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 !