1

Analysis and Presentation of Gender Statistics

3 October 2007

Republic of Moldova

UNECE Statistical Division

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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…..

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

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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)

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

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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

74.369.6

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.

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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

0

5

10

15

20

25

30

35

Male Female

Age

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

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.

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• 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.

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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.

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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

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

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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

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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