Analysis and Presentation of Gender Statistics

3 October 2007 Republic of Moldova UNECE Statistical Division 1

Analysis of Gender Statistics

• Why do Gender Analysis?

– Improve design of policies, projects and programs – Measure impact of interventions – Understand differences between genders 2

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 30% 20% 10% 0% 70% 60% 50% 40% Czech Republic Finland United States 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 No pre-school children At least one pre-school child 100 80 60 40 20 0 Men Women Czech Republic Men Finland Source: United Nations Economic Commission for Europe, 2000.

Women Men Women United States

Presenting Data

• Presentation is crucial • Should attract readers • Encourage further analysis • A range of formats – Tables – Graphs – Diagrams – Maps 7

Tips for Good Presentation

• Clear visual message • Appropriate heading • Convey one finding or a single concept • Simple 8

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 9

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 65 and over………………………………….

71.2

Non-Hispanic White alone……………….

72.9

Black alone………………………………….

56.6

Asian alone……………………………….

68.6

Hispanic (of any race)…………………………….. 68.8

Women 41.1

42.9

25.4

42.7

39.9

65 to 74……………………………………...

74.3

Non-Hispanic White alone……………….

76.4

Black alone………………………………….

59.2

Asian alone……………………………….

70.2

Hispanic (of any race)…………………………….. 72.5

75 to 84………...……………………………..

69.8

Non-Hispanic White alone……………….

Black alone………………………………….

71.3

54.9

Asian alone……………………………….

69.7

Hispanic (of any race)…………………………….. 65.7

85 and over………………………………… 56.1

Non-Hispanic White alone……………….

57.8

Black alone………………………………….

39.7

Asian alone……………………………….

39.2

Hispanic (of any race)…………………………….. 49.8

53.5

56.5

33.4

51.8

48.4

33.7

35.3

19.3

35.1

31.4

12.5

13.1

4.2

10.7

17.4

Widowed

Men 14.3

14.0

19.3

13.6

12.3

8.8

8.3

14.3

9.6

7.6

18.4

18.1

23.2

16.6

17.1

34.6

33.6

47.7

48.8

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

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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 11

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 20 15 10 5 35 Age 30 25 Male Female 0 B ur ki na F as o C hi na Source: United Nations, 1995.

C on go G ua te m al a In do ne si a Ja pa n M ex ic o P ar ag ua y S au di A ra bi a S w azi la nd U ni te d S ta te s V ie tn am

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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 2.7

5.1

3.0

3.7

3.4

3.5

4.2

3.9

2.4

1.9

1.3

B ur ki na F as o C hi na C on go Source: United Nations, 1995.

G ua te m al a In do ne si a Ja pa n M ex ic o P ar ag ua y S au di A ra bi a S w azi la nd U ni te d S ta te s V ie tn am

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• Both graphs give important, yet different, information

Mean Age at First Marriage in Selected Countries: Circa 1995 35 Age 30 25 Male Female 20 15 10 5 0 B ur ki na F as o C hi na Source: United Nations, 1995.

C on go G ua te m al a In do ne si a Ja pa n M ex ic o P ar ag ua y S au di A ra bi a S w azi la nd U ni te d S ta te s V ie tn am Difference in Mean Age at First Marriage Between Men and Women in Selected Countries: Circa 1995 9.6

Difference in years 2.7

5.1

3.0

3.7

3.4

3.5

4.2

3.9

2.4

1.9

1.3

B ur ki na F as o C hi na C on go G ua Source: United Nations, 1995.

te m al a In do ne si a Ja pa n M ex ic o P ar ag ua y S au di A ra bi a S w azi la nd U ni te d S ta te s V ie tn am

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Life Expectancy at Birth for Select Countries: 2003 Singapore Japan Italy France United States Chile Mexico China Egypt India Belarus Russia Swaziland Zimbabwe Botswana 32.2

32.3

37.9

41.0

40.1

37.9

Source: U.S. Census Bureau, International Programs Center, International Data Base.

78.9

84.2

77.6

84.4

76.5

82.5

75.6

74.4

80.1

72.9

79.6

71.9

59.6

62.9

64.4

62.5

70.1

73.3

67.9

73.0

74.6

73.0

77.6

83.1

Male Female

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Female Advantage in Life Expectancy at Birth in Select Countries: 2003 5.3

Singapore Japan Italy 6.1

6.8

France United States Chile Mexico China Egypt India Belarus Russia Swaziland -3.2

1.5

3.2

5.1

Zimbabwe Botswana -2.2

0.1

Source: U.S. Census Bureau, International Programs Center, International Data Base.

5.7

5.6

6.7

7.5

12.1

13.4

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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 19

Population ages 10 and over by economic activity status and reasons for not economically active in Tanzania Mainland 1990/91

Economically Active Not economically active of which Total Housework Student Too old Sick Disabled Others Number Women 5,674,626 Men 5,620,301 Total 11,294,927 2,327,291 366,997 1,978,022 142,350 4,305,313 509,347 1,399,348 211,826 238,224 37,317 73,579 1,512,705 90,376 139,630 41,309 51,660 2,912,053 302,202 377,854 78,626 125,239 8,001,917 7,598,323 15,600,240 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 Not economically active 5,675 2,327 71 29 5,620 1,978 74 26 50 54 50 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 Economically Active Not economically active Total, per cent numbers in 1,000's Women 71 29 100 8,002 Men 74 26 100 7,598 Women 50 54 51 Men 50 46 49 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 Housework Student Too old Sick Disabled Others Total Women Number Percent 367 16 1,399 212 238 37 74 60 9 10 2 3 2,327 100 Men Number Percent 142 7 1,513 90 140 41 52 76 5 7 2 3 1,978 100 Sex distribution Women 72 48 70 63 48 59 54 Men 28 52 30 37 52 41 46 • • 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 Housework Student Too old Sick Disabled Others Total, per cent numbers in 1,000's Percentage distribution Women 16 60 9 10 2 3 Men 7 76 5 7 2 3 100 2,327 100 1,978 54 Sex distribution Women 72 48 70 63 48 59 Men 28 52 30 37 52 41 46 • • 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 Men Women 20 40

Per cent

60 80 25

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 26