Use of census data for gender statistics and analysis

1
Use of census data for gender statistics and
analysis

• Margaret Mbogoni
• Demographic and Social Statistics Branch
• Statistics Division, DESA
• United Nations, New York

2
Outline

• Outline of the Methodological Guidelines for the
  Gender Analysis of National Population and
  Housing Census Data
• Strengths and weaknesses of census data for
  gender analysis
• Examples of questions for gender analysis that
  have been asked in national censuses
• Select topics for gender analysis based on census
  data
• Relative numbers of females/males by age
• Households and families
• Marital status
• Education and literacy
• Fertility
• Special population groups

3

• Methodological Guidelines for the Gender Analysis
  of National Population and Housing Census Data

4
Contents Part 1

• Introduction
• PART ONE - Background and Conceptual
  Clarifications for Gender Analysis of Census Data
• Gender in Population and Housing Censuses
• Conceptual Clarifications on Gender Equality and
  Gender-Responsive Data Analysis

5
Contents Part 2

• PART TWO 10 Key Gender Issues Analysed with
  Census Data
• Fertility
• Mortality
• Sex Ratio at Birth and During the Life Course
• Marital Status, Polygamy, Widowhood, Child
  Marriage
• Households and Families
• Income, Poverty and Living Conditions
• Education and Literacy
• Work, Economic Activities and Social Protection
• Migration
• Disability

6
Conclusions and Appendices

• Conclusions
• References
• APPENDICES
• Gender-Relevant Issues in 2005-2014 Census Forms
• Glossary of Important Gender Terms
• Mapping of Resources on Gender Statistics
• Brief Overview of the Evolution of Gender
  Statistics
• From Understanding the Gender Data Gap to
  Improving the Production and Analysis of Gender
  Statistics

7
Structure of each chapter

• What is it?
• Why is it important?
• Data issues
• Tabulations
• Indicators
• Multivariate and further gender analyses
• Interpretation, policy and advocacy

8
Tables, indicators and analysis

• The basic premise of the manual is that the
  census offers many opportunities for in-depth
  studies, but that this requires going beyond the
  standard tabulations and constructing more
  complex indicators and analyses
• Some of these techniques go beyond what NSOs
  normally consider to be their mandate, namely the
  preparation of standard general-purpose tables
  and simple indicators. In order to implement some
  of the proposals contained in the manual (e.g.
  multivariate analyses), it may be necessary to
  build strong research ties with academic and
  research institutions outside the NSOs

9
Tables, indicators and analysis

• To make the best possible use of the advantages
  offered by census data
• DISAGGREGATE, DISAGGREGATE, DISAGGREGATE
• Or at least, STANDARDIZE
• But have a plan for why you are disaggregating
• Control as many intervening factors as you can,
  if necessary by using multivariate techniques

10
Strengths of census data for gender analysis

• Censuses provide universal information on the
  demographic and social characteristics and living
  arrangements of every individual within the scope
  of the enumeration up to the lowest geographical
  level
• Sex-disaggregated characteristics of the entire
  population can be presented in detail down to the
  lowest geographic level
• Locality-specific differentials can be derived
• Good for identifying vulnerable groups for
  targeted interventions
• Censuses provide insights into the private and
  community spheres and (indirectly) into time-use
  of women and girls, men and boys

11
Strengths of census data for gender analysis

• Census data for advocacy A local-level early
  warning system on gender inequalities
• Censuses provide essential background information
  allowing for further research on women and men,
  girls and boys
• Identify data gaps on gender issues
• Sampling frame

12
Weaknesses of census data for gender analysis

• Census data may not have been produced in a
  gender-responsive way
• Census data are of very limited scope and depth
  (basic characteristics)
• Gender-related discrimination is not explicitly
  measured by censuses (e.g. why lower schooling
  rates for females than for males)
• The level of analysis for census data is sex, not
  gender
• The census data may be outdated or of low quality
  (e.g. due to underreporting on women)
• Data access and the capacity to analyze census
  data in the appropriate ways may be problematic

