Integrating a Gender Perspective into Time
Use Statistics
Session 8
Rachid Bouhia
Bouhia@un.org
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
What are Time Use Statistics?
• Quantitative summaries of how
individuals “spend” or allocate
their time over a specified period
(typically over the 24 hours of a
day or over the 7 days of a week)
• They shed light on:
→ What individuals in the reference
population do or the activities
they engage in
→ How much time is spent doing
each of these activities
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
An “emerging” field?
 TUS since 1990:
• 185 Time use surveys were conducted worldwide
→ 92 (50%) in “developing countries”
→ 93 (50%) in “developed countries” (total of 35
countries/territories only)
• In total 85 distinct countries:
→ 28 “developed countries” (that is 80% of developed countries
which conducted a TUS)
→ 57 “developing countries” (that is around 36% of developing
countries which conducted a TUS)
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
An “emerging” field?
“Developed countries”
“Developing countries”
Number of countries with
pilot surveys only
3 (11%)
10 (18%)
Average number of surveys
conducted
3.3
1.6
7 years
9 years
13
16
0.0% ICATUS-based
59% HETUS-based
23% Others
18% Missing
26% ICATUS-based
40% HETUS-based
26% Others
9% Missing
Kaplan-Meier estimation of
the average duration between
2 surveys
% of “Light diaries”
% of classifications used in
last survey since 2000
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Current context: growing
interest
• So far in developed countries, main purpose = traditional
concern of labour-leisure tradeoff
However, revival of interest:
• “Stiglitz Commission” on the Measurement of Economic
Performance and Social progress : Recommendation 5
("Broaden income measures to non-market activities")
"This should start with information on how people spend their time that is
comparable both over the years and across countries. Comprehensive and periodic
accounts of household activity as satellites to the core national accounts should
complement the picture“
• Supplementing National Accounts through Satellite accounts
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Implications for Gender Statistics
• This need of improving the measurement of unpaid
activities and household production coincides with
the general aim of integrating gender perspectives
into official statistics
• Reveals activities and social phenomena which are
not well captured in traditional statistical system but
where inequalities between women and men are
numerous and complex (drastic change of women’s
contribution to GDP for example, distribution of
domestic tasks within the household…)
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Flash-back: underutilization of
Time Use Data


Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Outline
• My presentation will be divided into two main parts
1) How Time Use data can cover some areas relevant
for Gender Statistics that have been quite neglected
so far
2) Critical points specific to Time Use data collection
to be considered in order to limit “gender bias”
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Flash back II: Uncovered areas
Frequency of production of different types of gender statistics
100.0
ECA region
90.0
Sexual and reproductive health
Mortality
Unemployment
Poverty
Morbidity
80.0
Violence against w omen
Education
Access to health services
Access to sanitation
Agriculture
Child marriage
20.0
50.0
40.0
30.0
70.0
Access to clean w ater
60.0
All countries
70.0
Pow er and decision making
Informal Employment
Labour force
Adolescent fertility
80.0
90.0
100.0
60.0
Disability
Satellite accounts
Unpaid w ork
50.0
Entrepreneurship
ICT
Media
Many areas related to
the contribution of
women and men in
the economy
Workshop on Gender Statistics, 4-7 December 2012, Uganda
40.0
30.0
20.0
Social and Housing Statistics Section
unstats.un.org
Unpaid work
Limitations of conventional labour statistics:
• 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
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Unpaid work
Examples of unpaid work:
• Unpaid domestic services for own final use within
household: cleaning, cooking, do-it-yourslf
decoration
• Unpaid caregiving services to household members:
childcare, adultcare…
• Community services and help to other households:
volunteering, repairs of dwellings…
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Unpaid work
Why is it important for gender statistics?
• Measuring 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.
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Unpaid work: New Zealand
• Men and women spend about
the same amount of time
working: 49 hours a week.3
• However, females spent two
hours a day more than males
on unpaid work, while males
spent two hours a day more
than females on paid work.
• While approximately 60
percent of males’ work is paid,
almost 70 percent of females’
work is unpaid.
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Satellite Accounts
• Definition: the System of National Accounts recommends the
use of supplementary accounts for nonmarket activities
rather than the expansion of existing accounts.
→ Allow for experimentation with changes in scope and
measurement.
