Tabulation, Presentation and
Dissemination of Labour Statistics:
Highlighting gender issues
Workshop on Household Surveys and Measurement of
Labour Force with Focus on Informal Economy
Maseru, Lesotho, 14-18 April 2008
Overview
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Introduction
Aims of dissemination
Why highlight gender differences?
Common dissemination activities
Steps in data dissemination
Users and needs
Dissemination formats
When to highlight gender differences
How to include gender issues in dissemination
Steps to highlight gender issues
Collaboration in gender analysis
Concluding remarks
Introduction
Statistical production
Identify key issues or concerns
Determine the statistics needed
Assess quality
of existing data
and sources
Mainstreaming gender
Consider gender concerns,
policy goals and causes of
gender differences
Identify data gaps
Identify new sources
Consider social and cultural
factors that can produce
gender-biases in data collection
Specify methodological improvements
Collect/compile the statistics needed
Tabulate
Analyze
Disseminate
Highlight gender issues,
Shed light on underlying causes
Aims of data dissemination
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To serve user’s needs
To make available the information collected
To promote use and understanding of data
To establish dialogue with users
To improve data collection
Why highlight gender differences?
Most commonly
• In response to users’ needs
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Design policies, projects and programs, particularly
those aimed at promoting gender equality in
employment and decent work for all
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Monitor progress towards attainment of gender
equality in employment goals
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Measure impact of interventions
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Advocacy
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General interest
Why highlight gender differences?
Thinking more broadly
• To provide a more accurate and complete
description of the labour market and the
employment conditions of workers
• To add value to labour data
Common dissemination activities
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Regular dissemination plans as part of data production
programme
• Monthly, quarterly, annual bulletins
• Survey, census, administrative data reports
• Compendiums
• Database, micro-files
Special dissemination activities through inter-unit, interministerial or inter-agency collaborations
• Cross-sectoral publications addressing key issues for
specific populations: women and men, children,
elderly, disabled population
Publicity materials
• Flyers, booklets, posters, wall-charts
Steps in Dissemination
Regular
dissemination
plans
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Special
publications
Publicity
materials
Identification of target users and needs
Choice of dissemination format, scope and contents
Identification of data needs
Tabulation / Data mining
Basic data analysis
Publishing of dissemination materials
Presentation and marketing of results and products
Feedback from users
Target users and needs
Type
•Government
•Workers’ associations
•Media
•Researchers
•NGOs
•Donors
Ability to understand and use statistics
•Technical
•Non-technical
•Data needs
•Policy-making, planning
•Advocacy
•Research
•Reference
Target users and needs
Key users in need of statistics highlighting gender issues
Government:
• Ministry of Labour
• Ministry of Planning
• National Women’s Machinery or institution
responsible for women’s affairs, equal
opportunity or gender and development
Worker’s associations:
• Trades with where women predominate
NGOs:
• Women or gender equality focus
Researchers
Target dissemination formats
User type
User needs
Statistical knowledge
Dissemination formats
• Reports
• Compendiums
• Booklets
• Posters, Wall charts
• Briefs
• Micro-data files
• CD-ROM
• On-line database
Important
•Tailor product and message to audience
When/how to highlight gender differences?