13
Some interesting questions in censuses

• Time spent caring for children own or of other
  people (Australia)
• Looking after, or give any help or support to
  family members, friends, neighbours or others
  because of either (i)long-term physical or
  mental ill-health/disability, or (ii) problems
  related to old age (UK)
• Time spent for sick or disabled household members
  (Aruba, Australia, Iran, Ireland)
• Unpaid domestic work carried out in the household
  (Australia)
• Matrix of family relationships between household
  members (Ireland)
• Children ever born, not only for women, but also
  for men (Bermuda, Croatia, Hungary)
• Reasons to migrate (Cambodia, Nepal, Iran)
• Previous marriages (Ireland, Nepal, Mauritius,
  Maldives)

14
Some interesting questions in censuses

• Income data detailed by household members or by
  source (several)
• Trans-gender identity (India, Thailand)
• Question about homosexual unions (Germany,
  Brazil, Croatia, UK)
• Any kind of activity which generated income
  (several)
• Fertility preferences (Kazakhstan, Korea)
• Ownership of land and/or property (Nepal)
• Assistance received in the delivery (Cambodia)
• Sex of person sending remittances (El Salvador)

15
Some interesting questions in censuses

• 19 countries ask for the date or the age of the
  woman at the time of her first marriage
• 11 countries ask for the date (year) or the age
  of the mother at the time of birth of the first
  live-born child
• 24 countries allow the identification of domestic
  servants in the household
• Some countries ask men about polygamous unions
• Several censuses address causes of disability
  (Zambia 2010 has spousal violence)
• 30 countries are asking the questions allowing
  the estimation of maternal mortality from the
  census

16
Gender analysis based on census data

• Are there any gender issues (problems, questions
  related to women/girls and men/boys in society)
  regarding
• Their relative numbers?
• Age/sex distribution
• Where they live?
• Spatial distribution (urban/rural)
• Migration
• Housing conditions
• Whom they live with?
• Households and families
• Marital status

17
Gender analysis based on census data

• Are there any gender issues (problems, questions
  related to women/girls and men/boys in society)
  regarding
• Their socio-economic and demographic
  characteristics?
• Education and literacy
• Fertility
• Mortality
• Labour force participation
• Vulnerabilities
• Special population groups (children, youth,
  elderly, persons with disabilities)

18
Population size by age and sex

• Numbers of males and females at different ages
  depends on their numbers at birth, migration
  patterns and mortality conditions throughout the
  life cycle
• Relative proportions of males to females by age
  group follow an expected pattern with extreme
  departures (imbalances) requiring investigation
  of underlying demographic processes (births,
  deaths, and migration)

19
Male and female population size by age

• Policy relevance
• Statistics and indicators on age/sex composition
  are important to assess the needs of the
  different age groups (care for pre-school aged
  children, education for the young, employment for
  adolescents and working age adults, care for the
  elderly, etc.)
• In terms of distribution by age and sex
• Is there a balanced ratio of females to males or
  is there significantly more of one sex?
• At what ages are deficits of females or males
  substantial and what are the likely causes as
  well as consequences?

20
Male and female population size by age (total,
rural/urban)

• Tabulation
• Population by single years of age(age groups)and
  sex
• Indicators
• Proportional age distribution by sex
• Proportion by sex for each age group
• Sex ratios
• Data issues
• Errors in age reporting
• Selective under-reporting
• Distinguishing errors from other issues

21
Relative sizes (males/females)
Proportion of population by age and sex, total,
Malawi (2008)
22
Relative sizes (males/females)
Proportion of population by age and sex, urban,
Malawi (2008)
23
Relative sizes (males/females)
Proportion of population by age and sex, rural,
Malawi (2008)
24
Relative sizes (males/females)
Proportion of population by sex, by age, total,
Malawi (2008)
25
Relative sizes (males/females)
26
Relative size (males/females)
27
Sex ratios at birth, selected age groups
Regions At birth 0-4 years 5-14 years 15-24 years
Sub-Saharan Africa 104 103 102 101
Middle East and North Africa 105 105 105 105
South Asia 107 108 108 108
South Asia excl. India 105 105 105 104
East Asia and Pacific 113 114 114 109
East Asia and Pacific excl. China 105 105 105 104
Latin America and the Caribbean 105 104 104 103
CEE/CIS 106 106 105 103
Developing countries 107 107 108 106
World 107 107 107 106
28
Sex ratio by age, total, urban, rural Malawi
(2008)
29
Sex ratio by age, total Qatar (2010)
30
Households and families

