1. Surveys: Using LSMS, HBS, LFS and SILC for Poverty Analysis
Rachel Smith-Govoni
April 4, 2008

2. Goals and Needs Goals: Measure the poverty impact of economic policy
Measure the distributional impact of economic policy
Needs:
Rely heavily on household survey data

3. Household Surveys - types
Single Topic
Labour Force Surveys( LFS) (ILO)
Census – national, 10 years – Serbia 2002
In-between
Multi-topic
No such thing as a single topic survey really, so artificial even the basic labor force survey collects some demographic (age, sex, often relation to household head) and education (yrs of schooling, degrees). But the overall purpose is to measure outcomes or carry out analysis in one sector. No one is going to use it to discuss the demographic profile of the country (LFS sample doesn’t include the whole population so couldn’t use this).

4. Household Surveys In-between Agricultural Surveys (FAO)
Single Topic
In-between
Agricultural Surveys (FAO)
Demographic and Health (DHS)
Household Budget Surveys (HBS)
Multi-topic
Not all alike
Each developed for specific purposes, don’t always work for other purposes

5. Household Surveys Multi-topic Single Topic In-between
Multiple Indicator Cluster Survey UNICEF
Living Standards Measurement Study
Survey on Income and Living Conditions (SILC, EU)
MICS: World Summit for Children in 1990 New York and subsequent declaration and Plan of action for children, requires monitoring of 75 indicators largely on status of children but also a bit on women and families; one sub-group, but a variety of indicators (health, education, labor, access to sanitation etc.)
NHSCP: UN program- largely led to expanded labor force surveys in LAC-
LSMS: World Bank Initiative:

6. Census Purpose Accurate measure of the population of a country
Geographic distribution of the population
Basic demographic information

7. Census Not a sample Universal coverage No sampling errors in estimates
Some corrections for non-response may be needed
Not many items
Basic need: only once every 10 years so can’t monitor inter-censally, indicators change slowly, subjective assessment of needs, weighting problem

8. Census
Content
Demographic information: age, sex, race/ethnicity, family and household composition
Housing information
Others: basic education, labour, disability
Census

9. Census
Albania: (1989)
BiH 1991 (1981)
Montenegro (1991)
Serbia 2002
Kosovo 1981
Limited monitoring
Census
Limited use if looking at impact of policies affecting taxes, tariffs or pricing

10. Census Uses Sample frame
Link with household surveys for small area estimation (data mapping)
Provides the frame from which all samples for household surveys are dr

11. Two types of errors: Sampling and non-sampling Time Cost Training
Non-response
Census

12. Sampling vs. non-sampling errors
Total error
Non-sampling error
Sampling error
Sample size

15. Labour Force Survey (Anketa o radnoj snazi – ARS)
Purpose
Direct measurement of unemployment
General characteristics of the labour force

16. Labour Force Survey Sample Relatively large samples
Desire to disaggregate to different geographic areas
Individuals of working age

17. Labour Force Survey Content Characteristics of the labour force
Demographics
Education
Sectoral distribution of employment
Degree of formality
Seasonal
Income

18. Labour Force Survey Limitations:
LFS typically capture partial, not total, income, under-estimate welfare
Measurement Error - Labour income measurement error at both ends of the distribution

19. LFS in Latin America Item non-response
Salaried
Self- employed
Employer
Mean non- response rate
3.9%
10.2%
12.0
Source: Feres, 1998

20. Household Budget Survey (Anketa o potrosnji domacinstava – APD,
Inputs to National Accounts on consumer expenditures
Track changes in expenditures over time
Weights for the Consumer Price Index
(Indeks Potrosackih Cijena)

21. Non response rates (Eurostat Household Budget Surveys, 2003)
Bulgaria: 39.7%
Estonia, 44%
Hungary, 58.8% before replacement
Romania, 21.6 %
Sample
Usually medium size sample
High non-response rates

22. Household Budget Surveys
Content
Total Income
Total Consumption - diary
Short Demographics
Central Europe: agriculture
Limited health and education

23. Household Budget Surveys
Poverty Measurement
Consumption based welfare measure
Purpose of an HBS survey is NOT to measure welfare but to precisely measure mean expenditures on specific goods and services
These are conflicting goals

24. Household Budget Surveys
Poverty Measurement
Shortest possible reference periods
Minimize number of omitted expenditures
Good for precise measurement of regional or national means
Because of lumpy nature of purchases, not good for comparisons among households

25. Multi-topic Household Surveys
Those with a focus on measuring poverty
Survey on Income and Living Conditions (SILC)
Living Standards Measurement Study Surveys (LSMS)

