Transcript Analysis and Presentation of Gender Statistics

Analysis and Presentation of
Gender Statistics
Tashkent, 11-15 July 2005
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Analysis of Gender Statistics
• Why do Gender Analysis?
– Improve design of policies, projects and programs
– Measure impact of interventions
– Understand differences between genders
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For Example…
• In many countries, men have higher labour force
participation rates than women
• Sex-disaggregated data shows us this, but we
don’t know why
• So, we need more information…..
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Percent of Economically Active People Aged 20-29 by Sex
Men
Women
70%
60%
50%
40%
30%
20%
10%
0%
Czech Republic
Finland
Source: United Nations Economic Commission for Europe, 2000.
United States
Percent Economically Active People Aged 20-29 by
Sex and the Presence of a Pre-school Child: 1998
No pre-school children
At least one pre-school child
100
80
60
40
20
0
Men
Women
Czech Republic
Men
Women
Finland
Source: United Nations Economic Commission for Europe, 2000.
Men
Women
United States
Presenting Data
• Presentation is crucial
• Should attract readers
• Encourage further analysis
• A range of formats
– Tables
– Graphs
– Diagrams
– Maps
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Tips for Good Presentation
• Clear visual message
• Appropriate heading
• Convey one finding or a single concept
• Simple
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A Good Graph
• Accurately shows facts
• Grabs the readers attention
• Shows trends or changes
• Is clear and easy to read
• Has a title and minimal labels
• Uses colours or patterns to show differences
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How many statisticians present data
Table 6-2. Population Aged 65 and Over, by Marital Status, Age, Sex, Race, and Hispanic Origin: 2003
(In percent)
Age, race, and Hispanic origin
Married, spouse present
Men
Women
Widowed
Men
Women
65 and over………………………………….
Non-Hispanic White alone……………….
Black alone………………………………….
Asian alone……………………………….
Hispanic (of any race)……………………………..
71.2
72.9
56.6
68.6
68.8
41.1
42.9
25.4
42.7
39.9
14.3
14.0
19.3
13.6
12.3
44.3
44.0
50.8
39.7
39.5
65 to 74……………………………………...
Non-Hispanic White alone……………….
Black alone………………………………….
Asian alone……………………………….
Hispanic (of any race)……………………………..
74.3
76.4
59.2
70.2
72.5
53.5
56.5
33.4
51.8
48.4
8.8
8.3
14.3
9.6
7.6
29.4
28.8
36.2
27.1
25.9
75 to 84………...……………………………..
Non-Hispanic White alone……………….
Black alone………………………………….
Asian alone……………………………….
Hispanic (of any race)……………………………..
69.8
71.3
54.9
69.7
65.7
33.7
35.3
19.3
35.1
31.4
18.4
18.1
23.2
16.6
17.1
53.3
52.3
62.7
53.7
53.5
85 and over…………………………………
Non-Hispanic White alone……………….
Black alone………………………………….
Asian alone……………………………….
Hispanic (of any race)……………………………..
56.1
57.8
39.7
39.2
49.8
12.5
13.1
4.2
10.7
17.4
34.6
33.6
47.7
48.8
33.2
78.3
77.8
87.2
75.5
74.2
Reference population: These data refer to the civilian noninstitutionalized population.
Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement, 2003.
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Make it Easy to Understand
• Graphic presentation of data makes it easier to
understand
• Easier to see the differences between men and
women
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Percentage Married at Older Ages by Sex in the US: 2003
74.3
69.6
Men
Women
56.1
53.5
33.7
12.5
65 to 74
75 to 84
85 and over
Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement, 2003.
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• How we present sex-disaggregated data
influences the analyses we make
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Mean Age at First Marriage in Selected
Countries: Circa 1995
Age
35
Male
Female
30
25
20
15
10
5
Source: United Nations, 1995.
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Difference in Mean Age at First Marriage
Between Men and Women in Selected Countries:
Circa 1995
9.6
Difference in years
5.1
4.2
3.7
3.9
3.5
3.4
3.0
2.7
2.4
1.9
Source: United Nations, 1995.
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1.3
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• Both graphs give important, yet different,
information
Difference in Mean Age at First Marriage
Between Men and Women in Selected Countries:
Circa 1995
Mean Age at First Marriage in Selected
Countries: Circa 1995
Male
Age
Female
35
9.6
Difference in years
30
25
20
5.1
15
4.2
3.7
10
3.9
3.5
3.4
3.0
2.7
2.4
1.9
1.3
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Source: United Nations, 1995.
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Source: United Nations, 1995.
