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Why time use data matters for gender equality—and why it’s hard to find

Eliana Rubiano-Matulevich's picture
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Photo: © Stephan Gladieu / World Bank

Time use data is increasingly relevant to development policy. This data shows how many minutes or hours individuals devote to activities such as paid work, unpaid work including household chores and childcare, leisure, and self-care activities. It is now recognized that individual wellbeing depends not just on income or consumption, but also on how time is spent. This data can therefore improve our understanding of how people make decisions about time, and expand our knowledge of wellbeing.

Time use data reveals how, partly due to gender norms and roles, men and women spend their time differently. There is an unequal distribution of paid and unpaid work time, with women generally bearing a disproportionately higher responsibility for unpaid work and spending proportionately less time in paid work than men.

How do women and men spend their time?

In a forthcoming paper with Mariana Viollaz (Universidad Nacional de La Plata, Argentina), we analyze gender differences in time use patterns in 19 countries (across 7 regions and at all levels of income). The analysis confirms the 2012 World Development Report findings of daily disparities in paid and unpaid work between women and men.

On average, both women and men spend by far most of their time (about 11 hours in both cases) on personal care activities such as sleeping and grooming. But looking beyond this, clear differences emerge.

Among women, unpaid domestic work—including childcare and household chores—is the second most significant activity (5.1 hours), followed by leisure (4.7 hours). Women dedicate the least amount of time to market work (2.3 hours). In contrast, for men, personal care activities are followed by leisure and market work (approximately 5 hours each). Men assign the least amount of time to unpaid domestic work (2 hours per day). While interesting, these results should be interpreted with caution, given data limitations that I will describe below.

Time use and gender equality in the development agenda

Reflecting the growing importance of time use data to development, its collection is integral to Sustainable Development Goal 5 target 5.4, which calls for recognizing, reducing and redistributing unpaid care work as a condition for achieving gender equality. The related SDG indicator (5.4.1)—compiled by the United Nations Statistics Division (UNSD) based on data produced by national statistics offices and recently added to our Gender Data Portal—measures the proportion of time spent on unpaid domestic and care work, disaggregated by sex.

Using data from the SDG indicator, the graph below shows that gender inequalities in unpaid care and domestic work are associated with lower rates of female labor force participation. With few exceptions in the Africa Region, women in countries with more responsibility for domestic and care tasks are less likely to be engaged in market work.

Collecting time use data in the context of stand-alone and nationally representative surveys is hard and costly. Developed countries have conducted time use surveys for a long time, but this practice is less common in developing countries. As a result, the data needed to monitor SDG 5.4 on unpaid care work remains limited.

There are 135 countries with no data on the proportion of time spent on unpaid domestic and care work between 2000 and 2015, rendering the bulk of unpaid domestic work in developing countries invisible.

The indicator itself is also problematic because it combines the time allocated to both household chores and to care work—activities that are quite different in nature. Unfortunately, given the methods and tools used to collect the data, combining them is probably the best way to monitor progress at the global level.

What are the limits and difficulties of time use data?

Another issue is the quality and cross-country comparability of time use data. Differences in data collection instruments, sampling designs, and activity classifications are common. The two main approaches are: (i) time diaries, where respondents record the activities they undertake over a period of time, and (ii) stylized questions that ask respondents the amount of time spent on specific activities. Wide variation in population coverage also poses a challenge. Some surveys are only representative at the urban level, as is the case of Panama, while others like West Bank and Gaza are even representative of refugee populations. Age groups also vary, with the minimum age of respondents ranging from 5 years of age (Tanzania) to 15 (China, Turkey), 18 (Argentina), or even 20 (Austria, Spain). Some countries use a maximum age of 64 (South Africa) or go up to 80 (Armenia). Furthermore, many surveys do not capture seasonal variations in time use and limit data collection to one or two months.

In addition to all of these challenges, time use data is yet to be used to properly measure certain kinds of tasks—particularly those that are critical to understanding disparities between women and men. For instance, usually time use data are coded to classify people engaged in one activity at a time. In a few developing countries, surveys capture the reporting of simultaneous activities, like cooking while listening the radio. However, in the majority of cases, ‘primary’ activities are extensively recorded but ‘secondary’ tasks tend to be omitted by respondents.

Time spent on childcare is especially vulnerable to omission since caregivers often combine it with other tasks, for example, watching television with their children. This causes a misrepresentation of the time constraints associated with parenthood, which varies extensively across households and countries. Therefore, where possible, both primary and secondary activities should be considered when measuring care work.

Experiences to move forward

Given the importance of time use data, how can we make it easier and cheaper to collect? Adapting traditional methods of data collection and using new technologies offers a promising start. The good news is that alternative approaches are emerging. For example, the Women’s Empowerment in Agriculture Index II has successfully piloted a ‘light’ time use module in a larger survey, including the option of reporting simultaneous activities. And a recent United Kingdom study created a web-based diary and a smartphone app to collect data on the time allocation of adolescents with great success. A United States marketing study provided respondents with a special smartphone to carry with them for 10 days to complete a self-administered survey. Respondents were prompted on an hourly basis to complete a short survey that included questions about their current activity, including duration, location, and mood.

This is the first of two blog posts on gender and time use. The next post will explain the approach that we followed to harmonize data across countries and will present the results of the time use paper referenced in this post.


Submitted by libbet on

It is great that some upcoming LSMSs are collecting data on how much time each household member is spending collecting drinking water for the household!!

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