Transcript Employment Indicators Second Inter-Agency and Expert Group Meeting (IAEGM) on Gender Statistics in the Arab Region, Beirut, 12-14 October 2009 International Labour Office Department of.

Employment Indicators
Second Inter-Agency and Expert Group Meeting (IAEGM)
on Gender Statistics in the Arab Region,
Beirut, 12-14 October 2009
International Labour Office
Department of Statistics
List of indicators
1.4.
Growth rate of GDP per person employed – labour
productivity
1.5. Employment to population ratio
1.6. Proportion of employed people living below the
national poverty line – the working poor
1.7. Proportion of own account and contributing family
workers in total employment – vulnerable
employment
1.1.5. Number of hours of unpaid work per week for 18-44
years old
1.1.9. Proportion of working children (5 to 17 years old)
International Labour Office
Department of Statistics
List of indicators
(cont’d)
3.1.1. Proportion of women working in agriculture
3.1.2. Share of women in wage non-agricultural employment
3.1.3. Share of women in employment (by industry, size of
establishment, institutional sector, incl. informal sector)
3.1.4. Gender pay gap
3.1.5. Gender gap in unemployment
3.1.6. Gender gap in youth unemployment
3.1.8. Maternity benefits as a percentage of earnings
3.4.10.Proportion of workers with health insurance
3.4.11.Proportion of workers with retirement benefits
International Labour Office
Department of Statistics
For each indicator, we will
discuss …
1.
2.
3.
4.
How we will define/calculate it
How to interpret changes
What is the gender issue
What are the most important conceptual limitations and
only measurement limitations which are specific
5. What are the possible sources
International Labour Office
Department of Statistics
1.4. Growth rate of labour
productivity
(GDP at constant prices per person employed)
• Indicator for MDG goal 1, Target 1B
• Calculation:
Labour productivity t – Labour productivity t-1
Labour Productivity t-1
->by sex?
• Interpretation:
– Labour productivity represents the amount of output achieved
per unit of labour input (-> GDP / person employed);
– An increase in the growth rate can mean increased efficiency of
labour, of capital and/or of intermediate inputs
• Gender issue: efficiency of women’s labour should be as
high as men’s
International Labour Office
Department of Statistics
1.4. Growth rate of labour
productivity
(GDP at constant prices per person employed)
• Limitations
– A change may be due to factors other than labour, so other
indicators are also needed to interpret it, e.g., employment to
population ratio
– Productivity cannot be disaggregated by sex (yet!!) so this
indicator cannot be used for gender studies (yet ---)
• Sources:
– For the numerator and denominator : ES, HS, AR
International Labour Office
Department of Statistics
Growth rate of labour
productivity
International Labour Office
Department of Statistics
1.5. Employment to
population ratio
• Indicator for MDG goal 1, Target 1B
• Calculation:
Total employment
* 100
Working age population
by sex and rural/urban areas
• Interpretation: An increase means that the economy is
increasingly able to provide employment to people
• Note: the working age population relates to the
population above a certain age to be determined
nationally
International Labour Office
Department of Statistics
1.5. Employment to
population ratio
• Gender issue: Comparing men and women ratios
provides an idea of equal employment opportunities --ratio should be equally high for men and women
• Limitations
– Says nothing of
– Says nothing of
– Says nothing of
employment ---
quality of employment
volume of employment
reasons that women or men are or are not in
is it choice?