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Life Expectancy at Birth for Select Countries: 2003
78.9
Singapore
84.2
77.6
Japan
84.4
76.5
Italy
82.5
75.6
France
83.1
74.4
United States
80.1
72.9
Chile
79.6
71.9
Mexico
77.6
70.1
China
73.3
67.9
Egypt
73.0
62.9
64.4
India
62.5
Belarus
74.6
59.6
Russia
73.0
41.0
Swaziland
37.9
40.1
37.9
Zimbabwe
Botswana
32.2
32.3
Male
Female
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Source: U.S. Census Bureau, International Programs Center, International Data Base.
Female Advantage in Life Expectancy at Birth in Select
Countries: 2003
Singapore
5.3
Japan
6.8
Italy
6.1
France
7.5
United States
5.7
Chile
6.7
Mexico
5.6
China
3.2
Egypt
5.1
India
1.5
Belarus
12.1
Russia
Swaziland
Zimbabwe
Botswana
13.4
-3.2
-2.2
0.1
Source: U.S. Census Bureau, International Programs Center, International Data Base.
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From ‘raw data’ to easily
understood gender statistics
• Tables and graphs from ‘raw data’
• Gender concern here is Poverty
• Underlying cause is the lack of means of
economic support
• Closer analysis requires reasons for not being
economically active
• Sources: labour force surveys or population
censuses
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Population ages 10 and over by economic activity
status and reasons for not economically active in
Tanzania Mainland 1990/91
Number
Women
Men
Total
Economically Active
5,674,626
5,620,301
11,294,927
Not economically active
2,327,291
1,978,022
4,305,313
366,997
142,350
509,347
Student
1,399,348
1,512,705
2,912,053
Too old
211,826
90,376
302,202
Sick
238,224
139,630
377,854
Disabled
37,317
41,309
78,626
Others
73,579
51,660
125,239
8,001,917
7,598,323
15,600,240
of which
Total
Housework
Source: The Labour Force Survey, 1990/91. Tanzania.
Basic Table 1
Population ages 10 and over by economic activity
status
Numbers in 1,000's, percentage distribution and sex distribution (%)
Status
Women
Men
Sex distribution
Number Percent
Number Percent
Women Men
Economically Active
5,675
71
5,620
74
50
50
Not economically active
2,327
29
1,978
26
54
46
Total
8,002
100
7,598
100
51
49
Source: The Labour Force Survey, 1990/91. Tanzania.
•
Focuses only on economic activity rate
•
Exact numbers rounded to 1,000’s and percentages to integers
Population ages 10 and over by economic activity
status
Numbers in 1,000's, percentage distribution and sex distribution (%)
Status
Percentage Distribution
Sex distribution
Women
Men
Women
Men
Economically Active
71
74
50
50
Not economically active
29
26
54
46
100
100
51
49
8,002
7,598
Total, per cent
numbers in 1,000's
Source: The Labour Force Survey, 1990/91. Tanzania.
•
Further simplified
•
Deleted two columns of numbers and included total in 1,000’s
Basic Table 2
Not economically active ages 10 and over by
reasons
Reason
Women
Men
Number Percent
Housework
Sex distribution
Number Percent
Women
Men
367
16
142
7
72
28
Student
1,399
60
1,513
76
48
52
Too old
212
9
90
5
70
30
Sick
238
10
140
7
63
37
Disabled
37
2
41
2
48
52
Others
74
3
52
3
59
41
2,327
100
1,978
100
54
46
Total
Source: The Labour Force Survey, 1990/91. Tanzania.
•
Focuses only on reasons for being not economically active
•
Exact numbers rounded to 1,000’s and percentages to integers
Not economically active ages 10 and over by
reasons
Reason
Percentage distribution
Women
Men
Housework
16
Student
Too old
Sex distribution
Women
Men
7
72
28
60
76
48
52
9
5
70
30
10
7
63
37
Disabled
2
2
48
52
Others
3
3
59
41
100
100
54
46
2,327
1,978
Sick
Total, per cent
numbers in 1,000's
Source: The Labour Force Survey, 1990/91. Tanzania.
•
Further simplified
•
Deleted two columns of numbers and included total in 1,000’s
Not econom ically active ages 10 and over by reasons
Disabled
Others
Too old
Sick
Housew ork
Student
0
20
40
60
80
Per cent
Men
Women
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Acknowledgements
• Victoria Velkoff, US Census Bureau
• Statistics Sweden
Engendering Statistics: A Tool for Change
• Statistics New Zealand
http://www.stats.govt.nz/NR/rdonlyres/A1892BF2-6E4A-4D08-9667-BC5EE45B99F4/0/GraphicsGuidelines.pdf
• Office of National Statistics UK
• Statistics Denmark
• Russian Federal State Statistics Office
• UNECE Gender Statistics Database
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