1. Gender and Informal Employment in Zimbabwe
Lindiwe Ngwenya, CSO Zimbabwe
Malte Luebker, International Labour Office (ILO)
Global Forum on Gender Statistics
26-28 January 2009 in Accra, Ghana

2. Outline of the presentation
Limits of traditional ‘headline’ labour market statistics
Employment in the informal sector and informal employment
Results from Zimbabwe’s 2004 Labour Force Survey
Changes to the 2009 Labour Force Survey
Gender sensitization, training and analysis of the LFS
Summary: Generating labour market statistics that are relevant for gender analysis

3. Limits of traditional ‘headline statistics’
Unemployment rate alone can be misleading:
Suggests improvement in LM situation sine early 1990s, but ignores e.g. changes in type of jobs and returns to work.
Suggests gender equality in LM, but conceals e.g. differences in access to formal employment, type of economic activity, returns to work, non-SNA work and working time.

4. Employment in the informal sector and informal employment
Informal sector (enterprise-based concept):
Defined by ICLS (1993) as private unincorporated enterprises, optional limitation to (a) non-agricultural activities and (b) below size threshold (e.g. less than 10 employees).
Informal employment (job-based concept):
ICLS (2003) definition builds on informal sector concept and status in employment (ICSE-1993).
x informal employment o formal employment

5. Informal employment in the 2004 LFS
Informal employment is dominant source of employment.
Concept is broader than informal sector.
Also captures informal employment in the formal sector and informal employment in households.

6. Differences in access to formal employment
Distribution of total employment suggests gender equality, but:
Almost three quarters of formal [sector] jobs are held by men.
Majority of informal [sector] jobs are held by women.
Concept is useful to reveal gender differences.

7. Differences in branch of economic activity and returns to work
2004 LFS shows informal employment is concentrated in agriculture (male: 75.7%, female: 79.5 %).
Non-agricultural activities are often (incorrectly) coded as “Personal services n.e.c.” (ISIC Rev. 2 code 9599).
Small-scale pilot survey in Glen View, Harare, shows:
Women are concentrated activities with low barriers to entry and low returns (low-end street vending, apparel, etc).
Men are more likely to be in higher-end vending (electrical goods, roast mealies, marihuana, etc), taxi operators, furniture production and repair of motor vehicles & household goods.
Weekly cash earnings of men (mean: US$33, median: US$9) are higher than of women (mean: US$11, median: US$4.60).
Gender differences contribute to high inequality (Gini: 0.72).

8. Gender differences in working time
Do men work more hours than women – or less?
Answer depends on concept of work:
‘More’, if only employment is considered (i.e. SNA work) .
‘Less’, if unpaid domestic work is included (i.e. non-SNA work).

9. Informal employment in Zimbabwe’s 2009 LFS
In 2004 LFS categories ‘permanent employees’ vs. ‘casual/temporary employees’ were used as proxy to distinguish between formal and informal employees.
New section in 2009 LFS on social security to capture job-based concept of informality (ICLS 2003).
Informal employees are those employees who lack at least one of the following:
Employer contributions to pension fund, or
paid annual leave, or
paid sick leave.
Lack of written contract as additional indicator.

10. Inclusion of secondary jobs in 2009 LFS
Stakeholder workshop in July 2008 recommended inclusion of a new section on secondary jobs:
Most formal jobs fail to sustain households, so some formal employees also hold an informal job to supplement income.
Helps to properly measure the extent of informal employment.
Data are potentially relevant from a gender perspective.

11. Gender sensitization, training and analysis
Gender sensitization in conjunction with training for 2009 LFS field staff to ensure that data collection is gender sensitive.
To be the duty of the Internal Gender Committee that is chaired by the department’s gender focal person, whose mandate is to spearhead gender mainstreaming at the CSO.
Gender and child analysis training for CSO Statisticians & gender focal points in line ministries and parastatals.
Hope for in-depth analysis of the 2009 LFS to shed light on gender and informality in Zimbabwe.
Plans underway to set up a Gender Statistics Committee to be chaired by national gender machinery.

12. Conclusions: Generating labour market statistics that are relevant for gender analysis
Sex disaggregation of traditional labour market statistics can be insufficient for gender analysis:
E.g. unemployment rate suggests gender equality where deep inequality between men and women exists.
Informal employment is one useful way to capture difference in type of jobs held by men and women.
Zimbabwe’s example shows that Labour Force Surveys are a good tool to collect gender relevant statistics.
In line with ICLS (2003) ‘Checklist of good practices for mainstreaming gender in labour statistics’:
Collect labour statistics on all topics relevant to gender, e.g. informal employment, working time, non-SNA work.