• Policy relevance
• Statistics on household size, composition and
  headship are useful indicators for gender
  analysis with regard to living arrangements of
  families, likely number of wage earners and
  overall economic needs that have to be provided
  for within the household
• Families with children present a higher
  likelihood of vulnerability and poverty than
  families without children
• Families of lone mothers (e.g., teenagers) versus
  those of lone fathers in terms of poverty rates
• Care-giving roles of females in home and likely
  impact on their schooling and participation in
  formal employment
• Living arrangements of elderly persons

31
Households and families

• Policy relevance
• Important for identifying the prevalence of
  one-person households, single-parent and
  multi-generational families
• Statistics on household/family characteristics
  can be linked to data on housing characteristics
  (living conditions)

32
Households and families

• Tabulations (total, urban, rural)
• Population in households by age and sex and
  relationship to head or other reference member of
  household, and institutional population by age
  and sex
• Households by household size and age and sex of
  head of household or other reference
• Households by type of household, age and sex of
  head of household or other reference member
• Population in households by age and sex and
  marital status of head of household or other
  reference member
• Children under 15 years by age and sex and
  whether living with (i) both parents, (ii)
  mother only, (iii) father only, (iv) parents and
  grandparents, and (v) grandparents only

33
Households and families

• Indicators
• Percentage distribution of the population by age
  and sex and living arrangements (with family,
  alone, institutional, etc)
• Percentage distribution of households by sex and
  age of head or other reference member of
  household
• Percentage distribution of households by size
  (population by household size), by age and sex of
  head or other reference member of household
• Percentage distribution population by age, sex
  and marital status of head or other reference
  member of household
• Percentage distribution of households with
  children under 15 years of age by age, by
  presence of both parent, presence of mother only,
  presence of father only

34
Households and families

• Indicators
• Percentage distribution of households with
  children under 15 years by number of children,
  sex and marital status of head
• Percentage distribution of elderly persons by age
  and sex and living arrangements (couple, living
  alone, with children, grandchildren, other
  relatives, non-relatives)

35
Headship rates
36
Variety of household compositions Cambodia
2008

• Cambodia (2008)

  Without other adults Without other adults With other adults With other adults
  Male head Female head Male head Female head
Head without spouse or children 30,274 68,377 52,970 174,078
Couple without children 121,031 10,135 256,785 19,225
Couple with 1-2 children under 15 485,038 38,463 568,448 45,617
Couple with 3 children under 15 246,319 18,834 288,206 22,632
Lone parent with 1-2 children under 15 12,286 81,563 32,561 173,868
Lone parent with 3 children under 15 2,835 25,275 9,601 49,643
37
Living arrangements of older persons Australia
(2011)
  65-74 years 7584 years 85 years  and over Total 65 years and over
   Male  Male  Male  Male
Living with spouse or partner 73.8 67.6 46.1 69
Living with children or other relatives 3.6 4.4 7.3 4.2
Group household 2.3 1.7 1.2 2
Lone person 15.3 18.5 25.2 17.4
Total in private dwellings 98.3 95.1 82.3 95.7
In non-private dwelling 1.7 4.9 17.7 4.3
Grand total (no.) 740.9 417 132.2 1290.1
   Female  Female  Female  Female
Living with spouse or partner 59.6 37.4 11.5 44.4
Living with children or other relatives 9.5 13.4 14.8 11.6
Group household 1.9 1.2 0.7 1.5
Lone person 25 38.8 40.5 32.2
Total in private dwellings 98.6 92.9 69.3 91.9
In non-private dwelling 1.4 7.1 30.7 8.1
Grand total (no.) 775 514.5 250.9 1 540.4
38
Headship problems

• The definition of head of household is vague
  and in no way uniform across countries thereby
  putting into question how the results should be
  interpreted. At least five different concepts of
  head of household can be found in censuses
• Main breadwinner
• Householder
• Main authority
• Reference person
• Questionnaire respondent
• Gender inequality may take place at the
  intra-household level (e.g. unequal distribution
  of earnings and consumption among members of the
  household). Therefore, focusing on female-headed
  households may not capture these inequalities and
  be misleading.