• Sources:
– In theory, any source: HS, ES, AR
– In practice, it is best if numerator and denominator come from
the same source, therefore HS are best
International Labour Office
Department of Statistics
Employment to population
ratio in 2007, by sex
80
70
60
Developed Economies and
European Union
%
50
Sub Saharan Africa
40
South Africa
30
20
10
0
MF
M
F
Source: ILO, Trends Econometric Models, May 2009; and Stats SA, LFS, 2007
International Labour Office
Department of Statistics
Employment to population
ratio
2007, population
15+
%
Employment-topopulation rate
Labour force
participation
rate
Unemployment
rate
South Africa
Sub-Saharan
Africa
Developed
economies
41.3
65.2
54.5
53.4
70.7
57.8
22.6
7.7
5.7
Source: ILO, Trends Econometric Models, May 2009; and Stats SA, LFS, 2007
International Labour Office
Department of Statistics
Employment to population
ratio (15-24 yrs old)
2007,
pop. 15-24
%
Employment-topopulation rate
Labour force
participation
rate
Unemployment
rate
South Africa
Sub-Saharan
Africa
Developed
economies
15.9
50.1
44.4
30.0
56.5
50.6
46.9
11.4
12.2
Source: ILO, Trends Econometric Models, May 2009; and Stats
SA, LFS, 2007
International
Labour
Office
Department of Statistics
1.6. Working poor
• Indicator for MDG goal 1, Target 1B;
• Calculation:
Working poor = Poverty rate * Labour Force
Working poor rate = Poverty rate * Labour Force
Employment
• Interpretation: an increase indicates that there are more
persons whose work does not provide an income high
enough to get them out of poverty
• Note: the poverty rate relates to persons living below a “poverty
line” as a percentage of the total population;
– The poverty line is to be determined nationally
– For international comparisons it can be a fixed value, e.g. 1.25 $ PPP
per day
International Labour Office
Department of Statistics
1.6. Working poor
• Gender issue: there are probably more women workers
than men workers who are poor ---- the indicator
should decrease more (or increase less) for women than
for men
• Limitations
– It is a derived estimate that assumes that poor persons are
equally likely to be in the labour force than non-poor persons --and that if they are poor they cannot be unemployed
– Poverty cannot be disaggregated by sex (yet!)
– The working poor rate will be very close to the poverty rate itself
---- does not add information
• Sources:
– For the numerator: IES; For the denominator: any source
International Labour Office
Department of Statistics
Working poverty rate US$
1.25, by region (1997 and 2007)
70.0
60.0
50.0
40.0
%
1997
2007
30.0
20.0
10.0
SubSaharan
Africa
North
Africa
Middle
East
Latin
America
and the
Caribbean
South Asia
SouthEast Asia
and the
Pacific
East Asia
Central
and South
Eastern
Europe
0.0
Source: ILO, Trends Econometric Models, October 2008
International Labour Office
Department of Statistics
1.7. Vulnerable employment
rate
•
•
Indicator for MDG goal 1, Target 1B
Calculation:
own-account workers + contributing family workers * 100
total employment
•
•
->by urban/rural, sex
Interpretation: a decrease indicates that there are less
persons in vulnerable employment
Gender issue: there are probably more vulnerable women
workers than men workers --- the indicator should
decrease more (or increase less) for women than for men
International Labour Office
Department of Statistics
1.7. Vulnerable employment
rate
• Limitations
– It assumes that all own account workers are vulnerable --- many
may be professionals or technicians
– It requires than unpaid own account workers (i.e., subsistence
workers) be properly identified ---- may underestimate the rate
for women more than the rate for men
• Sources:
– HS
International Labour Office
Department of Statistics
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Vulnerable employment rate
Vulnerable employment rate (countries ranked by level of GDP/capita)
100.0
80.0
60.0
40.0
20.0
0.0
Source: ILO, Key Indicators of the Labour Market, 5th ed., 2007
International Labour Office
Department of Statistics
Status in employment,
Namibia (1997 and 2004)
Share in total employment (%)
80.0
70.0
Female 1997
Female 2004
Male 1997
Male 2004
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Contributing
family workers
Own-account
workers
Employers
Source: Namibia LFS, Ministry of Labour and Social Welfare, 1997 and 2004
Employees
International Labour Office
Department of Statistics
Vulnerable employment rate and
education level, Namibia (2004)
Share of vulnerable employment (%)
35
30
25
Vulnerable employment
20
15
10
5
0
No
education
Primary Junior sec. Senior sec. After Std. University
education education education
10
Certificate
Post
Graduate
International Labour Office
Department of Statistics
Vulnerable employment and
union density, Namibia (2004)
60.0
Both sexes
Males
Females
Union density (%)
50.0
40.0
30.0
20.0
10.0
0.0
Total
Contributing
family workers
Own-account
workers
Employers
Private
employees
Government
employees
International Labour Office
Department of Statistics
Vulnerable employment and
social security, Namibia (2004)
100.0
Both sexes
Males
Females
80.0
60.0
40.0
20.0
0.0
Total
Contributing Own-account
family work
workers
Employers
Private
employees
Government
employees
International Labour Office
Department of Statistics
Vulnerable employment rate
Source: ILO, Trends Econometric Models, February 2009
International Labour Office
Department of Statistics
1.1.5. Number of hours of
unpaid work per week
for 18-44 years old
• Definition: number of hours spent on unpaid household
service work
– Main characteristic: the output of these services is consumed by
the household to which the services are rendered
– Activities are related to the maintenance, protection and care of
the household’s members, including pets, premises and
equipment --- include activities common to maids, cooks,
waiters, valets, butlers, laundresses, gardeners, gatekeepers,
chauffeurs, caretakers, governesses, babysitters, tutors and
personal secretaries.
