Transcript Labor Market Information Systems and Data Analysis Kathleen Beegle Development Economics Research Group And Living Standards Measurement Study (LSMS) group World Bank April 7, 2009

Labor Market Information
Systems and Data Analysis
Kathleen Beegle
Development Economics Research Group
And Living Standards Measurement Study
(LSMS) group
World Bank
April 7, 2009
1
Data for labor analysis: what can
you do and how can you do it?


Focus on quantitative analysis
 Qualitative analysis is another method of
analysis which is not part of this discussion
 When under-taking new quantitative data
collection (and even when doing analysis of
secondary analysis), you would probably
always do some qualitative analysis.
Focus on data needs for analytical work
2
Labor data


Many sources of data for labor market analysis.
How/if these data can be used will depend on several
factors:

Who is eligible to be included?


Who reports information?
 Household head reporting for all individual members




Firm manager reporting on individual staff
What information is reported?


census v. survey v. administrative records
Unpaid family labor
Women’s domestic work
How often is the data collected?
Can it be merged/combined with other data?

LFS combined with rainfall data
3
Types of data

Population and Housing census




In theory, all residents of the country with
limited information (age, sex, education,
migration, “main activity”)
Every 10 years
Often source for sampling frame for
household surveys
Difficult to get unit-record data but means
are often readily available
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Types of data

Household survey data


Topical surveys
 Household Budget Surveys (HBS), Income and
Expenditure Surveys (IES)
 Labor Force Surveys (LFS)
 ILO SIMPOC surveys (Statistical Information and
Monitoring Programme on Child Labour part of
IPECL)
 Demographic and Health Surveys
Integrated Household Surveys (LSMS, FLS)
include income & non-income dimensions of living
standards
 www.worldbank.org\lsms
 www.rand.org\FLS
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Types of data

Administrative data (records)


From companies or from governments (local,
regional, national)
Firm/enterprise surveys


rru.worldbank.org/EnterpriseSurveys/
Rural investment climate surveys
Non-labor data is also relevant…examples:
 Price data (to deflate nominal values)
 Infrastructure information (access to
markets)
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Data producers

National statistical office


Multi-laterals: ILO, World Bank, IDB


Not systematically public
Researchers


policies of access to unit-record data vary
Not systematically public
How to find data: not so easy!


IHHSN
 www.internationalsurveynetwork.org/home
WB’s DDP (e.g. Africa Household Survey Data
bank)
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A “simple” labor question may
embed many demands on data



Single topic surveys may lack breadth of
topics (eg: measure of poverty status)
LSMS surveys may lack depth (eg:
willingness to co-pay for health insurance,
pension contributions for civil servants)
Administrative data: little background
information on respondents (eg:
education level)
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Unemployment & Poverty
45
40
35
30
25
20
15
10
5
0
Segovia
Poverty
Unemployment
West
Managua
South
Central
North
Atlantic
Nicaragua, 1993
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UNE and Poverty: what data would
you need?

“ILO” definition of unemployment





Did you work (for at least 1 hour) in the last 7 days
 Does this include working as unpaid family
labor on the hh farm?
 Does this include the wife who worked 2
hours in the hh’s non-farm business?
If no, do you have a regular job (on leave/sick) to
which you will return?
If no, have you searched for work in the past 4
weeks?
3+ questions, asked of all household members.
In low-income countries, you find few who
qualify as unemployed
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UNE and Poverty: what data would
you need?


Poverty status of household
(detailed consumption module)
Sufficient sample sizes in each
region to generate reliable
unemployment statistics
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Employment and Poverty Indicators
Sample Means
Poor below
food poverty
line
Between food
poverty line and
poverty line
Nonpoor
Total
Household members who
have worked during the
past week (%)
39.4
43.6
46.6
44.8
Number of jobs per
household member during
the past week
0.5
0.6
0.7
0.6
Average monthly wage
from primary occupation
65,948
99,706
103,438
98,401
5.8
5.8
4.5
5.0
Children under 15 who
were employed during the
past week (%)
Cambodia 1997
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Employment and Poverty: What data
would you need?