26. Multi-topic Household Surveys
Purpose
Analysis of welfare levels and distribution
Study links between welfare levels and individual and household characteristics, economic, human and social capital
Social exclusion
Levels of access to, and use of, social services, government programs and spending

27. Multi-topic Household Surveys
Sample
Small sample sizes
Trade-off issue: Quality and cost considerations
Limits ability to assess programs or policies that affect small groups or small areas (over- sample)
Infrequent in many countries

28. LSMS 2002, 2003, 2007 Content 1 household composition 2 housing
3 individual demographics
4 health
5 labour
6 work history
7 social programs
8 migration
9 values and opinions
10 consumption
11 agriculture

29. Multi-topic Household Surveys
Poverty Measurement
Total consumption
Longer reference periods
Able to calculate use value of durables and housing
Total income
Suffers from standard measurement errors

30. Designs for surveys across time
Repeated cross sectional surveys
(e.g. Household Budget Survey, Labour Force Survey)
Common design for large government surveys
New sample drawn for each survey
Carry similar questions each year
Used for trend analysis at aggregate level

31. Designs for surveys across time
Cohort Studies
Sample often based on an age group
Follow up same sample members at fairly long intervals
Developmental data as well as social and economic data
Data from parents, teachers associated with cohort member

32. Designs for surveys across time
e.g. Panel Study of Income Dynamics, USA – since 1968!
Living in BiH , LSMS Albania ,
LSMS Serbia
Draw a sample at one point in time and follow those sample members indefinitely (or as long as the funding continues)
Collect individual level data in household context
Repeated measures at fixed intervals (annual data collection)

33. Advantages of Panel Data
Comparison of same individual over time - outcomes
Track of aspects of social change
Facilitates study of change and causal inference
Minimise the problem of inaccurate recall
Compare a person’s expectations with real change
Look at how changes in individuals’ behaviour affects their households
Identifies the co-variates of change and the relative risks of particular events for different types of people

34. Changes in Employment Status
A: CROSS-SECTIONAL INFORMATION
Unemployed
2001
2007
Net change -
0.1% unemployed
Employed

35. Changes in Employment Status
B: PANEL INFORMATION
continuously
unemployed
3.2%
Still Unemployed
Unemployed
unemployed 2001 but employed 2007
5.1%
employed 2001
but unemployed 2007 5%
Employed
Still Employed
continuously
employed
86.7%
2001
2007
Net change - 0.1% unemployed
Actual change is 10.1

36. Balkan Examples
Albania - 15% of the unemployed in 2002 had made the transition to formal sector employment by 2004
BiH - About half who were poor in 2001 remained poor in Many individuals moved out of poverty.
(Cross section headcount 18% for both years)

37. Employment and the labour market
Unemployment duration and exit rates
Do the unemployed find stable employment?
The effect of non-standard employment on mental health
Temporary jobs: who gets them, what are they worth, and do they lead anywhere?
Family and Household
Patterns of household formation and dissolution
Breaking up - finances and well-being following divorce or split
The effect of parents’ employment on children's educational attainment

38. A Sample
Concept of ‘longitudinal household’ problematic for a panel - households change in composition over time or disappear altogether
Individual level sample

39. Following rules All members of households interviewed at Wave One
Children born to these original sample members
Original members are followed as they move house, and any new individuals who join with them are eligible to be interviewed
New sample members are followed if they split from the original member

40. Questionnaire design Core content carried every wave
Rotating core questions
One-off variable components
lifetime job history
marital and fertility history
Variable questions to respond to new research and policy agendas

41. Attrition in panel surveys
Inevitable to some extent but can be minimised
Multiple sources of attrition in a panel
refusal to take part
respondents move and cannot be traced
non-contacts
Worry is potential bias if people who drop out differ significantly from those who stay in

42. UK Panel Wave 1 Respondents Wave-on wave re-interview rates

43. Fieldwork respondent incentives as a ‘thank-you’
extended fieldwork period for ‘tail-enders’
refusal conversion programme
tracking procedures during fieldwork
panel maintenance between waves
Change of Address cards to update addresses
mailing of Respondent Report
details of contacts with respondents between waves

44. The user database Longitudinal data is complex
Provide users with database structure which enhances usability
Consistent record structure over time
Key variables for matching and linking data cross wave
Consistent variable naming conventions

45. Conclusions
Longitudinal panel data allows us to answer research questions that cannot be answered with with cross-sectional data
Provides a different view of the world - see process through the life-course not just a static picture
Is complex (but so is the real world) - so needs to be well designed and conducted with sufficient resources to be successful

46. Final points
Welfare: household surveys- always missing the homeless, street children, institutionalized population
No one survey can meet all needs, review its purpose, coverage, content and quality before using
Need a system of surveys that meets the needs of data users