In all data dissemination activities
When
How
Census, survey or
administrative data reports,
bulletins, compendiums
Basic tabulations by
appropriate cross-classifying
variables
Summary findings
Analytical publications, multi- Simple graphs and charts
sectoral publications, briefs, Explanatory text
poster, wall-charts
Tabulations as Appendix
Flyers, charts
Data files
Simple table, graphs and
charts
Explanatory text
Basic data series with
sufficient level of detail
Steps to highlight gender differences
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Identify/select key gender issues to highlight
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Identify data needs
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Choose appropriate measure or indicator
(counts, percent, rates, ratios)
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Determine and prepare raw/basic data
tabulation
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Determine and prepare appropriate data
presentation format (table, graph, chart, map)
1. Identify/select gender difference
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Participation in labour force (entry/exit)
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Conditions of work
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Sector, industry, occupation, status in employment,
size of establishment, place of work, occupational
injuries, diseases and fatalities, union membership,
representation
Contributions to work (labour inputs)
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Labour force, employment, unemployment,
discouraged job seekers, labour turnover
Hours worked, work schedules, absenteeism
Returns from labour
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Wages, overtime payments, fringe benefits, social
security benefits, regular and irregular payments
1. Identify/select gender difference
Key mechanisms to identify/select key issues for
your country and users:
• User-producer collaboration
• Collaboration with your gender statistics unit,
department, or working group in your
organization
• Collaboration with your national women’s
machinery
2. Identify data needs
• Key outcome variable (issue or area of focus)
– Appropriate level of detail at which gender
differences may manifest themselves
• Key explanatory variables
– Factors underlying gender-based inequalities and
differential patterns of behavior
– age, education, ethnicity
– Family context (marital status, household
composition, number and age of children in
household, presence of elders needing care)
2. Identify data needs
Gender patterns may vary according to other
characteristics of the individuals or the
communities where they live. These should
also be considered in identifying the data
needs and conducting the analysis
For example:
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Socio-economic grouping
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Geographical area
3. Choose appropriate measure or indicator
• Measures of relationship
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Ratios: relation between two quantities (a/b)
Proportions, percentages: quotient between one
part and the total (a/(a+b))
Index numbers: value in relation to standard value
• Measures of central tendency
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Mean, median, mode
• Measures of variability
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Frequency distributions, range, standard deviation,
quartiles
• Shape of distribution
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Skewness
3. Key labour measures and indicators
Participation in labour force (entry/exit)
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Activity, employment and unemployment rates
Conditions of work
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Share of women in category i
Percentage of all women in category i
Sex ratio (in category i)
[Fi/Ti*100]
[Fi/F*100]
[Fi/Mi*100]
Contributions to work (labour inputs)
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Distribution of workers by hours worked per week
Percentage women/men who work less/more than x hours per week
Distribution of workers by working time arrangements
Returns from labour
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Gender wage gap
[(Wm-Wf)/Wm*100]
Gender wage gap corrected
[1/N ∑Ni*(Wmi–Wfi)/Wmi]
Median wage, wage quartiles
Distribution of workers by categories of income earned
4. Determine and prepare basic tabulation
Title
Women
N
Men
%
N
Sex distribution
%
A
B
C
Total
Source…
100
100
%W
%M
5. Determine data presentation format
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Consider target audience
Should attract interest
Facilitate gender comparisons
Encourage further analysis
Clear message
Appropriate heading
Convey one finding
Simple
Data presentation formats
Common statistical tables
Table 6-2. Population Aged 65 and Over, by Marital Status, Age, Sex, Race, and Hispanic Origin: 2003
(In percent)
Married, spouse present
Widowed
Age, race, and Hispanic origin
Men
Women
Men
65 and over………………………………….
71.2
41.1
14.3
Non-Hispanic White alone……………….
72.9
42.9
14.0
Black alone………………………………….
56.6
25.4
19.3
Asian alone……………………………….
68.6
42.7
13.6
Hispanic (of any race)……………………………..
68.8
39.9
12.3
65 to 74……………………………………...
74.3
53.5
8.8
Non-Hispanic White alone……………….
76.4
56.5
8.3
Black alone………………………………….
59.2
33.4
14.3
Asian alone……………………………….
70.2
51.8
9.6
Hispanic (of any race)……………………………..
72.5
48.4
7.6
75 to 84………...……………………………..
69.8
33.7
18.4
Non-Hispanic White alone……………….
71.3
35.3
18.1
Black alone………………………………….
54.9
19.3
23.2
Asian alone……………………………….
69.7
35.1
16.6
Hispanic (of any race)……………………………..
65.7
31.4
17.1
85 and over…………………………………
56.1
12.5
34.6
Non-Hispanic White alone……………….
57.8
13.1
33.6
Black alone………………………………….
39.7
4.2
47.7
Asian alone……………………………….
39.2
10.7
48.8
Hispanic (of any race)……………………………..
49.8
17.4
33.2
Reference population: These data refer to the civilian noninstitutionalized population.
Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement, 2003.