39
Marital status

• Policy relevance
• Related to living arrangements, educational
  attainment, fertility
• Early marriage interferes with the educational
  and career development of women much more than
  for men, especially when early marriage is
  associated with early pregnancy and childbirth
• Marital status is related to property rights in
  some societies
• Women are more vulnerable to dependency and
  poverty with early marriage and in likelihood of
  marital dissolution, e.g., widowhood
• Polygamy has many potential negative impacts on
  women

40
Marital status

• Tabulations (total, urban, rural)
• Population aged 15 (??) years and older by
  marital status, age group and sex
• Population aged 15 (??) years and older by age at
  first marriage, age group and sex
• Total population 15 years and older, by
  disability status, marital status, age and sex
• Data problems
• Definition of marriage and implications for entry
  into a union
• Age mis-reporting

41
Marital status

• Indicators (total, urban, rural)
• Percentage distribution of population by age, sex
  and marital status
• Widowhood and divorce related to vulnerability
  particularly for women
• Sex distribution within marital status categories
  by age group
• Age at first marriage by sex
• Singulate mean age at marriage by sex
• Singulate mean age at marriage by sex and
  educational attainment
• Percentage of women aged 20-24 years old who were
  married or in a union before age 18
• Early marriage (relates to termination of
  education and lack of career development leading
  to economic dependency and poverty)
• Adolescent fertility
• Age difference between spouses

42
Marital status Population 15 years and older by
Population 15 years and older bymarital status
and sex Egypt (2006)
43
Tabulation of Census Data Australia (2011)
44
Educational characteristics

• Policy relevance
• School attendance provides information on access
  by gender especially for boys and girls
• Educational attainment levels of the population
  give an overview of the distribution of skills
  and the extent of preparedness for the labour
  force and is linked to age at marriage,
  fertility, socio-economic status, health and
  survival of women and children
• Literacy is crucial in contemporary society as it
  ensures access to knowledge and information

45
Educational characteristics

• Tabulations (total, urban, rural)
• Population 5 years of age and over by school
  attendance, educational attainment, age and sex
• Population 10 years of age and over by literacy,
  age and sex
• Population 5-29 years of age, by disability
  status, school attendance, age and sex
• Population 15 years of age and over by disability
  status, educational attainment, age and sex
• Data problems
• Literacy is self-declared with likelihood of
  reluctance of some persons to admit not being
  literate and difficulty of administering test to
  ascertain literacy

46
Educational characteristics

• Indicators (total, urban, rural)
• Percentage distribution of population 5 years of
  age and over by school attendance, educational
  attainment, age and sex
• Percentage distribution of population 10 years of
  age and over by literacy, age and sex
• Proportionate distribution of population 5 years
  of age and over by school attendance, educational
  attainment, age and sex
• Proportionate distribution of population 10 years
  of age and over by literacy, age and sex

47
School attendance by age and sex, Lesotho (2006)
    Total Total Total Males Males Females Females  
                   
Age Number Number Percent Number Number Percent Number Percent Percent
                   
Total 497,110 497,110 100.0 239,617 239,617 48.2 257,493 51.8 51.8
6-12 267,021 267,021 53.7 130,414 130,414 48.8 136,607 51.2 51.2
13-17 172,569 172,569 34.7 81,064 81,064 47.0 91,505 53.0 53.0
18-24 57,520 57,520 11.6 28,139 28,139 48.9 29,381 51.1 51.1
Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban
6-12 53,780 53,780 47.3 26,514 26,514 49.3 27,266 50.7 50.7
13-17 39,249 39,249 34.5 18,780 18,780 47.8 20,469 52.2 52.2
18-24 20,601 20,601 18.1 10,051 10,051 48.8 10,550 51.2 51.2
Rural Rural Rural Rural Rural Rural Rural Rural Rural Rural
6-12 213,241 213,241 55.5 103,900 103,900 48.7 109,341 51.3 51.3
13-17 133,320 133,320 34.7 62,284 62,284 46.7 71,036 53.3 53.3
18-24 37,934 37,934 9.9 18,619 18,619 49.1 19,315 50.9 50.9
48
Educational attainment by sex, Lesotho (2006)
49
Fertility Analysis

• Policy relevance
• Early and repeated child-bearing
• Poses risks for womens health and often keeps
  them from obtaining sufficient education or
  training to ensure a secure future for themselves
  and their children
• Interferes with employment
• When education is truncated, opportunities for
  employment are limited
• Women tend to withdraw from labour force to
  attend to family and take care of young children
  with likely consequences for career development

