Post on 28-Dec-2015
United Nations Economic Commission for EuropeStatistical DivisionUnited Nations Economic Commission for EuropeStatistical Division
Engendering Labour Statistics
UNECE Statistical Division
- UNECE Statistical Division Slide 2
Working age
Population
Labour Force
Outside labour force(not active)
Employed UnemployedHousework Study Pension Other
By occupation
By industry
By status
Segregation
- UNECE Statistical Division Slide 3
Working age
Population
Labour Force
Outside labour force(not active)
Employed UnemployedHousework Study Pension Other
Activity rate
Unemployment Rate
- UNECE Statistical Division Slide 4
Working age
Population
Labour Force
Outside labour force(not active)
Employed UnemployedHousework Study Pension Other
Employment Rate
- UNECE Statistical Division Slide 5
Working age
Population
Labour Force
Outside labour force(not active)
Employed UnemployedHousework Study Pension Other
Labour Force Surveys, Census, Surveys
LFS, Census, Registers
Enterprise surveys,
LFS, Census
- UNECE Statistical Division Slide 6
How can we make the process of collecting, processing and disseminating employment
statistics more gender sensitive?
Engendering Labour Statistics
- UNECE Statistical Division Slide 7
Where is the gender bias?
Man-biased data collection (question wording)
Inadequate definitions and concepts Gender-biased responses Gender-biased enumerators Gender-blind content of the data collection
Engendering Labour Statistics
- UNECE Statistical Division Slide 8
Question wording
• Formally there is a clear distinction between employed and non employed population
• ILO definition: a person is currently employed if he/she has worked at least one hour the week previous the survey
• Work: for income (cash or kind) or unpaid production of goods
Engendering Labour Statistics
- UNECE Statistical Division Slide 9
Question wording
Prior 1994, US Labour Force Survey (LFS): “What were you doing most of last week—working, keeping house, or something else?”
For women who primarily kept house but also did some paid work, this question appears to have
led to some underreporting of work
Now, US LFS: “Last week, did you do any work for pay or profit?”
Following the redesign, the survey found an increase in the number of workers, primarily women, who usually worked fewer than 10
hours per week
Engendering Labour Statistics
- UNECE Statistical Division Slide 10
Question wording
Can the LFS questions be improved to include all women and men who do work according to the ILO definition?
Do the current questions capture persons who have “atypical jobs”?
Engendering Labour Statistics
- UNECE Statistical Division Slide 11
Question wording
Concepts should be operationalized in a way that respondents can understand it.
What does work mean?
What does child care mean?
Cognitive testing, focus groups help to make sure that the concepts used are
interpreted correctly
Engendering Labour Statistics
- UNECE Statistical Division Slide 12
Concepts and definitions
• Women’s work tend to be more heterogeneous than men’s work, but standard classifications are more one-dimensional
• Some unit of analysis hide the individual (and therefore the gender) dimension• household, farm, economic unit
Engendering Labour Statistics
- UNECE Statistical Division Slide 13
Gender-biased responses
• Male respondents may fail to report women
• Respondents may not understand the content of the questionnaire
• Respondent give wrong answers to meet social norms
Engendering Labour Statistics
- UNECE Statistical Division Slide 14
Meeting social norms: US Survey Example
The following questions and results were obtained in an American survey
% 'Yes'
53Have you ever heard of the Taft-Pepper Bill concerning veteran's housing (no such bill!)
16
25
33
Have you ever heard of the famous writer, John Woodson? (no such writer!)
Have you ever heard of the Midwestern Life Magazine? (no such magazine!)
Do you recall that, as a good citizen you voted last December in the special election for your state representative? (no election!)
8Have you ever heard the word AFROHELIA? (no such word!)
Sometimes this type of bias is called prestige error
Engendering Labour Statistics
- UNECE Statistical Division Slide 15
Gender-biased enumerators
• Enumerators may introduce his/her personal view (norm) in the interview • Poor training• Social pressure• Lack of interest
• Enumerators may establish poor relationship • Not gender-correct language• Body language
Engendering Labour Statistics
- UNECE Statistical Division Slide 16
Enumerator-bias: Example Australian Survey
Average number of sex partners reported
• By women who were watched as they filled in their survey answers: 2.6;
• By women who knew they were completely anonymous: 3.4;
• By women who thought they were attached to a lie detector: 4.4 Sydney Morning Herald, August 31, 2003
Engendering Labour Statistics
- UNECE Statistical Division Slide 17
Gender-blind content
What are the gender issues in employment?
……….Next activity………….
Engendering Labour Statistics
- UNECE Statistical Division Slide 18
Thank you !