Haoyi Chen Social and Housing Statistics Section United Nations Statistics Division

1. Integrating a Gender Perspective into Work Statistics Haoyi Chen Social and Housing Statistics Section United Nations Statistics Division

2. How to make work statistics more gender relevant? • Ensure comprehensive coverage of gender issues • Producing data disaggregated by sex is not enough! • Identify gender issues in the world of work • Identify available data sources & gaps • Improve quality of work statistics from a gender perspective • Frameworks, concepts, definitions that recognize differences • Methods that reduce underreporting & misclassification • Facilitate understanding of gender differences • Highlight gender issues in presentation of data • Often requires detailed disaggregation to identify differences

3. A. Ensure comprehensive coverage • Scope & objectives of work statistics • Identify gender issues • Identify data needs to address gender issues • Assess existing sources of data

4. Work & Labour market statistics:Scope and objectives (19th ICLS, 2013) • Describe and monitor labour markets • Participation in employment, characteristics, working conditions • Extent of underutilization, labour market access and integration • Measure & participation in all forms of work (paid & unpaid) • Contribution to economy (national accounts / satellite accounts) • Contribution to household livelihoods and wellbeing • Assess differences in participation • Urban / rural , women / men, children / youth / adults, etc.

5. Identify gender issues Data needs Gender differences -Levels & patterns of work and labour market participation -Characteristics of the work -Working conditions -Contributions & returns from work Forms of work performed (paid & unpaid) Labour force status Barriers to labour force entry Occupation, industry, employment status Union membership Occupational injuries Earnings, working time, benefits, social security Education Family constraints Intra-household & gender roles Community expectations Access to physical & financial assets Discrimination on the job market And in the workplace Personal & context variables -Age, sex, education, marital status -Family constraints (presence of children by age groups, other dependent members, child care…) -Area context (urban /rural, regions) -Personal ownership of assets (land, livestock) -Employment experience, seniority

6. Identify gender issues: 4 dimensions

7. 1. Forms of work (paid & unpaid) • Do they engage in work for pay or profit? • Employment • Do they provide unpaid household services? • Own-use providers of services • Do they engage in subsistence agriculture, fishing? • Own-use producers of goods, subsistence foodstuff producers • Do they participate in unpaid community / village work? • Volunteer work

8. ILO Department of Statistics Illustration: Forms of work

9. 2. Labour market access • Do they have work for pay / profit ? • Employment • Do they look / are available for work for pay / profit? • Unemployment • Do they work for pay /profit or look for work? • Labour force • Do they enter and exit the labour market? • Labour turnover, life cycle patterns

10. Labour force participation rate, by sex Source: United Nations, 2010

11. 3. Characteristics & conditions of their work • Tasks & duties in their job - occupations • Kind of goods / services produced - industries • Employment relationship - status in employment • Security and stability – contract type, duration • Type of employer - institutional sector • Type of establishment –formal, informal, household • Type of place where they work - place of work • Hazardousness of their work – occupational injuries, illnesses • Voice and representation– union density, collective agreements • Benefits provided -social security coverage, maternity leave

12. Source: ILO Department of statistics Illustration: Occupations with highest concentration of women / men

13. 4. Contributions & returns for their work • Working time • Hours worked, working time arrangements • Income from employment • Wages, salaries, commissions, tips • Profits / losses • Overtime payments, other regular & irregular payments • Social security benefits • Contribution to households, community & economy • Value of production for own-final use • Value of paid and unpaid work to national production & satellite accounts

14. Illustration: time spent on paid and unpaid work Source: World’s Women 2010

15. Unpaid work in GDP

16. ILO Department of Statistics Official sources of work statistics Different sources exist, with different purposes • Population and housing census • Household surveys • Labour force surveys (LFS) • Household income & expenditure surveys (HIES) • Time-use surveys (TUS) • Establishment-based censuses & surveys • Administrative records

17. Improve quality of work statistics - Frameworks, concepts, definitions that recognize gender differences- Methods that reduce underreporting & misclassification

18. New work statistics framework(Resolution I, 19thICLS, 2013) • Address gender bias in recognition of ALL work (paid and unpaid) • Make visible participation patterns & quantify contributions • Inform policies targeting different forms of work, paid & unpaid • Working conditions, remuneration, social protection, work life balance, social inclusion & cohesion

19. Source: ILO Forms of Work (III): 5 distinguishedBy main intended destination & transaction type Goods Services S G S G G Services Goods S SNA labour input

20. Illustration: Participation of WAP in different forms of work (%) Source: ILO

21. Illustration: Own use providers of servicesby sex and activity cluster (%WAP) Most unpaid household services predominantly performed by women, except for household repairs Source: ILO calculations based on national data (LFS-CWIQ, 2010)

22. Classification by: Main reason for not being in labour market • Personal reasons • Own illness, disability • Studies, training • Family related reasons • Pregnancy, family or household responsibilities • Refusal by family • Labour market reasons • Past failure in finding a job, gave up looking for jobs • Lack of experience, qualifications or jobs matching skills • Lack of jobs in the area • Considered too young or too old by prospective employers • Lack of infrastructure • No roads, transport, employment services in the area • Other sources of income • Pensions, rents Social barriers Discouragement

23. Issues in measurement To reduce underreporting & misclassification

24. Reduce gender biases in data collection • Instrument design • Add probes (questions) and examples to better capture activities likely to be underreported (secondary, casual, part/-time self-employment jobs) • Use reference periods that take account of different gender roles • Field operations • Interviewer training (raise awareness of concepts, activities likely to go unreported, social expectations & roles, multiple activities of women) • Mixed teams of interviewers (men / women) • Avoid proxy responses, reduce interviewer interpretation by providing full questions to be read verbatim • Data processing, coding • Collect detailed information for industry and occupation • Reduce coding based on assumptions of typical gendered occupations

25. Suggested activities for gender units and gender focal points • Review questionnaires, manuals & training for surveys and censuses: • Work topics covered (main topics + causal factors) • Use of additional questions on “WHY – not working, not seeking work etc.) • Use of probing questions, activity lists / sketches • Examples given in the manuals (should be free of gender bias) • Degree of details used in classifications • Coverage of gender aspects in the training • Discuss data quality with survey/census team • Get involved in data quality assessments at the end of data collection • Careful assessment of data for adequate interpretation

26. Facilitate understanding of gender differences Highlight gender issues in presentation of data Detailed disaggregation to identify differences

27. Basic table for gender analysis

28. Group exercise • Using the handout provided, do the following: • Identify key gender issue(s) • Determine key message(s) to be highlighted • Propose a title / heading that highlights the gender issue shown • Draft a short paragraph explaining key message(s) • Discuss its relevance for labour market and social policies • Was the information provided sufficient? -If no, which additional information is needed?

29. 37%

30. Visit us at: http://unstats.un.org/unsd/gender/default.html