child care. However, it is unlikely that all 1998/99 incidences of talking to children have been re-coded. As a result, more time was coded to playing, reading, talking with child in 2009/10.
Religious, cultural, and civic participation
This category includes time spent filling in the TUS diary. This is a civic activity performed only by TUS respondents, so caution is required when generalising results for this category to the wider New Zealand population. For example, although people spent an additional four minutes on average on religious, cultural, and civic activities compared with 1998/99, half this increase is due to spending two minutes more filling in the TUS diary.
In 2009/10, if a respondent recorded being in bed and a short period later they recorded sleep, the entire sequence was coded as sleep. In 1998/99, lying in bed before sleeping was coded as thinking, reflecting, relaxing, resting, and planning. Where possible in the 1998/99 data, activities of this type have been re-coded to sleeping; however it is possible that not all incidences were changed. As a result, more time was coded to sleeping in 2009/10 than in 1998/99.
Socialising and conversation
In 2009/10, intermittent social-networking activities such as texting were coded to the total period allocated to them in the diary. Similarly, online chatting on the Internet could be coded as an activity along with a simultaneous Internet-based activity. There was much lower reporting of these social networking activities in 1998/99, so it is likely that more time was coded to socialising and conversation (particularly as a simultaneous activity) in 2009/10 than in 1998/99.
Thinking, reflecting, relaxing, resting, and planning
In 2009/10, activities such as lying in bed, resting, or relaxing were only coded if there was no simultaneous activity. This rule did not exist in 1998/99 when both the primary and simultaneous activities were coded. Consequently, in 2009/10 less time was coded to thinking, reflecting, relaxing, resting, and planning than in 1998/99.
Who the activity was done for
The estimates for time spent on unpaid work for other households are not comparable between the two surveys due to coding differences. In the 1998/99 survey, when unpaid work was done ‘for own household’ and ‘for other household’ at the same time, in most cases this was only coded as unpaid work ‘for own household’. This resulted in an underestimate of unpaid work ‘for other household’ in 1998/99.
Other changes between the surveys
Changes to calculating sampling errors
In original publications for the 1998/99 survey, sampling errors were based on a model. A more accurate jack-knife method was used on the subsequent 1998/99 comparison datasets, so the sampling errors are different to those previously published.
Sampling methodology for Māori
For both surveys, the samples were designed to amplify the number of Māori within the sample. However, an additional Māori booster sample included in 1998/99 was not included in the 2009/10 design. As a result, the number of Māori in the 2009/10 sample is about half that in the previous sample. In 2009/10, the sampling errors for the top 11 activity categories for Māori vary from about 2 percent to over 90 percent. Much of this variation is due to real differences in the activity patterns and cannot be separated from the change in the Māori sample size. These changes have not affected whether or not differences were significant.
Sampling errors for other ethnicities
The number of Asian people in the sample doubled as a result of an increase in their New Zealand populations; consequently, the sample errors for this category have fallen about 30 percent.
Similarly, the number of Pacific peoples in the sample increased about 50 percent; the corresponding sample errors fell about 20 percent.
Ethnicity classification for ‘New Zealander’ responses
In 1998/99, a New Zealander response was included in the New Zealand European category. For 2009/10, New Zealander responses to ethnicity (and similar responses such as Kiwi) were classified to a separate category at level four in the ‘Other Ethnicity’ group. This is unlikely to affect European ethnic group comparisons between the two surveys because New Zealanders are a small group (2 percent of the time-use total population) with similar characteristics (age, sex, labour force status) as the total population.
Collection of ‘Who else was with you’ diary data
Collecting this data in the diary is standard practice in most international TUS. It is an important measure of social connectedness/social capital (ie contact with family and friends) and was introduced to the 2009/10 survey as part of the review of best practice for TUS.
Questions on formal unpaid work for an organisation
The person questionnaire in 2009/10 asked respondents for the name of the organisation(s) they performed unpaid work for. This allowed for a split between non-profit organisations and other organisations, which has important implications for the volunteering rate reported in the non-profit institutions satellite account (NPISA). The first account used formal unpaid work data from the 1998/99 survey, including all volunteering. The next NPISA will use volunteering rates from the 2009/10 survey. However, it will only include volunteering done for non-profit organisations, and although more accurate, will not be truly comparable with the first NPISA.
Question change regarding unpaid work for another household
A higher proportion of 2009/10 respondents reported doing unpaid work for another household than in 1998/99 in the person questionnaire. It is likely that this finding is a result of a wording change to the relevant question. In 2009/10, respondents were asked whether they did any cooking, cleaning, or other household work for another household without pay. In 1998/99, respondents were asked whether they had done any household work, without specifying the cooking or cleaning.
Changes to methodology for calculating time spent on simultaneous activities
To produce comparable data estimates, the 1998/99 comparison data used in this release used the same approach as in 2009/10 . As a result, estimates of time spent on simultaneous activities differ from those published in 1998/99.
Accessing the data
Later in 2011, TUS 2009/10 and the comparable TUS 1998/99 datasets will be available through the Statistics NZ Data Lab, alongside a comprehensive user guide. This will give researchers the opportunity to carry out their own analysis on time-use microdata, with the help and support of Statistics NZ.
For more information about accessing the data, see Contacts.
Timed statistical releases are delivered using postal and electronic services provided by third parties. Delivery of these releases may be delayed by circumstances outside the control of Statistics NZ. Statistics NZ accepts no responsibility for any such delays.
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Customised data requests
Statistics NZ will publish analytical reports using the TUS 2009/10 data throughout 2011/12. If you would like to join the Statistics NZ Time Use Survey Data Users Group, please contact us.