->by sex and presence of small children
• Interpretation: a decrease indicates that activities are
done more efficiently or done by others, including by
paid labour
International Labour Office
Department of Statistics
1.1.5. Number of hours of
unpaid work per week
for 18-44 years old
•
•
•
•
Gender issue: women are probably spending more time
than men in these activities --- the indicator should
decrease more (or increase less) for women than for men
Proposal: an indicator about time spent by women as
proportion of time spent by men on these activities may
be simpler
Limitations --- expensive to measure
Sources:
–
TUS, LFS with an “activity list” that includes these types of
activities
International Labour Office
Department of Statistics
1.1.6. Proportion of working
children (5 to 17 years old)
• Definition: children in productive activities are those
engaged in any activity falling within the general
production boundary as defined in the System of
National Accounts (SNA)
– Children in employment
– Children in other productive activities --- i.e., in unpaid
household services
• Calculation:
Number of children in productive activities (5-17) * 100
Number of children (5-17)
By sex
• Interpretation: a decrease indicates that less children are
engaged in productive activities International Labour Office
Department of Statistics
1.1.6. Proportion of working
children (5 to 17 years old)
•
Gender issue:
–
–
•
•
•
There are probably more girls engaged in productive activities
than boys --- the indicator should decrease more (or increase
less) for girls than for boys
On the other side, there are probably more boys who are
engaged in employment than girls, or in worst forms of child
labour
Proposal: distinguish between children in employment
and children in other productive activities
Limitations --- expensive to measure, difficult to identify
all children who work, especially if unpaid
Sources: General HS with a low age threshold;
specialised child labour surveys International Labour Office
Department of Statistics
3.1.1. Proportion of women
working in agriculture
• Definition: employment in agriculture units, including
unpaid family work and subsistence work
• Calculation:
Number of women employed in agriculture * 100
Number of persons employed in agriculture
• Interpretation: An increase in paid employment in
agriculture together with a decrease of unpaid family
work and subsistence work in agriculture will mean that
women are accessing better quality employment in
agriculture
International Labour Office
Department of Statistics
3.1.1. Proportion of women
working in agriculture
• Gender issue:
– Women tend to be more numerous among the most vulnerable
forms of employment in agriculture
– Women’s unpaid employment tends to be badly measured, the
bulk of which is in agriculture
• Proposal: distinguish between status in employment
categories
• Limitations
– Since it is not clear the extent to which women’s employment is
properly measured, it is not clear what the figures will really
mean
• Sources: HS -> ideally TUS and specialised agriculture
surveys
International Labour Office
Department of Statistics
3.1.3. Share of women in
employment
• Calculation:
Number of women employed in category x * 100
Number of persons employed in category x
– Where “x” can be a particular industry, size of establishment,
and institutional sector, including the informal sector (as a
subsector of the household sector)
• Interpretation: will indicate labour market segregation
• Gender issues: it can be expected that women will be
concentrated in service oriented industries, in small
establishments and in the government sector --• Limitations: No clear interpretation
• Sources: HS
International Labour Office
Department of Statistics
3.1.4. Gender Pay Gap, GPG
• Calculation:
Hourly wages of men – Hourly wages of women * 100
Hourly wages of men
-> by occupational group, education level and seniority
• Interpretation: a decrease will mean that women’s
wages are getting closer to men’s --- which may mean
that they are increasing more (or decreasing less) than
men’s wages. Value to attain= 0.
• Gender issues: in average, women earn less than men in
all countries of the world, even after correcting for
occupations, hours of work, and skills
International Labour Office
Department of Statistics
3.1.4. Gender Pay Gap, GPG
• Limitations:
– Very sensitive to the definition of wages used --- the more
income components it includes, the higher the value
– Very sensitive to the worker coverage
– Very sensitive to the level of wages in a group --- the lower the
wages the lower the GPG …
• Sources: HS, ES, AR
International Labour Office
Department of Statistics
3.1.5. Gender gap in
unemployment
• Calculation:
Unemployed women * 100
Unemployed men
-> by education level, urban/rural
• Interpretation: a decrease will mean that women are
finding it less hard than before to find jobs as compared
to men; it could also mean that women are not looking
for work as much as they did, as compared with men.
