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Time use surveys

    Note: This section of the manual draws extensively on the United Nations publication Guide to Producing Statistics on Time Use: Measuring Paid and Unpaid Work (2005). Readers are strongly encouraged to consult the above mentioned publication as more details as well as additional information are covered at length.

  • + Uses of time use data for gender statistics
    • Time use data show how individuals allocate their time to specific activities over a specified period - typically over the 24 hours of a day and over the 7 days of a week (United Nations, 2005). These data are generally obtained through two types of survey instruments: 24-hour time diaries and stylized analogues of these diaries. In time diaries, the respondents report all activities undertaken over a prescribed period of time and the beginning and ending time for each activity. In stylized versions of diaries, respondents are asked to recall the amount of time allocated to certain activities over a specified period of time. Compared to stylized questions, diaries can be a more reliable tool for measuring time use and thus, a more reliable tool in obtaining gender statistics, however, the amount of resources required and the burden on the respondents are considerably higher.

      Time use data are the basis for obtaining gender statistics related to several topics: time allocation patterns; unpaid work; participation in all forms of paid work; working time, work locations and scheduling of economic activities; work-family balance; investment of time in education and health; welfare and quality of life; and intrahousehold inequality.

      Time allocation patterns

      Time use data can show differences between women and men in time allocation patterns (type of activities and their schedule during the specified period of time), reflecting differences in roles and expectations with regard to family, domestic life, and participation in work and social activities outside the home. Women, for example, tend to spend more time than men taking care of children and less time than men working for payment outside of their homes. The schedule of various episodes of activities may also be different for women and for men. For example, men may be more likely than women to spend time for paid work activities during the night. Or, the time spent with children may be more concentrated for men in the evening hours and in the week-end. Gender differences extend beyond the traditional distribution of roles in paid and unpaid work. Different patterns of leisure activities may be described for women and for men. In some societies, for example, men may spend time more often than women in sports and fitness activities.

      Unpaid work

      Time use data are essential in estimating the participation of women and men in unpaid work (activities unaccompanied by remuneration) and the value of this unpaid work for the economy. Some types of unpaid work are not covered by conventional labour statistics or the System of National Accounts (SNA). Conventional labour statistics are limited to activities that contribute to the production of goods and services as defined by the SNA and cover mainly market activities and some unpaid non-market activities. Unpaid work referring to own account production of services are outside the general boundary of SNA and therefore not covered at all in conventional labour force statistics. Examples of unpaid work are cleaning dwellings; small repairs; preparing and serving meals; caring for and instructing children; caring for other persons in the household; as well as certain types of volunteer community services.
      Data on time use for those types of activity are typically obtained in time use surveys or time use modules attached to labour force surveys, living standard surveys or other multi-topic surveys. The data obtained can be used to estimate household production in satellite accounts that extend measurement of gross domestic product (GDP) to include non-SNA production, making the national accounts more complete and comparable across countries. At the same time, time use data on unpaid work is crucial in making the contribution of women to the economy and society more visible. Women, more often than men, tend to be involved and spend a great amount of time in unpaid work in the home and community. When only cash transactions are taken into account in measuring the economic production, a large portion of women’s work remains unaccounted for.

      Participation in all forms of work

      Time use data have an important role in improving estimates of employment and labour force participation through more extensive capturing of the participation in non-market activities that are within the general productive boundary of SNA. These activities refer to the production of goods for own consumption, such as: agricultural work, fishing, hunting, cutting firewood, carrying water, threshing and milling grain, making butter and cheese, slaughtering livestock, etc. Such activities are taken into account by current concepts of labour force and employment and should be covered by conventional labour statistics. However, due to bias in data collection, these activities are often underreported in labour force surveys or censuses. Women, in particular, tend to have their participation in labour force underreported, because they tend to be more often involved in non-market economic activities and because it is often assumed (by interviewers or respondents themselves) that women’s activities are limited to the domestic area. Time use surveys are more suitable to capture the involvement of women and men in atypical cases of non-market activities that should be considered within the general productive boundary of SNA, and to obtain a measure of the amount of time allocated to those activities.

      Working time, work locations and scheduling of economic activities

      Characteristics of work such as working time, work locations and scheduling of economic activities are often different for women than for men. Time use data can be used to improve the measurement of time spent for economic activities and to better identify work locations and scheduling of activities during the week and within 24 hours. Time use surveys may be able to provide better estimates of working time than labour force surveys, especially when the distinction between periods of work and non-work may be unclear or when such periods are frequently interchanged. They may also provide better estimates of when work is carried out, and on what locations. Work is increasingly undertaken in non-traditional places. A good portion of paid work may be performed at home or while commuting. Contextual information - for whom and for what purpose is the activity done - is important for differentiating activities outside workplace that are actually performed for an institution even if may appear as personal. Reporting work-related activities may also help to distinguish non-paid activities that are performed for work. For example, self-employed persons may carry out various activities that are important for their business but are not formally remunerated, such as socializing.