Poverty status of household
Work status of individual household members,
including children under 15 (often missing)
Information on working and number of jobs


Wage data




wrt to some time period – last week, month year
imputed wages for self-employed?
In-kind value of wage payments (housing, food)
Difficult to annualize
CPI to convert price data from nominal to real values
(spatial and temporal price data)
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Private Rates of Return to Schooling by Level of
Education
Education Level
All
Males
Females
Public
Sector
Primary (v. less
than primary)
13
4*
21
-27*
23
Secondary (v.
primary)
5
4
6
6
4
Vocational (v.
primary)
4
5
5
6
**
University (v.
secondary)
11
10
12
11
**
*Not statistically significant
Private
Sector
**Not enough observations
Vietnam 1992/93
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RTE: What data would you need?



Sector of work (maybe including
second or thirds jobs?)
Wages (real values)
Education level
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Time Spent on Activities
Average Minutes
Fetching wood
Fetching Water
Child care
Urban
Rural
Accra
Other
Coastal
Forest
Savannah
Male
9
51
21
28
33
Female
5
45
30
33
46
All
6
47
27
32
43
Male
22
34
26
24
44
Female
27
35
32
40
58
All
25
35
30
38
54
Male
170
95
146
101
84
Female
251
182
215
243
144
All
230
167
203
209
129
Ghana 1998-99
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Time Use: What data would you need?

Reported time use across distinct
sub-categories of activities asked of
every individual member of the
household

Fetching water and collecting firewood:
does this include waiting time?
 does it include walking to the source


What if farming is combined with childcare?
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What data would you need?



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MDG 3: Share of women in wage
employment in the nonagricultural
sector
Impact of credit access on entry
into self-employment
Ex-post impact of minimum wage
legislation
Ex-ante impact of proposed changes
changes to pension system
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Data analysis of labor issues:
Challenges

What if? Posing hypothetical situations to
respondents (willingness to
pay/contingent valuation)



Consistency in definitions across time
and space
Relevance of international definitions


Reliability of complicated questions on
tradeoffs today with future returns
Unemployment in SSA v. ILO definition
Impact: Identifying appropriate control
groups
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Data analysis of labor issues:
challenges

Seasonality



Means are deceiving
How to measure labor bottlenecks?
Rare events: Difficult to
measure/assess rare events in largescale LSMS-type surveys



Impact of HIV/AIDS on absenteeism
LM outcomes for disabled
Children involved in dangerous work
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Malawi Time Use 2004
Male 15+
Female 15+
%<10
%<10
Mean
Median
hrs
Mean
Median
hrs
Mar-04
27.6
24
28.8
27.2
22.5
28.3
Apr-04
29.6
28
20.2
25.8
23.5
26.6
May-04
26.4
24
27.7
25.4
23.5
23.7
Jun-04
27.7
28
24.9
25.5
22
29.1
Jul-04
27.0
24
23.1
23.2
20
30.9
Aug-04
26.3
24
25.3
24.3
21
26.1
Sep-04
28.2
24
23.6
25.1
22
26.8
Oct-04
29.0
28
21.7
28.5
27
19.3
Nov-04
31.8
31
16.2
31.0
30
18.3
Dec-04
35.0
35
8.5
32.3
32
14.1
Jan-05
33.5
32
10.8
31.7
30.5
12.0
Feb-05
28.9
28
18.2
27.8
26
20.0
Mar-05
29.9
29
20.1
26.8
23.5
24.9
Source: Malawi IHS2. Note: Total time in last week: fetching water, collecting
firewood, working on household farm, working in household non-farm business, and
wage or salary work. Includes unpaid family labor in household income generating
activities.
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Conclusions
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Lots of data, but (usually) no one source
has it all
Search for your data: good literature
review may reveal some ideal data
Be creative. combine data across
sources (LSMS with administrative data)
Be realistic about what you can and
can’t answer
Pay attention to the details of your data
source
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Web Source of Information on
Household Surveys with Labor Data
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LFS
 www.statistics.gov.uk/statbase/Product.asp?vlnk=1537
 www.census.gov
 www.ilo.org/dyn/lfsurvey/lfsurvey.list?p_lang=en
LSMS
 www.worldbank.org/lsms
DHS
 www.measuredhs.com
MICs
 www.unicef.org/statistics/index_24303.html
 www.childinfo.org
IES/HBS
 www.bls.gov/cex/home.htm
 europa.eu.int/estatref/info/sdds/en/hbs/hbs_base.htm
CWIQ
 www.worldbank.org/afr/stat
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
http://www.ilo.org/dyn/lfsurvey/lfsu
rvey.list?p_lang=en
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