1. Comments on Integrating designs for economic variables
Luxembourg Income Study (LIS) asbl
17, rue des Pommiers
L-2343 Luxembourg –City
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Comments on Integrating designs for economic variables
Workshop « Integrating European Census Microdata II »
Paris, 7-10 June 2006
Teresa Munzi
Luxembourg Income Study

2. Luxembourg Income Study
Since 1983
Promote comparative research on income inequality, poverty, labour market outcomes, and social policy
Harmonizing social and economic household survey data
Disseminating the data to social science researchers through a remote access system based on the internet

3. LIS / IPUMS
Similarly to IPUMS: confronted to the task of harmonising data
from various countries  different institutional/societal setups
from various existing surveys  output harmonisation
over time  changes in original surveys
household/individual level data  confidentiality issues
some overlap in the contents  economic variables (labour market data)
Differently from IPUMS
NOT based on censuses, but a variety of household surveys
LIS harmonises data, while IPUMS standardises it

4. Labour Market variables
Very difficult to create comparable variables
Many international guidelines and recommendations, but those are usually
only applicable to data from LFS  different definitions
Rigid routing of the labour market questions  different universes

5. Activity status
Universe
Concept
Reference period

6. Activity status: definition and reference period
Any work
Main activity
At present
(or at a given date / week)
IPUMS
LIS I
LIS II
Over a longer reference period
LIS III

7. Activity status: some unclear cases
Sometimes it can be difficult to assign a specific national code (or category) to the employed, unemployed or inactive population
Persons on leave (maternity, sickness, layoff)
Persons in occupational training / trainees / apprentices
Conscripts (military or civil service)
Mixed categories
Two different approaches for these unclear categories
Follow the routing of the questionnaire  comparability is harmed
Follow some pre-determined rules  inconsistent data

8. Activity status: some guidelines
Adopt one clear definition, and try to stick to it as much as possible
Use the documentation to warn against deviations from the ideal definition
Semi-standardisation is OK, but also keep as much detail as possible in further digits (so that the users have the flexibility of treating specific categories differently)
Among the employed, if possible distinguish the different extent of work (regularly employed versus marginal/occasional employed)
The category of unemployed should not coincide with the ILO unemployed

9. Time worked Definition Weekly hours
“Usual” hours in the sense of regular and not actual during a given reference week, nor contractual (if different because of overtime)
Time worked at all jobs (NOT FT/PT modality of main job)
Includes paid work and unpaid family work, but excludes unpaid voluntary work

10. Time worked Universe and importance of getting the zeros right
Ideal case: universe = all persons who are employed
Not in the universe = zero working hours (it has a meaning!!!)
But can differ considerably (only those who are mainly employed, only those who have a regular schedule, only employees, etc.)
 An effort should be made to set to zero only the true zeros
Top-coding
Top-coding can vary a lot
Some basic top-coding (99?) should be applied to datasets with very high numbers
Importance of warning users for datasets that applied a stringent top-coding policy on hours

11. Job characteristics:
Status in employment
Occupation
Industry
Place of work
Differently from the activity status and time worked variables, these variables refer to a job and not a person: main job
No correspondence between the persons employed according to activity status and universe of job characteristics variables
If standard international classifications are not available, keep the detailed national ones

12. Some generic recommendations
LIS Golden rules:
Maximise comparability by setting clear definitions for each variable and trying to stick to them as much as possible
Document very well any deviation from the general rule/definition
Allow for maximum flexibility to the users by keeping all the available detail necessary for any other concept
Enhance user-friendliness by creating some semi-standardised codes, but keep the country-specific detail in the further digits