      Work-family balance

      Time use data can provide great insights into the gender specifics of interaction of work and family life, and the relationship between labour force participation of various female and male household members and their involvement in the domestic care activities. Time use data can also show how the gender division of labour is changing with the change in the balance between market and non-market activities. This is especially the case when there is available supplementary information on local infrastructure, domestic appliances and consumption of market services that substitutes for households own labour (maids, child care centers, nursing care).

      Investment of time in education and health

      Time use data can contribute to understanding of gender differences in investment in education and health. Data on children’s investment in education may refer to time use spent on activities such as being in school, doing homework or other learning activities, as well as on the balance between time spent on learning activities and the time spent in employment or doing housework. Data on time use can also be used to better understand gender differences in physical access to school when girls and boys do not use the same transportation means or do not attend the same schools. Furthermore, data on use of technology such as Internet, computers, or telephones in performing various activities can be used to assess gender gaps in access to communication and technology.

      Time use data can be used to understand the relationship between gender and health. Commonly, time use data cover activities of care for sick and disabled, which are more often the responsibility of women than of men. Time use data may also cover transportation to health facilities and waiting time to obtain a consultation, which may show gender differences in accessing health services. Finally, some data needed to assess the time lost to ill health, which are often used as a measure of health status for individuals and a non-consumption indicator of poverty, can also be obtained in time use surveys or multi-purpose surveys collecting data on health and time use.

      Welfare and quality of life

      Time use data on leisure and the psychological well-being experienced while performing various types of activities can be used as measures of welfare and quality of life for women and men. In certain contexts, shortage of leisure can be an indicator of poverty. Poor people have to spend most of their time to produce the income required for basic needs and do not often have time for leisure. Leisure may include social interactions, relaxation, cultural activities, solitude, physical exercise, or participation in sports or games. However, the definition of an activity as leisure is cultural and varies from person to person. Cooking is often given as an example of an activity that may be a chore for one person, but leisure for another person. Women are usually responsible for cooking, and this activity is often identified as a household chore. However, cooking may be performed once in a while, for example, by the husband, as a hobby, and therefore it may be identified as leisure. Shopping is another example of activity that can be defined as household chore or individual leisure.

      Variables that measure psychological well-being while performing each activity – for example whether people experience negative emotions such as tension or stress, or positive feelings, such as enjoyment or content – can also be used to differentiate between activities that are performed as duty and activities that are performed as hobby, and to give an indication of the quality of life. Women for example, are most often in charge of taking care of their children. A woman may experience positive feelings while spending time with her children when the availability of child care services prevent the time invested to become a burden. However, when care services are not available and the woman is the only care provider, negative emotions and lower quality of life may be associated with some of the activities related to the care of children.

      Intrahousehold inequality

      Data on the amount of time spent by all household members on household chores can be used as an indicator of household and individual living standards and help redefine poverty in terms of lack of time resources. At household level, for example, “household time overhead” is defined as the minimum number of hours that a household must spend on the basic chores vital to the survival of the family - preparation of meals, washing clothes, cleaning of the house, as well as time spent fetching water and firewood for cooking. A household with low household time overhead is better off than a household with a high time overhead. How the burden of work is distributed among female and male members of the household is an important contribution of time use data to the understanding of intrahousehold inequality. The household maintenance tasks are not distributed evenly among household members and have a different impact on women and men. As a result, women are more often than men “time poor”. Furthermore, data on time use can show how the gender allocation of time within the household is changed when access to public services, infrastructure, or domestic appliances, is provided. They can also show whether the household time overhead is covered by girls or boys when adults, especially women, spend more time on market activities, and whether there are gender differences in the impact on time devoted to schooling and learning activities.

  • + Avoiding gender-bias in data collection
    • Several aspects specific to time use surveys are important in avoiding gender bias in data collection: classification of activities covered; recording of contextual information; recording of simultaneous activities; coverage of relevant individual and household characteristics; and sample coverage.

  • + Classification of activities
    • Time use classifications should be detailed enough to identify separately activities mainly undertaken by women or by men. It is important that activities with great gender differences in time use are collected as detailed as possible and later, at the stage of coding, analysis or presentation of data, they are not collapsed into larger categories where the gender differences disappear. Also, when using light diaries or stylized analogues of time diaries, the pre-defined list of activities of interest should capture the specificity of the type of activities carried out by women and men, and the different amount of time allocated. It is important that data is collected as detailed as possible. For example instead of one category of care of children/ adults/elderly, more categories should be defined, such as: care of children; care of ill adults; care of elderly; care of disabled. Fetching water and fetching firewood should also be included as separate activities among other types of non-market work.

      Time use classifications should allow the distinction between market work, non-market work, domestic activities and volunteer work and enable the provision of data that can be linked to official statistics emanating from the SNA and labour statistics frameworks. This is especially critical where time-use data are used to measure unpaid work in satellite accounts that extend measurement of gross domestic product (GDP) to include non-SNA production. Furthermore, the distinctions between different types of work are particularly important in understanding the specific contribution of women and men to the economy and society.

