Surveys: Using LSMS, HBS, LFS and SILC for Poverty Analysis

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

4. Household Surveys • Single Topic • In-between • Agricultural Surveys (FAO) • Demographic and Health (DHS) • Household Budget Surveys (HBS) • Multi-topic

5. Household Surveys • Single Topic • In-between • Multi-topic • Multiple Indicator Cluster Survey UNICEF • Living Standards Measurement Study • Survey on Income and Living Conditions (SILC, EU)

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

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

9. Census Albania: 2001 (1989) BiH 1991 (1981) Montenegro 2003 (1991) Serbia 2002 Kosovo 1981 Limited monitoring 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)

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

12. Sampling vs. non-sampling errors Total error Sampling error Non-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 AmericaItem non-response 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 2001-2004, LSMS Albania 2002-2004, LSMS Serbia 2002-2003 • 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. Net change - 0.1% unemployed 2001 2007 Changes in Employment Status A: CROSS-SECTIONAL INFORMATION Unemployed Employed

35. 3.2% continuously unemployed 5.1% unemployed 2001 but employed 2007 5% employed 2001 but unemployed 2007 86.7% continuously employed Changes in Employment Status B: PANEL INFORMATION Still Unemployed Unemployed Employed Still Employed 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 2004. 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 RespondentsWave-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. Finalpoints • 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