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1
Analysis and Presentation of Gender Statistics
3 October 2007
Republic of Moldova
UNECE Statistical Division
2
Analysis of Gender Statistics
• Why do Gender Analysis?
– Improve design of policies, projects and programs
– Measure impact of interventions
– Understand differences between genders
4
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…..
0%
10%
20%
30%
40%
50%
60%
70%
Czech Republic Finland United States
Percent of Economically Active People Aged 20-29 by Sex
Men Women
Source: United Nations Economic Commission for Europe, 2000.
Percent Economically Active People Aged 20-29 by Sex and the Presence of a Pre-school Child: 1998
0
20
40
60
80
100
Men Women Men Women Men Women
No pre-school children At least one pre-school child
Source: United Nations Economic Commission for Europe, 2000.
Czech Republic Finland United States
7
Presenting Data
• Presentation is crucial
• Should attract readers
• Encourage further analysis
• A range of formats
– Tables
– Graphs
– Diagrams
– Maps
8
Tips for Good Presentation
• Clear visual message
• Appropriate heading
• Convey one finding or a single concept
• Simple
9
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
10
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)
Men Women Men Women
65 and over…………………………………. 71.2 41.1 14.3 44.3 Non-Hispanic White alone………………. 72.9 42.9 14.0 44.0 Black alone…………………………………. 56.6 25.4 19.3 50.8 Asian alone………………………………. 68.6 42.7 13.6 39.7 Hispanic (of any race)…………………………….. 68.8 39.9 12.3 39.5
65 to 74……………………………………... 74.3 53.5 8.8 29.4 Non-Hispanic White alone………………. 76.4 56.5 8.3 28.8 Black alone…………………………………. 59.2 33.4 14.3 36.2 Asian alone………………………………. 70.2 51.8 9.6 27.1 Hispanic (of any race)…………………………….. 72.5 48.4 7.6 25.9
75 to 84………...…………………………….. 69.8 33.7 18.4 53.3 Non-Hispanic White alone………………. 71.3 35.3 18.1 52.3 Black alone…………………………………. 54.9 19.3 23.2 62.7 Asian alone………………………………. 69.7 35.1 16.6 53.7 Hispanic (of any race)…………………………….. 65.7 31.4 17.1 53.5
85 and over………………………………… 56.1 12.5 34.6 78.3 Non-Hispanic White alone………………. 57.8 13.1 33.6 77.8 Black alone…………………………………. 39.7 4.2 47.7 87.2 Asian alone………………………………. 39.2 10.7 48.8 75.5 Hispanic (of any race)…………………………….. 49.8 17.4 33.2 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.
Married, spouse present WidowedAge, race, and Hispanic origin
11
Make it Easy to Understand
• Graphic presentation of data makes it easier to understand
• Easier to see the differences between men and women
12
Percentage Married at Older Ages by Sex in the US: 2003
74.369.6
56.153.5
33.7
12.5
65 to 74 75 to 84 85 and over
Men Women
Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement, 2003.
13
• How we present sex-disaggregated data influences the analyses we make
14
Mean Age at First Marriage in Selected Countries: Circa 1995
0
5
10
15
20
25
30
35
Male Female
Age
Source: United Nations, 1995.
15
Difference in Mean Age at First Marriage Between Men and Women in Selected Countries: Circa 1995
9.6
2.7
5.1
3.0
3.73.4 3.5
4.23.9
2.41.9
1.3
Burki
na Fas
o
China
Congo
Guatem
ala
Indone
sia
Japan
Mex
ico
Parag
uay
Saudi A
rabi
a
Swazila
nd
Unite
d Sta
tes
Vietn
am
Difference in years
Source: United Nations, 1995.
16
• Both graphs give important, yet different, information
Mean Age at First Marriage in Selected Countries: Circa 1995
0
5
10
15
20
25
30
35
Burki
na Fas
o
China
Congo
Guatem
ala
Indone
sia
Japan
Mex
ico
Parag
uay
Saudi A
rabi
a
Swazila
nd
Unite
d Sta
tes
Vietn
am
Male FemaleAge
Source: United Nations, 1995.
Difference in Mean Age at First Marriage Between Men and Women in Selected Countries: Circa 1995
9.6
2.7
5.1
3.0
3.73.4 3.5
4.23.9
2.41.9
1.3
Burki
na Fas
o
China
Congo
Guatem
ala
Indone
sia
Japan
Mex
ico
Parag
uay
Saudi A
rabi
a
Swazila
nd
Unite
d Sta
tes
Vietn
am
Difference in years
Source: United Nations, 1995.
17
32.3
37.9
37.9
73.0
74.6
64.4
73.0
73.3
77.6
79.6
80.1
83.1
82.5
84.4
84.2
32.2
40.1
41.0
59.6
62.5
62.9
67.9
70.1
71.9
72.9
74.4
75.6
76.5
77.6
78.9
Botswana
Zimbabwe
Swaziland
Russia
Belarus
India
Egypt
China
Mexico
Chile
United States
France
Italy
Japan
Singapore
Male
Female
Life Expectancy at Birth for Select Countries: 2003
Source: U.S. Census Bureau, International Programs Center, International Data Base.
180.1
-2.2
-3.2
13.4
12.1
1.5
5.1
3.2
5.6
6.7
5.7
7.5
6.1
6.8
5.3
Botswana
Zimbabwe
Swaziland
Russia
Belarus
India
Egypt
China
Mexico
Chile
United States
France
Italy
Japan
Singapore
Female Advantage in Life Expectancy at Birth in Select Countries: 2003
Source: U.S. Census Bureau, International Programs Center, International Data Base.
19
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
Population ages 10 and over by economic activity status and reasons for not economically active in Tanzania Mainland 1990/91
NumberWomen 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
of which Housework 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
Total 8,001,917 7,598,323 15,600,240
Source: The Labour Force Survey, 1990/91. Tanzania.
Basic Table 1Population 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
• Further simplified
• Deleted two columns of numbers and included total in 1,000’s
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
Total, per cent 100 100 51 49
numbers in 1,000's 8,002 7,598
Source: The Labour Force Survey, 1990/91. Tanzania.
Basic Table 2Not economically active ages 10 and over by reasons
• Focuses only on reasons for being not economically active
• Exact numbers rounded to 1,000’s and percentages to integers
Reason Women Men Sex distribution
Number Percent Number Percent Women Men
Housework 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
Total 2,327 100 1,978 100 54 46
Source: The Labour Force Survey, 1990/91. Tanzania.
Not economically active ages 10 and over by reasons
• Further simplified
• Deleted two columns of numbers and included total in 1,000’s
Reason Percentage distribution
Women Men Women Men
Housework 16 7 72 28
Student 60 76 48 52
Too old 9 5 70 30
Sick 10 7 63 37
Disabled 2 2 48 52
Others 3 3 59 41
Total, per cent 100 100 54 46
numbers in 1,000's 2,327 1,978
Source: The Labour Force Survey, 1990/91. Tanzania.
Sex distribution
25
Not economically active ages 10 and over by reasons
0 20 40 60 80
Student
Housew ork
Sick
Too old
Others
Disabled
Per centMen Women
26
Acknowledgements
• Victoria Velkoff, US Census Bureau
• Statistics SwedenEngendering Statistics: A Tool for Change
• Statistics New Zealandhttp://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