      For example, the United Nations International Classification of Activities for Time-Use Statistics (ICATUS) use SNA as a basic framework and distinguish between productive activities within SNA, productive activities outside SNA, and personal activities. Also useful for understanding gender differences are the categories of unpaid non-SNA activities included in the classification. For instance, three of the major groupings of the classification are: “unpaid domestic services for own final use within households”; “unpaid caregiving services to household members”, and “community services and help to other households”.

  • + Recording of contextual information
    • The separation between different types of work and between work and leisure is possible only when additional contextual information is collected in the time use surveys. The context within which activities take place include the location of an activity, the other people present, the person or institution for whom the activity was done, the purpose of activity and any remuneration that may have been received for the activity. Contextual information is crucial for coding and classification of activities reported in the time use surveys. For example, information on the persons or institutions for whom a particular activity was being carried out, and whether payment was involved, would be needed to identify volunteer work, unpaid work within the household, and unpaid work outside of the household.

      Other contextual information can be useful from a gender perspective. For instance, subjective information on the experienced well-being while performing an activity may be used in constructing measures of quality of life for women and men. Also, information on ownership of assets and durable goods such as domestic appliances and information on types of fuels used in the household and types of water sources can be used for valuing unpaid work and construction of satellite accounts.

  • + Recording of simultaneous activities
    • Time use for specific types of activities, often related to unpaid work and often performed by women, can be adequately identified only when simultaneous activities are recorded. An activity may be carried out in parallel with one or more other activities over an interval of time. For example, a woman may take care of her children while cooking or while doing the laundry. When estimates of time use are based only on primary activities, many activities such as caring for children, older persons, ill or disabled persons, for example, are clearly underestimated. These “missing” activities would typically be reported as secondary or simultaneous activities.

      A large proportion of secondary activities tend to be underreported. For example, respondents may perceive domestic or personal care activities as not important. Probing questions can bring out unreported simultaneous activities. When multiple activities are recorded in a questionnaire for the secondary activity and only one activity can be recorded in the database, priority should be given to activities such as unpaid domestic work, childcare, elderly care and care of the sick and disabled.

      The ability to collect data on simultaneous activities depends on the methods of data collection used. For example, it is difficult to record simultaneous activities through a telephone interview. Underreporting of secondary activities may be more likely to appear when using activity lists and stylized questions that constrain people to sum up their activities into a total of 24 hours are used.

  • + Coverage of relevant individual and household characteristics
    • Gender differences in time allocation for specific activities tend to vary in different groups of population and at different life stages. Individual characteristics commonly considered to be recorded in time use surveys refer to sex, age, marital status, presence of children, education, and labour force status. This information will allow time use data to be disaggregated at the level of particular groups of women and men. When time use data is collected only for one person in the household, and the questionnaire needs to be kept at minimum, it is important that the demographic, social and economic characteristics of the partner of the respondent are recorded. However, when data on time use is collected for all relevant household members and more extensive background characteristics can be recorded, individual characteristics should be captured for all household members. In addition, information on housing characteristics or other measures of wealth of the household should be collected. Such information will enable identification of patterns of intrahousehold allocation of time resources by various types of living arrangements and wealth group of households.

  • + Sample coverage
    • Samples used in time use surveys should cover all relevant groups of population and all seasons. In particular, children and older persons should not be excluded by the survey sample. It is also important that the sample of days included in the survey covers all seasons relevant for agricultural or other weather-dependent activities.

      Data on time use for multiple persons from the same household are the basis for understanding intra-household allocation of time and resources. A full accounting of time use during the previous 24 hours for all eligible household members is necessary to study how housework and childcare are allocated among household members, and how a change in one person’s labour activities affects the use of time by other household member.

  • + References
    • Bittman, Michael, 2000. Issues in the Design of Time-use Surveys for Collecting Data on Paid and Unpaid Work. Paper presented at the United Nations Expert Group Meeting on Methods for Conducting Time-Use Surveys 23-27 October 2000. New York: United Nations Statistics Division.

      Eurostat, 2009. Harmonised European Time Use Surveys. 2008 Guidelines. Luxembourg: Eurostat.

      Harvey, Andrew S. and Maria Elena Taylor, 2000. “Time use”, in Designing Household Survey Questionnaires for Developing Countries. Lessons from 15 years of the Living Standards Measurement Study. Edited by Margaret Grossh and Paul Glewwe. World Bank, Washington DC.

      Hoffmann, Eivind and Adriana Mata, 2000. Statistics on Working Time Arrangements: Issues and the role of time use surveys. Paper presented at the United Nations Expert Group Meeting on Methods for Conducting Time-Use Surveys 23-27 October 2000. New York: United Nations Statistics Division.

      Grosh, Margaret, and Paul Glewwe (ed), 2000. Designing Household Survey Questionnaires for Developing Countries. Lessons from 15 years of the Living Standards Measurement Study. World Bank, Washington DC.

      United Nations, 2005. Guide to Producing Statistics on Time Use: Measuring Paid and Unpaid Work. DESA, Statistics Division, New York.

      United Nations Economic Commission for Europe and World Bank Institute, 2010. Developing Gender Statistics: A Practical Tool. Geneva.

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