→ Consistent and could be used with the existing national
accounts without overburdening them
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Satellite Accounts
• Direct application of measuring unpaid work:
estimating household production in satellite
accounts that extend measurement of gross
domestic product (GDP) to include non-SNA
production
• Makes the national accounts more complete and
comparable across countries
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Satellite Accounts: major
challenge
• How to valuate household time: different approaches
i. Opportunity cost approach: Focus on the intrinsic
productivity of the individual. Time spent on doing unpaid
work valued as potential time non spent on the labour
market regardless of the activity
ii. Market price approach: Focus on the specificity of the
unpaid activity which is done. Valued as if it was done by a
professional. Within: different concepts and methods to
determine the exact hourly compensation
 TUS data should be in line with the concepts and the avaibility
of Labour statistics
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Satellite Accounts: Philippines
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Satellite Accounts: Philippines
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Outline
• My presentation will be divided into two main parts
1) How Time Use data can cover some areas relevant
for Gender Statistics that have been quite neglected
so far
2) Critical points specific to Time Use data collection
to be considered in order to limit “gender bias”
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Diary versus stylized questionnaire
Two main types of survey instrument to collect TUS
data
1) Stylized questionnaire
2) 24 hour diary
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Stylized questionnaires
• Specific questions where
the respondents need to
recall the amount of time
spent on the related
activities.
• May target specific
activities or be designed to
be as exhaustive as possible
so as to capture a complete
period of time (24 hours, a
week)
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Stylized questionnaires
Pros
Cons
• Less expensive
• Preferable for a specific and
short time period
• High degree of errors
↘ “Normative editing”: Under
or over reporting of socially
marked activities (ex:
childcare versus watching
television)
↘ Memory recall errors
↘ Not measuring
simultaneous activities:
gender bias
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
24 hour diary
• Writing verbatim
descriptions of activities
that are coded later on
to an activity
classification
• “Light” diary
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
24 hour diary
Pros
• Provide more reliable
and accurate data
• More flexible and more
powerful for data
dissemination
• Allows to record
simultaneous activities
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Cons
• More costly in terms of
data collection and data
coding
• Burden on the
respondents (pressure
on the participation
rates)
Social and Housing Statistics Section
unstats.un.org
Stylized questionnaires vs 24
hour diary: conclusions
• The statistical community recognizes that the 24 hour diary is
the best instrument to collect Time Use data and to avoid
biases in activity reporting including gender bias. Many
discrepancies affect the distribution of the activities within
the household and so between women and men, such as
domestic tasks or childcare.
• However, the country should be prepared to face the
financial and technical requirements to conduct a diarybased survey
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Simultaneous activities
•
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Contextual variables
• Definition: “contextual variables” describe the
context, the conditions within which an activity takes
place
• Examples: Location, for whom, use of a computer….
• There are 2 dimensions to consider in terms of
“gender awareness”
1) The nature of the “contextual variable”
2) Their position in the survey package
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
The nature of the contextual
variables
• The statistician should select the relevant contextual
variable required for the main purposes of the
survey. Especially, they should be in line with te
classification (see below)
• Example: For unpaid work, whether the activity is
“paid” , for whom
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
The position of the contextual
variables
There are 3 locations to collect contextual variables (diary-based
survey):
 The diary (for each activity)
 The household/individual questionnaire (characteristics of the
formal work)
 Within the classification (“I cook” vs “I cook for my kids”)
• The position is strategic because it will determine the scope
of the areas that could be covered
↘ Example: Unpaid work and Informal Employment
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
The Classification of Activities
• Reflects the most recurrent
activities at the country level
(through pilot or previous survey)
• Detailed enough to identify
separately activities mainly
undertaken by women or by men
• Example: ICATUS
↘ Particularly in line with the SNA
↘ Oriented to measure unpaid work
and set up satellite accounts
↘ Trial version since 2005 but
finalization in progress (Expert
Group Meeting in 2012)
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Major divisions of ICATUS 2012
(provisional)
1. SNA work and related activities
2. Unpaid domestic services for own
final use within household
3. Unpaid caregiving services to
household members
4. Community services and help to
other households
5. Learning
6. Socializing, community
participation and religious practice
7. Leisure and sports
8. Self-care and maintenance
Social and Housing Statistics Section
unstats.un.org
Conclusion
• TUS transversal topic: opportunity to gather statisticians from
diverse backgrounds
• Gender statisticians should intervene in two main phases of
the survey:
 Conception phase:
1) Inform the general public and the administration of the
benefits of conducting a TUS (especially because they are
costly and need the support of many stakeholders)
2) Participate in the Task force in charge of elaborating the
survey
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Conclusion
 Dissemination/Analysis: Role to advocate for more
analysis and provide your expertise (underexploitation because data very difficult to use, make
sure that satellite accounts are attempted)
 Further information disclosed the UN “Guide”
to producing Statistics on Time Use”
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org
Many thanks for your attention and
your questions
Workshop on Gender Statistics, 4-7 December 2012, Uganda
Social and Housing Statistics Section
unstats.un.org