• Gender issues: women generally find it harder to find
jobs as compared to men; women do not look for work
in the same way or to the same extent than men
International Labour Office
Department of Statistics
3.1.5. Gender gap in
unemployment
• Limitations:
– It does not indicate the extent to which women are finding it
hard to find jobs, which the unemployment rate would – the
indicator will probably always be below 100, as there are
probably more men than women unemployed in any given
country --- a gap of unemployment rates may be better
– It is not possible to know whether women are looking less for
work than before or are finding more work than before -- it may
be important to identify workers who want to work but do not
look for work
• Sources: HS, AR
International Labour Office
Department of Statistics
3.1.6. Gender gap in youth
unemployment (15-24)
• Calculation:
Unemployed women (15-24) * 100
Unemployed men (15-24)
-> by urban/rural
• Interpretation: a decrease will mean that young women
are finding it less hard to find jobs as compared to
young men than before; it could also mean that young
women are not looking for work as much as they did, as
compared with young men.
• Gender issues: young women generally find it even
harder to find jobs (than adult women) as compared to
young men
International Labour Office
Department of Statistics
3.1.6. Gender gap in youth
unemployment (15-24)
• Limitations: same as previous indicator, namely --– It does not indicate the extent to which women are finding it
hard to find jobs, which the unemployment rate would – the
indicator will probably always be below 100, as there are
probably more young men than young women unemployed in
any given country --- a gap of unemployment rates may be
better
– It is not possible to know whether young women are looking less
for work than before or are finding more work than before -- it
may be important to identify workers who want to work but do
not look for work
• Sources: HS, AR
International Labour Office
Department of Statistics
3.1.8. Maternity benefits as
a percentage of earnings
• Definition: relates to statutory entitlements of women
during pregnancy, childbirth and breastfeeding
• Calculation
Benefits paid during maternity leave (of at least 14 weeks) * 100
Wages that would have been paid during the same period
• Interpretation: an increase will mean that the law has
improved the entitlements of women during pregnancy,
childbirth and breastfeeding. Maximum value to attain:
100.
• Gender issue: a major reason that women leave the labour
market is childbirth; a major reason that women postpone
or avoid having children is a loss of income
International Labour Office
Department of Statistics
3.1.8. Maternity benefits as
a percentage of earnings
• Limitations:
– It does not indicate how many workers have access to this
entitlement
– It does not cover cases of maternity leave entitlements which
are shorter than 14 weeks
• Sources: Legislation
International Labour Office
Department of Statistics
3.4.10. Proportion of workers
with health insurance
• Definition: workers with health insurance are those
persons in employment who contribute to a health
scheme (private or public, statutory or not) that pays for
medical expenses or provides medical services.
• Calculation
Persons in employment who contribute to a health scheme * 100
Total employment
-> by sex
• Interpretation: an increase means that there are more
workers covered in the event of sickness or accident.
Maximum value to reach for: 100.
International Labour Office
Department of Statistics
3.4.10. Proportion of workers
with health insurance
• Gender issue: it is expected that women will have lower
health insurance coverage than men as they are in
informal employment to a larger extent than men.
• Limitations:
– Many women who are not contributing to a health plan may still
be covered by one, by virtue of their spouse status. So the
indicator does not really reflect health coverage.
• Sources: HS, AR
International Labour Office
Department of Statistics
3.4.11. Proportion of workers
with retirement benefits
• Definition: workers with retirement benefits are those
persons in employment who contribute to a pension
scheme (private or public, statutory or not) that will
provide an income when they reach a certain age
• Calculation
Persons in employment who contribute to a pension scheme * 100
Total employment
-> by sex
• Interpretation: an increase means that there are more
workers who will enjoy a pension in the event of old age.
Maximum value to reach for: 100.
International Labour Office
Department of Statistics
3.4.11. Proportion of workers
with retirement benefits
• Gender issue: it is expected that women will have lower
pension coverage than men as they are in informal
employment to a larger extent than men.
• Sources: HS, AR
International Labour Office
Department of Statistics