1. UNECE Gender Statistics Session, 18-20 October Dissemination and Use of Time Use Data The New Zealand Experience UNECE Gender Statistics Session Geneva, 18-20 October

2. UNECE Gender Statistics Session, 18-20 October Outline Background Dissemination strategy Indicators Uses of data Conclusion

3. UNECE Gender Statistics Session, 18-20 October Background New Zealand’s first national Time Use Survey 1998-99  to provide information on patterns of time use of New Zealanders Commissioned by Ministry of Women’s Affairs  raised awareness of unseen role played by women in families and community  measurement and valuation of unpaid activities – gap in official statistics Methodology  8,500 individuals 12 years and over  interviews spread over 12 month period  3 data collection documents - household questionnaire (ownership of household, availability of appliances etc) - personal questionnaire (demographic, labour force, education, income etc) - 48 hour dairy (activities undertaken, simultaneous activities, location of the activity)  72 percent response rate

4. UNECE Gender Statistics Session, 18-20 October Dissemination of results Media releases  Key findings  Labour market  Education  Health and welfare  Culture 50 tables published on website Analytical report ‘Around the Clock’ Inclusion of results in other analytical reports e.g. ‘Older New Zealanders’ Customised requests for data Unit record data available in Data Laboratory Seminars to promote the survey to researchers

5. UNECE Gender Statistics Session, 18-20 October Indicators Unpaid work  time spent on unpaid work (e.g. shopping, housework, childcare, working for a voluntary organisation), whether a primary/simultaneous activity Paid work  actual hours of paid work, work-related travel, work from home, work at non- standard times Total work  time spent on paid and unpaid work combined, ratio of unpaid to paid work time, proportion of total time spent on work Education  time spent on formal education, homework, time of day, education-related travel  helping with homework, unpaid work for educational institutions

6. UNECE Gender Statistics Session, 18-20 October Indicators Welfare and health  time spent caring for other household members/people in other households, time spent working unpaid for community organisations  time spent health maintenance/personal care (e.g. sleeping, eating, personal hygiene), exercising, smoking, leisure activities, receiving health services Culture & mass media  time spent on cultural activities (e.g. visiting museums, art galleries, performing arts etc), characteristics of individuals  time spent watching television, listening to the radio etc, location, time of day, whether a primary or secondary activity

7. UNECE Gender Statistics Session, 18-20 October Indicators Social capital  time spent volunteering (formal participation), types of association people volunteer for, characteristics of volunteers  time spent helping others or providing informal care (informal participation)  social time with friends and family Transportation  time spent travelling, reason for travel, mode of travel, times at which people travel

8. UNECE Gender Statistics Session, 18-20 October Uses of time use data Valuation of unpaid work  further the measurements in national accounts  contribution to the economy from unpaid work and production of goods and services for ones own consumption  experimental work in estimating the value of unpaid household activities  estimated value of unpaid work was 39 percent of GDP  development of household satellite accounts Work/life balance  extent to which NZ has moved to a 24 hour economy  extent to which requirement to work at unsocial times of the day/week are concentrated amongst particular groups of workers  amount of paid work that is done at workers’ homes  extent to which long hours of paid work mean less time with other family members

9. UNECE Gender Statistics Session, 18-20 October Conclusion Time Use Surveys are multi-purpose collection instruments data is relevant to almost every area of government policymaking can enhance understanding of existing statistics, so that policy development can take place in a more informed environment