Women
44.3
44.0
50.8
39.7
39.5
29.4
28.8
36.2
27.1
25.9
53.3
52.3
62.7
53.7
53.5
78.3
77.8
87.2
75.5
74.2
Data presentation formats
To highlight gender issues
• No need to present full cross-tabulation
• Present only the relevant categories to
highlight gender issue
• If the table is complex, it is better to prepare a
graph or chart to facilitate reading
• Leave full tabulation as an appendix
Key gender issues
Participation in labour force (entry/exit)
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Women and men tend to have different age patterns
of labour force participation
Women tend to have lower rates of labour force
participation than men at every age
Reasons for not being economically active tend to be
different for women and men
Women face different barriers to employment as
compared to men due to differences in education,
experience, and societal roles and expectations
Women have different approaches to seeking
employment as compared to men
Participation in labour force
Labour force participation rate
Mauritius, 2006
120
100
80
60
40
20
Men
Women
Sex ratio
75
+
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
0
Age
Economically Inactive by Status
Economically Inactive by Status
Ghana, 2000
Home maker
Student
Other
Old age
Disability
Retired
0
10
20
30
40
50
Per cent
Men
Women
Unemployment
Time-related underemployment by Reason
Key gender issues
Employment conditions
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Employment patterns of women are affected by their
caring role (presence of dependent children/family)
Women’s employment tends to be concentrated in the
services sector
Women tend to be concentrated in fewer occupations
than men, and are concentrated in service oriented
occupations
Women are a minority among administrative and
managerial workers
Within major occupational groups women tend to be
concentrated in the lower status occupations
Most unpaid workers tend to be women
Proportionately fewer women than men are employers
Employment
Employment rate by age of youngest dependent child
Employment rates of women and men,
Rate
United Kingdom, 2005
United
Kingdom 2005
100
100
80
80
79
60
71
60
40
40
20
20
0
Under 5
5–10
11–15
16–18
No dependent
children
Women
56
71
77
79
73
Men
91
90
89
73
0
Women
90
Men
Women
Men
Employment by Sector
Share of working women and men in agriculture, services and
industry, Botswana 2003
100%
16.5
28
80%
60%
43.3
70.6
40%
20%
28.6
12.9
0%
Women
Agriculture
Men
Services
Industry
Employment by Main Industry
Employment by Occupation
Employment by Status
Employment by Status
Distribution of women and men workers by employment
Distribution
of women
and men workers
status2004
in
status
and branch
of economic
activity,by
Turkey
employment, Turkey 2004
100%
100%
80%
80%
60%
60%
40%
20%
0%
40%
20%
0%
Women
Men
Women
Women
Men
Men
Agriculture, hunting, forestry,
Non-agricultural activities
Unpaid family workerfishing
Regular/casual employee Self-employed/employer
Unpaid family worker
Regular/casual employee
Self-employed/employer
Key gender issues
Labour inputs
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Women tend to be employed in part-time, seasonal,
casual employment to a larger extent than men
Hours of work of women are affected by their caring
role (presence of dependent children/family)
Activity status by hours worked
Employment by hours of work
Employment rate by hours of work and age of dependent
children
United Kingdom, 2005
100
80
60
Part-Time
40
Full-Time
20
Men
Women
All
No
Dependent
16-18
11-15
5-10
Under 5
All
No
Dependent
16-18
11-15
5-10
Under 5
0
Key gender issues
Returns from labour
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Women earn less than men
Pay differentials between women and men tend to be
wider in higher status occupations
Women tend to receive lower retirement/pension
benefits as compared to men
Wages
Wages by occupation
Wages by occupation
Key gender issues
Unpaid housework
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Unpaid housework is primarily performed by women
Promoting further gender analysis
Types of statistical analysis
Descriptive
•Organize data
•Summarize data
•Describe associations
Inferential
•Estimate population parameters
•Draw inferences
•Model patterns and relationships
•Need to establish and promote further research through
•Collaboration and partnerships with universities and
research centers
•Release and dissemination of micro-data
Collaboration in gender analysis
Collaboration with universities, research centers,
and NGOs in gender analysis is crucial to:
• To expand scope of analysis and use of data
• To promote better understanding of gender
issues in labour market
• To improve overall quality of data
Concluding remarks
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NSS can include basic gender analysis of labour data
to better describe the labour market and inform the
design of policies and programmes aimed at
promoting gender equality in employment
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Choosing the right presentation format is key for clear
and accurate interpretation of data
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Dissemination of results to various target audiences is
crucial to raise awareness of gender issues in the
labour market and promote interest in labour data
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Promote further analysis through collaboration with
researchers and through release of micro-data files