50
Fertility Analysis

• Tabulations (total, urban, rural)
• Female population 15 years of age and over, by
  age and number of children ever born alive by sex
• Female population 15 years of age and over, by
  age and educational attainment and number of
  children ever born alive by sex
• Female population 15-49 years of age, number of
  live births, by sex, within the 12 months
  preceding the census
• Data problems
• Recall errors
• Reporting by a proxy

51
Basic fertility indicators

• Indicators Total, urban, rural
• Age specific fertility rates
• Total fertility rate (by education)
• Parity progression ratios (by education)
• Adolescent birth rate (15-19)
• Age at birth of first child born alive (by
  education)
• Percentage of childless women (Age 40-44 or
  45-49)

52
Tabulation of Census Data Fertility Analysis

• The standard tables that NSOs prepare in their
  general-purpose census reports are geared towards
  the estimation of fertility levels and patterns
  (ASFRs/TFRs), for the general population or
  possibly some sub-groups
• In practice, this means
• Even though the majority of censuses (except 10)
  allow disaggregating births by sex, this is often
  not done
• In many cases only the total/average number of
  children by age category of the mother is
  tabulated, not a distribution by number of
  children ever born

53
Tabulation of Census Data Fertility Analysis
(contd.)

• Disaggregation by sex would allow the computation
  of Sex Ratios at Birth (SRBs) which is an
  important indicator in some countries.
  Alternatively, one may compute the sex ratio
  among children under age 1, but this already
  contains a mortality component.
• The distribution by numbers of children ever born
  would allow the analysis of childlessness by age
  category and preferably by marital status
  category. This is a major gender issue in many
  parts of the world.

54
Tabulation of Census Data

• Example 1.B. Childlessness
• Producing statistics on childlessness (preferably
  by marital status) serves two purposes
• To quantify this phenomenon, which in many
  countries represents a significant social stigma,
  more so for women than for men. In many developed
  countries, on the other hand, childlessness is
  clearly on the rise, e.g. 21.0 of women aged 40,
  in the 2010 census of Finland, as opposed to 9.9
  (Cambodia, 2008) and 7.0 (Ethiopia, 2007).
• To relate childlessness to certain negative
  social repercussions, such as divorce/separation.
  The problem, however, is that this relation can
  go both ways (Nepal, 2001 43.5 of divorced
  women were childless).

55
Special population groups

• Children (under 15 years) school attendance,
  relationship to head or reference member of
  household
• Infant and child mortality by sex
• Related to the girl child (school attendance,
  mortality, early marriage)
• Youth (15-24 years) school attendance,
  educational attainment, literacy, marital status,
  age at marriage, fertility, economic activity
  status
• Elderly (60 years and over) marital status,
  living arrangements
• Persons with disabilities place of residence,
  living arrangements, marital status, school
  attendance, educational attainment, economic
  activity status

56
Tabulation of Census Data

• Example 2 Disability and Marriage
• El Salvador (2007) - Percentage of ever married
  30-39 year olds by sex and type of disability
• Type of Disability Men Women
• Difficulty Walking or Moving 57.0 49.9
• Difficulty in Use of Hands or Arms 53.4
  48.0
• Sight Impairment, Even Using Glasses 68.8
  67.0
• Hearing Impairment, Even Using Hearing Aids
  39.3 42.5
• Speech Impairment 21.4 28.2
• Mental Retardation or Deficiency 6.9
  16.0
• Difficulty Bathing, Clothing, Eating 31.8
  38.7
• Other Type of Disability 51.9 51.7
• No Disability of Any Type 79.1 77.1

57
Conclusion

• Censuses have obvious limitations, especially
  with respect to the subjects that can be
  investigated
• No gender-based violence
• No female genital mutilation
• No male and female fertility preferences
• No distribution of resources within the household
• No time use information, etc. etc. etc.
• However
• A lot of census information is relevant to gender
  analysis, if properly analyzed
• Some censuses have special questions on
  gender-related topics
• Census data can be disaggregated to much more
  specific levels than is possible with surveys
• Census data may be merged with surveys on
  specific topics, e.g. poverty surveys

58

• Thank you
• ????